Tablet PC Technology for the Enhancement of Synchronous Distributed Education Abstract-In this paper, we describe how Tablet PCs are being used at Georgia Tech Savannah (GTS) to improve student learning in a distributed classroom environment. The Tablet PC is an attractive technology for use in synchronous distributed learning environments because of its mobility, and its ability to not only serve as an effective note taking device but also as a high-resolution course content viewing device and a tool for interactive assessments. The research questions addressed here are: 1) "What impact does the Tablet PC have on student perceptions of their engagement in a distributed learning environment?" and 2) "Can the Tablet PC be used to improve student learning in a distributed learning environment?" In this project, the instructor and students were given a Tablet PC to use during the semester, and surveys were administered to evaluate student attitudes about the use of Tablet PC technology as a means of receiving, processing, and learning course material. The significance of this work is that it serves as a case study on the use of Tablet PCs as an effective technology for implementing established educational practices in distributed education environments. The Tablet PC is an attractive technology for use in synchronous distributed learning (DL) environments because of its mobility and its ability to not only serve as an effective note taking device but also as a high-resolution course content viewing device. The implementation of Tablet PCs into the DL classrooms at Georgia Tech Savannah provided a general solution for improving the delivery of lecture content and providing alternative methods of in-class interactions between the instructors and students for facilitating active learning. The primary advantage of a Tablet PC over a laptop is the digital ink input modality. The use of the digital ink by the students in the class was largely dependent on the teaching style. Discussion with the faculty in this project revealed that at least one faculty member never made use of the panel submission feature of the interactive software, whereas another faculty member frequently required students to work problems in class on the Tablet PC and submit their responses. Therefore, there were some courses where it would seem that a normal laptop would have sufficed since the instructor primarily used the PC for content viewing and simple input requirements. One the other hand, for the instructors who made heavy use of the panel submission feature for doing in-class assessments, the digital ink modality was an essential feature. It was the goal of this project to provide a device that could provide instructors and students with the freedom to choose their type of interaction for which the Tablet PC was a general solution.. While it is clear that the students and instructors would largely prefer to participate in non-DL courses if given the option, the opportunity to participate in educational delivery at remote sites is still highly valued. Some of the significant conclusions presented in this article include:. . Provision of electronic notes (posted online before and/or after lecture) via the Tablet PC and Dyknow greatly reduced the frequency of in-class note-taking by students who had previously indicated a highfrequency for taking notes. Currently there is no clear indication on how this may have affected a student's performance in the class and will be investigated more fully in the future. . Use of the Tablet-PC-equipped classrooms for conducting the synchronous DL courses in this project helped to improve the overall attitude of students regarding their participation in DL. The most clearly seen improvement from the use the Tablet PCs was in the student's ability to more easily view the lecture notes being provided by the instructor since there was a direct transmission of lecture content from the instructor to the students Tablet PC. . There was a general feeling from the students that the use of the Tablet PCs during the semester had provided a slightly positive impact on their class performance. An objective look at the cumulative GPAs of the students, as well as the grades they received in the DL courses they participated in for this project, provided some evidence for this assertion. A more detailed analysis will be designed to assess the relationship between a student's historical performance in DL courses and their performance in Tablet-PC-equipped DL classrooms as the project continues to expand. Overall, the use of Tablet-PC-equipped DL classrooms has been a great success at the Georgia Tech Savannah campus. Future work will continue to monitor the impact on student learning and the pedagogy used by instructors by including an analysis of student responses on a courseby-course basis rather than the aggregate responses shown in this case study. The course-by-course analysis will allow student responses and performance to be assessed in light of course content, teaching style, and how instructors decided to use the unique capabilities afforded by the Tablet PCs and interactive software in their DL courses. Additionally, the assessment tools used in the project will be updated to gather more specific information on the frequency of use of the unique Tablet PC features as well as to modify questions related to students prior experiences in DL courses as more students are exposed to the Tablet PC technology at the campus. Tristan T. Utschig received the PhD degree in nuclear engineering at the University of Wisconsin Madison through the Fusion Technology Institute. He is currently a senior academic professional in the Center for the Enhancement of Teaching and Learning and is the assistant director for scholarship and assessment of teaching and learning at the Georgia Institute of Technology. Formerly, he was an associate professor of engineering physics at Lewis-Clark State College, Idaho, where he developed and directed the preengineering program at the college. Dr. Utschig's research in engineering education has focused on assessment at various levels from the classroom to program and institutional assessment. He has regularly published and presented work on a variety of topics including teaching diversity, using technology in the classroom, faculty development in instructional design, assessment instruments and methodologies, and peer coaching. His technical expertise involves the analysis of thermal systems for fusion reactor designs. Hayes is an associate chair in the School of Electical and Computer Engineering at Georgia Tech, the associate director for Georgia Tech Savannah, an associate editor for the IEEE Transactions on Education, and member of the SP Society Conference Board. Since joining the faculty at Georgia Tech, Dr. Hayes has become internationally recognized for his contributions to the field of digital signal processing, image and video processing, and engineering education. He has published more than 150 papers, is the author of two textbooks, and has received numerous awards and distinctions from professional societies. His research interests are in the areas of face recognition, image and video processing, adaptive signal processing, and engineering education. In 1992, he was elected as a fellow of the IEEE.. . For more information on this or any other computing topic, please visit our Digital Library at www.computer.org/publications/dlib. Over the 2006-2008 academic years, five faculty in six different engineering courses and over 120 students were involved in this project. The survey response rate was approximately 75 percent for the presurvey, 78 percent for the midsurvey, and 92 percent for the final survey. The differences in student response rate can be attributed to several factors. In one course, students ignored the presurvey completely, which lowered the overall number of responses. Additionally, the midsurvey was approximately 60 questions long, which discouraged many students from taking the time to complete it. The relatively high response rate for the final survey is likely related to instructors making greater efforts to encourage students to participate and providing other class-related incentives for completing the survey. Table 1 shows the student breakdown by major: CEE (Civil and Environmental Engineering), EE (Electrical Engineering), CmpE (Computer Engineering), and ME (Mechanical Engineering). Over 90 percent of the students were enrolled as full-time students.. Since, for most students, this was the first time that they had used Tablet PCs in the classroom with the Dyknow software, it was desired that the students would be able to quickly learn how to use the Dyknow interface on their Tablet PC. Therefore, all students were asked about their confidence and abilities in learning how to use new computer applications and their general skill in using computers. The responses indicated that the majority of students in the project felt they had slight or moderate confidence and skill in learning and using computer applications. Responses to other survey questions administered throughout the semester revealed that students did not have trouble acclimating to the use of Dyknow in the classroom. The importance of these results was that it helped to ensure that student responses to survey questions focused more on the educational aspects of the Tablet PC technology in the classroom rather than on their difficulties in learning how to use new software. It was also important to note that nearly all of the students participating in this project had either previously been enrolled or were currently enrolled in a traditional DL course, i.e., one that did not use Tablet PCs.. Evaluating the effectiveness of a new technology in education can be challenging, and a relatively large pool of students is necessary to make general conclusions. Ideally, any assessment strategy would focus on measuring the effect of technology on student learning. However, even with carefully designed assessment strategies, it is extremely difficult to assess student learning and determine the primary factors that contributed to any changes in learning. Ultimately, each student is responsible for making the effort to learn the material that is presented to them. Therefore, three primary areas are reported in this article, including 1) the potential impact of the Tablet PC on student participation, 2) student attitudes on the Tablet PC integration, and 3) a general summary of student performance. The underlying foundation of conveying information in an educational environment has changed very little over the years. The process of information delivery in the classroom generally revolves around an instructor presenting written or electronic material while the students process and/or write down the information presented to them. Additionally, in order to promote learning, instructors strive to create environments that promote and facilitate the learning and understanding of concepts. Thus, deep learning is separated from surface learning [8] and encompasses the higher levels of learning in the cognitive domain as defined by [9] . This type of learning can be achieved via the use of an appropriate instructional design process [10] , [11] . In the classroom, instructors may then pose questions, present problems or exercises to the class, design inquiry activities for teams to pursue, or use many other pedagogical techniques with the goal of promoting student engagement and interaction. Recent emphasis on these types of activities has created a shift from the traditional teaching paradigm to a learning paradigm [12] . Underpinning this paradigm shift is foundational educational research that has established a sound set of principles to better understand human learning [13] . Furthermore, it has been widely acknowledged that effective educational practices within this learning paradigm should provide active learning environments in which the cycle of knowledge transfer between instructor and student involves feedback to correct misconceptions and promote student learning. Several summaries of the literature in this area are available [14] , [15] , [16] , [17] .. What is changing, at a very rapid pace, is the technology that is available to the instructor to use in the classroom for the development of new educational practices and pedagogies. Computers, the Internet, hand-held devices, and a host of other technological marvels have altered the concept of knowledge transfer, and classrooms are being reconstructed and redefined with very different modalities for teaching, assessment, and learning. This revolution in communications has created broad impacts on the 21st century classroom [18] , [19] . The Classroom 2000 project [20] , [21] promoted technology for authoring, capturing, and storing lecture content and class events using pen-based computer devices for the instructor and students. One of the goals of the project was to ensure that lecture events could be easily captured and integrated for future access. Work concerning Authoring on the Fly [22] presented tools for creating multimedia representations of lecture content that could be used in a local class session or across distance. The use of technology to create virtual environments for instructorstudent interaction on pen-based and mobile computing devices has been promoted in several other projects as well, such as Classtalk [23] , ClassinHand [24] , and WIL/MA [25] .. However, the use of technology in the classroom does not necessarily equate to increased learning, more effective teaching, or a more engaging learning environment. In education, the merit of technology must be judged on its ability to improve student learning [26] , [27] , [28] , [29] . In other words, technology is only a medium or a tool through which new educational pedagogies may be developed, and the effectiveness of these new pedagogies will depend on how these technologies are deployed.. While there are a number of useful studies on the use of computer technology in the classroom, this article will focus on examples related specifically to Tablet PCs. One of the dangers in evaluating attitudes regarding new technology is that it is difficult to assess if the subjects really find value in the use of the technology or are just struck by the apparent novelty of something they have not experienced before. In order to evaluate the effectiveness of the Tablet PC integration into the DL courses in this case study, three surveys were administered over the 17-week semester as follows:. . Presurvey: Administered within the first two weeks of the semester. The purpose of this survey was to establish the baseline demographics of the students participating in the project. Information was gathered on student majors, the number of DL courses they had participated in, and their overall comfort with learning new computer applications. . Midsurvey: Administered between week 8 and week 12 of the semester. The purpose of this survey was to get an initial evaluation from the students on how they felt that the use of the Tablet PC and software was impacting their learning experience in the DL classroom. Information was also collected on the opinions of students regarding the use of Tablet PCs in DL courses (Fig. 1b) compared to their other DL courses, which were set up to only transmit video and audio (Fig. 1a) . . Final Survey: Administered during the final week of the semester. This survey was structured almost identically to the midsurvey. Having responses to the same questions from two different points in the semester allowed for tracking of the consistency in student attitudes as they became more accustomed to the technology. In addition to the subjective analysis of the surveys, a collection of cumulative student Grade Point Averages (GPAs) was collected along with the recorded grades for each student in the Tablet PC DL courses. The purpose of this analysis was to provide a general understanding of how well students performed relative to their cumulative performance in all of their other synchronous DL courses.

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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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Information Theoretic Analysis of Proactive Routing Overhead in Mobile Ad Hoc Networks Abstract-This paper considers basic bounds on the overhead of link-state protocols in mobile ad hoc networks. Hierarchical protocols are known for their good scalability properties, and hence this paper considers a two-level hierarchical protocol. In such protocols, nodes need to keep track of shortest path information, link states and cluster membership. Two types of overheads are considered; the memory needed to store routing-related information, including link-states and cluster membership, and the control messages that need to be exchanged to keep track of the changes in the network. Memory overhead is important practically for dimensioning network nodes, while message routing overhead is important since it reduces the effective capacity of the network to carry user data (vis-à-vis control data). The scalability properties of the message routing overhead are analyzed for different modes of network scaling. Practical implications, such as optimal cluster size, average/fixed memory requirement and routing protocol parameter selections are discussed. T HIS paper considers the protocol overhead needed for maintaining state information about the network. Such information may be needed for the proper functioning of various network protocols. For example, certain routing protocols may require sufficient state maintainance so that packets can be forwarded with an acceptable quality metric. Several classes of routing protocols can be viewed within this premise. For example, proactive routing protocols maintain up to date link state information periodically, while reactive protocols maintain link state information on an as-needed basis. Geographic routing protocols maintain geographic state (location) information.. For dynamic networks-almost every network is dynamic-significant protocol overhead may be needed in order to maintain state in the network, and, in our opinion, such an overhead has yet to be fully understood. But the real effective throughput achievable (per node) in a network depends not only on how much a node can send, but also how much of the sent information is actual user data vis-à-vis control packets. It is difficult to compare the overhead of various routing protocols since as yet there exist no absolute bounds on the minimum overhead incurred by any of the protocol classes. It would be useful to fill in this gap by developing some general theory, which ideally would precisely relate message routing overhead of a class of protocols to the other relevant network parameters such as node mobility.. The key departure point of the new framework proposed here is to treat the state (e.g., link state or node location, or a hybrid of both, etc.) as a random variable that exhibits random changes. The minimum protocol overhead is related to the minimum amount of information (i.e., effort) needed to identify the current state of the system, possibly within a distortion bound. The various state changes are derived from the probability distribution describing the cause of dynamism e.g., the nodes mobility pattern. Thus the protocol overhead can be brought into an information theoretic framework, and terms like entropy rate may now yield new practical design guidelines and basic limits.. This paper (and its earlier conference versions) represents a step in this direction by considering the class of hierarchical link-state. The extension to multiple levels is straightforward, but we do not include the results here for length consideration. More recently, the framework has been applied to reactive protocols in [1] as well as geographic routing protocols in [2] .. In this paper, we derive lower bounds on memory (bits) and minimum message routing overheads (bits per unit time) associated with a proactive routing protocol in an ad hoc network of mobile nodes as a function of the network parameters. The topology of an ad hoc network is randomly changing due to random node movement as well as random link-state changes (due to fading for example). To maintain up to date topology information, proactive routing requires that nodes of a network exchange control messages containing the new topology or topology change information. The memory requirement is related to the amount of state information stored or processed. The message routing overhead is related to the product of the control message size and the number of hops the control message travels.. In order to derive lower bounds on memory requirement and message routing overhead, the first step is to find lower bounds on the sizes of exchanged control messages, and then relate this to the rate of exchange through the parameters of the mobility 0018-9448/$26.00 © 2009 IEEE model. The minimum complexity of the control message sizes is intuitively a function of the complexity of the network. We capture this dependence through the information-theoretic measure called the Minimum Expected Codeword Length (MCL) (Section 5.4 of [3] ) which is the minimum number of bits required to describe (i.e., encode) a change.. Because of the hierarchical (clustered) structure, three different topology levels (types) are analyzed, where each topology level represents different granularity of the studied network topology. Three methods are used to derive expressions for the MCLs; topology cardinality (Method 1), topology probability distribution (Method 2) and topology prediction (Method 3).. To our knowledge, there is no previous work that bounds routing overhead using such information theoretic measure-related analytical work focuses on modeling (rather than bounding) routing overhead [4] , [5] . Gallager [6] analyzes the protocol overhead in a pure information theoretic manner. His paper uses an entropy measure to determine the basic limits on the amount of protocol information that must be transmitted in a stationary (i.e., without mobility) data communication network to keep track of source and receiver addresses and of the starting and stopping of messages. Topology changes (as it applies to routing for example) was not considered in [6] .. In [7] , Gavoille defines routing as a distributed algorithm over a static undirected random graph, and proposes multiple open research problems based on the structures of these graphs and the quality of service requirements. One of the interesting open questions is the tradeoff between the size of memory used to store topology information in the nodes of a network and the accuracy of finding shortest paths. The problem somehow is similar to our problem of finding the tradeoff between memory requirement and message routing overhead.. The main contributions of this paper are i) to derive analytic expressions of the MCLs for three information theoretic techniques for each topology level for link-state; ii) bound the average message routing overhead by the entropy rates of the sequences of topologies; iii) bound the average/fixed memory requirement; iv) provide a scalability analysis of the average memory requirement and message routing overhead with the number of nodes and number of clusters for three different modes of scaling; v) provide an analysis of the optimal number of clusters that asymptotically minimizes the message routing overhead; vi) provide a practical analysis of the encoding technique; and vii) quantify the tradeoff of the routing information accuracy versus routing efficiency impacted by the routing message exchange time intervals.. The paper is organized as follows. Section II introduces the network model (including the routing protocol, topology definitions and mobility model) and the notations used in the paper. Section III analyzes the minimum expected codeword lengths (MCLs). Section IV discusses the relationships between the entropy rates and the message routing overheads through the analysis of topology evolution. Section V derives lower bounds on the memory requirement and message routing overhead. Section VI studies the scalability of the overheads as a function of the network size. Section VII presents practical implications deduced from the theoretical results. Finally, Section VIII concludes the paper and outlines future research directions.

O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A Model for Secure Protocols and Their Compositions The paper develops a foundation for reasoning about protocol security. We adopt a model-based approach for defining protocol security properties. This allows us to describe security properties in greater detail and precision than previous frameworks. Our model allows us to reason about the security of protocols, and considers issues of beliefs of agents, time, and secrecy. We prove a composition theorem which allows us to state sufficient conditions on two secure protocols A and B such that they may be combined to form a new secure protocol C. Moreover, we give counter-examples to show that when the conditions are not met, the protocol C may not be secure. Consider a distributed network of communicating agents. Agents can send and receive messages, encrypt and decrypt messages, and generate new messages, keys and nonces. Most communication proceeds according to agreed protocols. Such protocols specify how an agent should interpret and respond to messages. The purpose of these protocols may be authentication, key distribution, or information sharing. For example, in the simple protocol given in Figure 1 , an agent A asks a server S to establish an A ? B session key (by sending the message fA;Bg K AS ), and S responds by sending a secure key K AB to A and B. We use fMg K to denote the encryption of message M with key K, and so fA;B;K AB g K AS denotes the message with components A, B and K AB encrypted with K AS . The keys K AS and K BS are assumed to be A's and B's respective secure keys for communicating with the server S. Unfortunately, this protocol is not secure. It is particularly vulnerable to replay attacks: an adversary can record messages 2 and 3 from a valid run of the protocol, and then replay them at any time to convince either A or B to reuse a stale session key.

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Fast min-hashing indexing and robust spatio-temporal matching for detecting video copies The increase in the number of video copies, both legal and illegal, has become a major problem in the multimedia and Internet era. In this article, we propose a novel method for detecting various video copies in a video sequence. To achieve fast and robust detection, the method fully integrates several components, namely the min-hashing signature to compactly represent a video sequence, a spatio-temporal matching scheme to accurately evaluate video similarity compiled from the spatial and temporal aspects, and some speedup techniques to expedite both min-hashing indexing and spatio-temporal matching. The results of experiments demonstrate that, compared to several baseline methods with different feature descriptors and matching schemes, the proposed method which combines both global and local feature descriptors yields the best performance when encountering a variety of video transformations. The method is very fast, requiring approximately 0.06 seconds to search for copies of a thirty-second video clip in a six-hour video sequence. With the rapid development of multimedia technologies, digital videos are now ubiquitous on the Internet. According to a report by AccuStream iMedia Research, 1 in 2006, the quantity of video streams increased 38.8% to 24.92 billion in media sites world-wide. One of the most popular video sharing sites, YouTube, hosted about 6.1 million videos, and 65,000 video clips were uploaded every day. The enormous growth in the amount of video data has led to the requirement for efficient and effective techniques of video indexing and retrieval. Since digital videos can be easily duplicated, edited, and disseminated, video copying has become an increasingly serious problem. A video copy detection technique would thus be helpful for protecting and managing video content. For instance, with such a technique, content providers could track particular videos with respect to royalty payments and possible copyright infringements. Platform providers could remove identical copies uploaded by users or aggregate nearduplicate videos into groups to facilitate browsing. Figure 1 shows the result of inputting the phrase "UFO Apollo 11" to YouTube. Several sets of identical or near-duplicate video clips are displayed on the search result page. If the near-duplicates of the same set are compacted into a single item, the search result page can display more diverse video clips for users. There are two general techniques for detecting video copies: digital watermarking and content-based copy detection. Digital watermarking embeds hidden information in video, while the content-based technique employs perceptual features of the video content as a unique signature to distinguish one video from another. Because the latter does not destroy or damage video content, it has generated a great deal of research interest recently. Most existing content-based methods treat a video as a set of individual image frames and focus on the investigation of compact image features or efficient index structures. However, this confines their use to particular applications. For example, some methods are limited to dealing with certain types of video transformation, while others are limited to other types, depending on the properties of the features they use. Since these methods seldom consider time-related features, they have difficulty handling video transformation types that modify the temporal structure of video, such as slow motion and frame insertion/deletion. The prebuilt index structures also cause an inherent search limitation, as some methods need to partition a video sequence into basic index units (e.g., shots) in advance. These methods might be inappropriate for monitoring broadcast streams.. In this article, we address the limitations posed by existing methods. We classify various video copies into four categories with respect to the spatial and temporal transformation. While current methods are limited to handling one or two categories, we propose a novel video content analysis scheme, called spatio-temporal matching, to tackle all the categories in a unified manner. The proposed matching scheme, which analyzes the content similarity of two videos compiled from their spatial and temporal aspects, can effectively handle a variety of video transformations.. To avoid the limitation caused by prebuilt index structures, we employ a sliding window approach that would be more appropriate for monitoring broadcast streams. Without the index structures, however, the search time spent on a large-scale video sequence would be considerable. To make the search more efficient, the proposed method adopts a coarse-to-fine matching strategy. In the coarse stage, the sliding window scans the entire sequence to find potential candidate clips quickly. Each windowed sequence, as well as the given query clip, is represented by a novel feature called the min-hashing signature that is compact and robust. For example, in this study, a 30-dimensional signature is sufficient to represent a sixty-frame sequence. In the fine stage, this spatio-temporal matching is used to filter out false positives from the candidate set. In addition, some speedup techniques are applied in both stages to great effect; hence, the proposed method is very fast overall.. To evaluate the proposed method, we implement several baseline methods that use different feature descriptors (e.g., the ordinal measure and the SIFT descriptor), as well as different matching schemes. The results of extensive experiments show that, with the composed feature descriptor, the proposed method achieves excellent results, which demonstrate the widest coverage for various transformation types among all compared methods. The proposed method is also very efficient, as it only needs about 0.06 seconds to search for copies of a thirty-second query clip in a six-hour video sequence.. The remainder of this article is organized as follows. In Section 2, we formulate the video copy detection problem. Section 3 reviews recent work related to video copy detection. In Section 4, we detail the proposed method, including min-hashing indexing and spatio-temporal matching. Section 5 describes the extensive evaluation experiments. Then, in Section 6, we summarize our conclusions. To achieve fast and robust video copy detection, we propose a novel method that is appropriate for dealing with a variety of video transformations in a continuous video sequence. The method utilizes the min-hashing signature to represent a video sequence, and spatio-temporal matching to evaluate the content similarity between two video sequences. In addition, we employ histogram pruning and inverted indexing techniques to speed up the search process. The results of extensive experiments demonstrate the abilities of the ordinal measure and the SIFT descriptor, the impact of the min-hashing signature, the effectiveness of the spatio-temporal matching scheme, and the efficiency of the speedup techniques. The results are very promising for a number of reasons. The two feature descriptors complement each other quite well; the compact min-hashing signature efficiently reduces the computation cost; the spatiotemporal matching scheme effectively improves the accuracy; and the speedup techniques accelerate the search process. The successful integration of these factors ensures that the proposed video copy detection method is both fast and robust. Our study of the video copy detection problem begins with content-based video retrieval (CBVR). The general paradigm for CBVR methods is based on the analysis of video shots [Chang et al. 1998; Deng and Manjunath 1998; Jain et al. 1999; Naphade and Huang 2001; Smoliar and Zhang 1994] . Shot boundaries are automatically detected by finding transitions (e.g., cut and fading) in video sequences. Each shot is then summarized as several key frames or clusters. For example, Jain et al. [1999] simply selected the first, middle, and last frames as key frames; Liu et al. [2003] extracted key frames by finding the peaks of the motion energy in the video sequence; Cheung and Zakhor [2003] proposed using the Voronoi video similarity for key frame selection; and Shen et al. [2005] modeled a video shot as a cluster described by the position, radius, and density of a hypersphere. Given a query clip, these methods search in the dataset by matching the shot key frames or clusters.. Existing CBVR methods do not consider video transformation because their ultimate goal is to find videos that are semantically similar, rather than perceptually similar, to the query clip. Moreover, they are regarded as typical of the partitioning and indexing approach, and suffer from the same problems mentioned in the previous section.. Searching by a sliding window is a popular approach [Chiu et al. 2008, Hampapur and Bolle 2001; Hua et al. 2004; Hoad and Zobel 2006; Kashino et al. 2003; Kim and Vasudev 2005] . Although this approach is simple and effective, the computation can be slow when scanning a long video sequence. However, if the indexing feature is represented in a histogram-based form, many frames can be skipped by exploiting the histogram pruning algorithm without influencing the matching result [Kashino et al. 2003] . In this article, we develop a video copy detection method based on the window sliding approach.. The ordinal measure has been widely used in video copy detection [Chiu et al. 2008; Hampapur and Bolle 2001; Hua et al. 2004; Kim and Vasudev 2005; Yuan et al. 2004] . To extract the ordinal measure, each video frame is partitioned into N x × N y nonoverlapping blocks and the average intensity of each block is computed. Then, the blocks are ranked according to their average intensities; the ranking order is known as the frame's ordinal measure. The merit of the ordinal measure is its compact representation, Since only a 9-dimensional vector is needed for a 3×3-block frame. Moreover, the measure is less sensitive to several video transformation types than general low-level image features (e.g., color histograms and texture descriptors). In addition to the ordinal measure, Hoad and Zobel [2006] proposed a compact video representation composed of color-shift and centroid-based signatures. The former computes the change of color histogram distributions, while the latter computes the spatial movement of the lightest and darkest pixels. Consequently, each frame is represented by a 2-dimensional vector, which is more compact and robust than the ordinal measure.. Both the ordinal measure and the color-shift/centroid-based signature are extracted based on the whole frame region. We refer to them as "global descriptors," which have shown their robustness to whole region-preserved spatial transformations in many studies. However, if the frame is modified by partial region-discarded spatial transformation, its global descriptors might be totally different from those of the source frame.. Due to the limited capability of the global descriptors, various local descriptors have been investigated by many researchers as an alternative feature representation for image/video copy detection, for example, the Harris descriptor [Schmid and Mohr 1997] , Scale-Invariant Feature Transform (SIFT) [Lowe 2004 ], local fingerprinting [Massoudi et al. 2006] , and spatio-temporal features [DeMenthon and Doermann 2006; Willems et al. 2008] . In addition, the bag-of-words model is frequently applied to aggregate local descriptors of clusters for the sake of compact representation [Chiu et al. 2007; Poullot et al. 2008] . The comparative study of Law-To et al. [2007] shows that local descriptors are more robust than global descriptors in handling several video transformation types.. In this study, however, we find that global descriptors are better for whole region-preserved spatial transformation, while local descriptors are better for partial region-discarded spatial transformation. These two types of descriptors can complement each other; therefore, combining them as a single feature representation improves the accuracy of detecting various video copies. This idea is different from the method of Wu et al. [2007] , which employs the color histogram as the global descriptor for fast rejection at the coarse stage and the PCA-SIFT descriptor as the local descriptor for detailed matching at the fine stage. Since the global and local descriptors are applied separately at each stage, copies derived from partial region-discarded spatial transformation might be falsely rejected at the coarse stage.. Consider two video sequences that have the same content but different speeds: one is normal speed, and the other is double speed, as shown in Figures 2(a) and 2(d), respectively. Since their contents do not synchronize, a window sliding-based method might obtain a lower similarity score and lead to a false negative. To remedy this problem, some methods have been proposed to take both spatial and temporal information into consideration. Hua et al. [2004] , Hoad and Zobel [2006] , and Chiu et al. [2008] applied the dynamic programming algorithm to solve the content synchronization problem; Joly et al. [2007] used a RANdom SAmple Consensus (RANSAC) algorithm to iteratively estimate the affine transformation parameters (say, resize, rotation, translation, and speed) between two video sequences; Law-To et al. [2006] proposed a voting algorithm for spatial and temporal registrations; and Kim et al. [2008] presented a non-crossing bipartite matching scheme to model the video linkage relation. A common point of these methods is that they assume the frame order of the video copy is not altered. They cannot handle frame order-changed temporal transformation, like the case shown in Figure 2 (e). To address this problem, we propose a novel spatio-temporal matching scheme by applying the Hough transform algorithm to search for specific copy patterns. Our matching scheme can effectively deal with both spatial and temporal transformation categories, as mentioned in the previous section.. In order to efficiently search for video copies in a high-dimensional space, we propose using a popular algorithm for nearest neighbor search, namely, Locality-Sensitive Hashing (LSH). LSH uses several hash functions to hash an input item. An effective LSH function ensures that the hash collision probability of two items is proportional to their similarity. Several LSH functions have been derived based on the following distance and similarity functions, including Hamming distance, L s norms, L 2 distance on a sphere, arccos, and Jaccard coefficient [Andoni and Indyk 2008] . The LSH family has been successfully applied in several research fields, such as Web mining [Das et al. 2007 ], bioinformatics [Buhler 2001] , and image copy detection [Ke et al. 2004] . In this article, we study the potential of the Jaccard coefficient-based LSH, min-hashing, in video copy detection. To evaluate the proposed method, we compiled a video dataset for use in several experiments. The code was implemented in C++, and the evaluation was carried out on a PC with a 1.8 GHz CPU and 2GB RAM.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Computing and Evaluating View-normalized Body Part Trajectories This paper proposes an approach to compute and evaluate view-normalized body part trajectories of pedestrians from monocular video sequences. The proposed approach uses the 2D trajectories of both feet and of the head extracted from the tracked silhouettes. On that basis, it segments the walking trajectory into piecewise linear segments. Finally, a normalization process is applied to head and feet trajectories over each obtained straight walking segment. View normalization makes head and feet trajectories appear as if seen from a fronto-parallel viewpoint. The latter is assumed to be optimal for gait modeling and identification purposes. The proposed approach is fully automatic as it requires neither manual initialization nor camera calibration. An extensive experimental evaluation of the proposed approach confirms the validity of the normalization process. A well-known medical study has shown that human gait is a complex motion that may be decomposed into twenty significant components [1] . It is believed that the complexity of the interactions between the various components encodes relevant information about the identity of the moving person. Recent progress in computer-based analysis of gait has confirmed its potential as a biometric feature. First and foremost, gait analysis allows for person identification at a distance, which is difficult or even impossible with other biometric techniques such as retinal scanning, fingerprints, or face recognition.. Gait-based person identification represents a key element in the design of robust visual surveillance systems. To the best of our knowledge, gait-based identification has not yet been integrated in surveillance systems. Previous computer-based surveillance systems [2] have focused mostly on pedestrian detection [3] and low-level tracking of human subjects using basic 2D appearance models [4] . More sophisticated 3D part-based models may also be obtained but they require manual interventions for initialization [5] . Besides, stereo data is required for methods using 3D temporal motion models [6] . Finally, 3D models are computationally expensive and therefore difficult to use in real-time surveillance.. A key surveillance issue addressed by the proposed approach is the varying angle between the camera optical axis and the walking trajectory direction of an observed pedestrian. This phenomenon introduces a variation of the human motion captured with an uncalibrated camera. In practice, many gait modeling approaches are either only applicable to fronto-parallel viewpoints [7, 8] , or at least view-dependent [9] . Height and stride length are estimated in a view-invariant way in [10] , but the method necessitates the camera to be calibrated with respect to the ground, which could be problematic in a realistic surveillance context. The method proposed in [11] uses the structure of articulated body part motion to recover the parameters of the projective transformation under which a subject is observed. The projective transformation is then used to generate a canonical fronto-parallel view. That method uses markers to obtain precise positions of the ankles, knees and hip, which are difficult to retrieve automatically from computer vision algorithms. Synthesis of a canonical side view from an arbitrary view is performed in [12] via two methods, namely perspective projection and optical flow-based structurefrom-motion. However, the synthesis of a side view is only feasible from a limited number of initial views. The method in [13] involves a scaling process, for each known view, on silhouette parameters such as height and distance between head and pelvis. In [14] , a method for tilt correction of silhouettes is proposed, but it requires camera calibration. Estimation of a person's 3D trajectory from a monocular calibrated camera is discussed in [15] . The 3D trajectories are used in order to recover the walking speed. Walking directions of people are computed in [16] using a camera with known focal length and the weak-perspective projection model. The walking direction is then used to recover view-invariant lengths at different parts of the silhouettes.. Other methods integrate the information from multiple views in order to recover a canonical view or to extract features that are view-invariant. This is the case of the method presented in [17] where the desired view of a moving object is reconstructed using multiple simultaneous views. The method proposed in [18] achieves view-invariance by learning gait parameters from mutiple views, and people identification is performed by providing only a single view. In [19] , a bilinear model is fitted on mutiple views. View-invariant identification is achieved by decoupling the identity of the person and the viewpoint from which he is observed. A view transformation model is used in [14] in order to transform already observed gait features into the same walking direction as newly observed features. The view transformation model is learned from multiple views of walking subjects. Those methods are difficult to carry out in the context of a surveillance system where typically a single view is available. Moreover, a general learning phase could be hard to obtain.. In many realistic settings, for instance when pedestrians are observed in extended premises via a network of loosely-coupled nodes [20] , an efficient and automatic modeling approach is required. Therefore, in order to address the constraints of a real-time surveillance system, we propose to use 2D trajectories of body parts for modeling gait. Our work is similar to [21] and [22] with respect to the fact that we use an implicit kinematic model for gait. Specifically, we extract spatiotemporal trajectories of body parts (head and feet) for modelling gait. Our method for trajectory generation improves upon previous work by solving the manual initialization issue in [21] and by extracting the spatiotemporal trajectories in real time from video data instead of obtaining them from a marker-based motion tracker [22] . Our main contribution consists in a novel technique for viewpoint normlization which is summarized below.. The trajectory of a body part (foot, head, etc.) is defined as a sequence of the successive 2D positions it takes in the frames of a video sequence. On a frameby-frame basis, each body part is represented by one point respectively. Body part trajectories are assumed to contain sufficient information about the gait of a person for view-invariant modeling and identification; this assumption is based on early work by Johansson [23] and on related work on kinematic gait models [21] [22] . The walking trajectory, which is the path followed by a person on the floor, is not assumed to be a single straight line. Instead, it is assumed to be a polyline that is, a sequence of straight-line segments of variable orientations and lengths. View normalization consists in making body part trajectories appear as if seen from the same fronto-parallel viewpoint for all straight-line walking segments of the video sequence. The proposed approach to view normalization features automatic initialization, no camera calibration, as well as a low computational complexity. This paper is an extension of the work presented in [24] . A new evaluation method is proposed to assess the performance of the normalization algorithm. An extensive evaluation is performed on more than 80 walking trajectories.. The remainder of the paper is organized as follows. Preprocessing is presented in Section 2. The proposed approach is detailed in Section 3. The evaluation method is dicussed in Section 4. Experimental results are presented in Section 5. Finally, Section 6 draws conclusions and outlines the main directions of future work. In realistic surveillance situations, pedestrians cannot be assumed to always follow a single straight line. Besides, their walking trajectory cannot be known in advance. The proposed approach deals with both difficulties by first estimating the walking trajectory using the original feet trajectories. The estimated walking trajectory is then "spatiotemporally" decomposed into piecewise linear segments. Original and normalized plane parameters are computed for each of those segments. Finally, body part trajectories of each segment are normalized using the computed homography between the corresponding planes. Figure 2 presents a situation where a person follows a straight walking trajectory. In this case, the person is to occupy different positions with different postures while walking from the right-hand side at time t 1 to the left-hand side at time t 2 . The walking trajectory angle with respect to the camera optical axis In this paper, an approach for normalizing body part trajectories was presented. The normalization process consists in the computation of a piecewisestraight walking trajectory, and a corresponding sequence of walking planes. A homography computation aligns the edges of each walking plane with the image edges. Each computed homography transforms the body part trajectories within the time interval of its corresponding walking plane.. The proposed approach is promising since it has direct applications to gaitbased modeling and identification, which performs significantly better from a fronto-parallel (side) view. As validated experimentally, the normalized trajectories of head and feet from different views are well aligned with real frontoparallel view trajectories. To the best of our knowledge, this is the first viewnormalizing method proposed in the literature that is applicable to real-time gait-based identification in a surveillance context.. Ongoing work focuses on testing the proposed approach on trajectories of additional body parts (hands, knees etc.) involved in human walk. More tests are to be performed on trajectories with changes in walking direction. Gaitbased identification will be perfomed by extracting gait characterisics from normalized body part trajectories.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O


A critique of recently proposed buffer-sizing strategies Internet router buffers are used to accommodate packets that arrive in bursts and to maintain high utilization of the egress link. Such buffers can lead to large queueing delays. Recently, several papers have suggested that it may, under general circumstances, be possible to achieve high utilisation with small network buffers. In this paper we review these recommendations. A number of issues are reported that question the utility of these recommendations. Buffers are used at network routers to temporarily store incoming packets when the arrival of packets received exceeds the capacity of the egress link. This is done to maintain a high-level of utilization of link capacity and to accommodate bursty traffic. Traditionally, router buffers have been provisioned according to the bandwidth-delay product (BDP) rule: namely, one chooses the buffer size as B×T , where B is the rate of the link served by the router, and T is the "typical" round trip time experienced by connections utilizing the link. Building upon the basic observation that, under some circumstances, only a fraction of TCP flows reduce their sending rates in response to a single congestive event, a number of recent papers have suggested the possibility of deploying significantly smaller buffers without compromising utilisation of a congested link [3, 4, 5] . For related work on determining the buffer size to achieve a desired level of utilisation for given network conditions see also [8, 7, 6, 9, 10] and the references therein.. While this work is clearly of scientific merit, in this paper we highlight a number of fundamental issues that arise in applying these results to guide buffer sizing in real networks. In particular, we make the following observations. * This work was supported by Science Foundation Ireland grants 00/PI.1/C067 and 04/IN3/I460.. (1) The buffer sizing strategies being proposed in the literature depend crucially on the nature of the arriving traffic, with the majority of existing results related to links with a fixed number n of long-lived tcp flows. Real links almost always contain a complex mix of flow connection lengths, round-trip times, UDP traffic etc. For a given traffic mix we can try to determine an effective number n -the recently proposed ADT algorithm [9, 10] is one (measurement-based) way to do this for example.. (2) Even when such a refinement is used, however, the traffic mix on a link may be time-varying. Our measurements on a production link confirm that traffic patterns do indeed change significantly (here "significantly" is with respect to buffer sizing requirements) over time. This immediately calls into question the utility of fixed buffer sizing strategies in real communication networks, and potentially motivates adaptive approaches to buffer sizing. Again the ADT algorithm [9, 10] can be used to adaptively tune the required buffer size.. (3) In the context of buffer sizing it is essential to distinguish between links at which TCP flows experience packet loss and those where they do not. Roughly speaking, we can classify links as core links or access links 1 . Core network links are over-provisioned, experience essentially no queueing and generate essentially no packet loss. We contrast this with access links where significant queueing and packet loss occurs. It is these latter links that are clearly of primary relevance for analysis and discussion of the interaction between buffer sizing and elastic traffic behaviour. To illustrate the lack of clarity in the literature on this point, we note, for example, that [11] cite measurements on a backbone link where no loss occurs (for buffer sizes above 2.5ms) as qualitative evidence in support for the long-lived TCP analysis of [3] . Since the analysis of [3] relates to a link which is the bottleneck for many long-lived TCP flows and necessarily suffers from significant packet loss regardless of buffer size, the inference here is clearly questionable.. (4) As we have already mentioned, link utilisation and queueing delay do not by themselves fully capture the quality of service perceived by TCP flows. As noted by [6] , packet loss is also important. We illustrate this in the context of the use of a very small queue on a live production linkas discussed later, we had in fact to end our test prematurely (after 2.5 hours) owing to the high number of user complaints regarding link quality when using a small queue.. With hindsight, many of these points are perhaps unsurprising. Their fundamental relevance to the recent literature on buffer sizing is nevertheless self-evident and arguably points to the need for an expanded research agenda in this area. We make the following observations from our measurements.. 1. Real links contain a complex mix of flow connection lengths and round-trip times.. 2. Traffic patterns change significantly (here "significantly" is with respect to buffer sizing requirements) over time.. 3. In the context of buffer sizing it is essential to distinguish between links at which TCP flows experience packet loss and those where they do not. On over-provisioned links that experience essentially no queueing and generate essentially no packet loss the choice of buffer size has little impact on performance. We contrast this with access links where significant queueing and packet loss occurs.. 4. Packet loss is an important aspect of link quality in practice. We illustrate this in the context of the use of a very small queue on a live production link -we had in fact to end our test prematurely (after 2.5 hours) owing to the high number of user complaints regarding link quality when using a very small buffer.. The fundamental relevance of these observations to the recent literature on buffer sizing is self-evident and points to the need for an expanded research agenda in this area. Our immediate conclusions point to the utility of adaptive buffer sizing solutions, provided that one accounts for both utilisation and loss rate in the adaptation strategy [12] .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Passive Sensor Based Multiple Objects Tracking and Association Method in Wireless Sensor Networks This article presents a method for dynamic data association in wireless sensor networks and addresses the issue of multiple objects tracking. The sensor node used in this article incorporates RFID reader and an acoustic sensor so that two different signals are cooperating for tracking and associating multiple objects. The RFID tag is used for object identification and an acoustic sensor is used for estimating object movements. In the heterogeneous sensor networks, our proposed association method is analyzed with association success, failure, and recovery cases. In addition, 2-dimensional (2D) particle filtering is used for estimating a objects state such as position and velocity. The performance is compared between a single sensor node and multiple sensor nodes in our proposed algorithm. In addition, the association performance with multiple sensor nodes is evaluated as a function of sampling time and object movement behavior. Finally, the effect of the two heterogeneous sensors range difference is analyzed and discussed. The multiple objects tracking and association have critical problems that arise in a wide variety of contexts such as monitoring people for security purposes in many surveillance areas [1] . Once receiving the unlabeled multiple measurements, the tracking system should match the measurements and tracked objects, which is called an association problem [2] . After the association among measurements and objects, each object state information of position or/and velocity should be estimated even in the noisy environment, which is called a tracking problem [2] . Once the association process is achievable, the tracking can be done with respect to a single object tracking.. For many years, an acoustic sensor based association has been investigated in many tracking applications [3] [4] [5] [6] [7] . Two simple approaches are the nearest neighbor filter (NNF) and the strongest neighbor filter (SNF) [2, 8] . In the NNF, the measurement closest to the predicted one is matched and the others are discarded. In the SNF, the signal with the highest intensity among the measurements are matched. While the deterministic approaches are reasonably solving the association problem, they fail in the overlapped cases due to noise sensitivity. In order to make up for the weak point in deterministic decision, the joint probabilistic data association filter (JPDAF) has been proposed [2] . The approach is to use all observed measurements by skipping one-to-one mapping. Furthermore, each measurement has a weight according to each object, and directly estimates the object-state information. However, the estimation is an approximation since each object may be corrupted by other unrelated measurements. In other words, it is difficult to obtain an accurate estimation. As another approach, multiple hypothesis tracking (MHT) is applied in many applications as well [2, 9, 10] . The MHT enumerates or arranges all feasible matching among measurements and objects with probabilities. The approach has an advantage that the mismatching rate may be reduced. On the other hand, it is difficult to implement because a large number of hypotheses may have to be maintained.. Together with the association problem, the object identification problem is also a critical factor in a surveillance system. In order to achieve the identification problem as well as the association problem, several methods are proposed using the range profile [14, 15] . However, the method is only effective for tracking airplanes when the High Resolution Radar (HRR) range-profiles are available. In addition, the HRR is not appropriate to track multiple objects with nonlinear movement as well as in indoor environments. As another approach, the Belief Matrix has been proposed [16, 17] to track aircrafts with improved performances. However, the Bayesian Inference (BI) has identification uncertainty and assumes that prior information is given.. Recently, a RFID system has been considered as a prominent technology to identify multiple objects. The RFID is more vulnerable to the exterior noise than other sensors such as an acoustic sensor and a visual sensor. The system can be classified into two groups; the active and passive system. The active signal has the benefit that the identification information is broadcasted periodically to the receiver by itself and ensures reliability of obtaining information. However, it is not feasible for the surveillance application because of an uncertain lifetime and economical efficiency. On the other hand, the passive RFID system has an efficient solution as it draws the power from the reader [18] . The critical defect of both systems is to provide existence information only; proximity to the reader is supported. Thus, we propose the algorithm to resolve problems by incorporating an acoustic sensor to a RFID reader in wireless sensor networks (WSN). In this article, bearings-only tracking with acoustic sensors is applied for the performance evaluation of our proposed method. The bearings only tracking has been widely used and applied to an extended kalman filter or a particle filter for nonlinear kinetic movement with non-Gaussian measurements uncertainty in many tracking applications [6, 7, [11] [12] [13] .. The key issue in the proposed method is to provide a robust solution against a plausible association failure. In other words, our method supports false association detection and correction. Based on the association method with a threshold angle, the association correction was introduced in a simple case where objects are not overlapped [19] . In order to have the better performance in the case of overlapping objects, a Sequential Monte Carlo (SMC) technique called particle filter is introduced [20] . The method is used to predict and estimate the object state using the particle filter. In addition, in order to properly associate a Direction of Arrival (DOA) with a tag from a DOA measurement set, the particle filtering is applied with the previous object state information. It improves the threshold angle based association so that an object is easily distinguishable from others.. Through the dynamic behavior of objects in deployed sensor networks, we can achieve not only the recovery of the failed association, but also the higher average association rate (AAR). Besides, the range mismatch between two sensors is another problem to make the association difficult. In order to analyze this problem, we model the sensor ranges and classify them into three types. In this article, the factors affecting the association are explained and analyzed in detail. The performance based on a single sensor node is compared with the ones based on multiple sensor nodes. The association performance in multiple sensor nodes is evaluated as a function of sampling time and object movement behavior. Finally, the effect of the mismatch range between two heterogeneous sensors is analyzed and discussed.. The remainder of this article has 5 sections. In Section 2, we present an overview of the sensor node architecture including its required functionalities and limitation. The threshold based method is briefly explained for the association process and the sensor range models are illustrated to explain the possible application for the realistic scenario. Section 3 presents object management methodologies for single sensor and multiple sensors paradigm. In order to resolve the objects overlapping problem, the particle filtering is introduced and the association cases related to the range mismatch are studied. In Section 4, the performance of the algorithms is evaluated in detail. Finally, our contribution is summarized in Section 5. frequency are necessary so that they can detect a signal perfectly in their range without loss or collision. We can control the sensing period, Ts, to be small enough so that a change of object position from the previous position is small. The acoustic sensor proposed by [21] is used and the reverberation effect is ignored. There are two different signals for two main functions in the application model: the RFID signal is used to identify an object and the acoustic signal is to track the object. The conventional association and tracking scheme usually focus on only the tracking except the identification. In a realistic application, however, identifying the tracked object is also one of the main functionalities. The object identification is not trivial only when the acoustic signal is used. Although the speech signature possibly solves the problem, the exterior noise and distortion cause the false or failed identification. In our approach, the RFID signal, which is more reliable than the acoustic signal, is incorporated for the object identification. Besides, this is used to inform the system that the object enters the surveillance region. This can improve the association performance when the acoustic signal based tracking is failed. The main purpose of our method is to identify tracked objects and recover it when the tracking fails using two different passive sensors. In this article, when we find a RFID signal of an object, which corresponds to a DOA of the object, it is called ''associated.'' If a DOA is updated from the previous DOA for an object, it is called ''tracked.'' This article presents the object association method based on the proposed sensor node architecture for multiple objects tracking and management in wireless sensor network. The sensor node incorporates the RFID tagging unit for identifying multiple objects and acoustic sensor for tracking them in realtime. This method enables the system to track and identify objects at the same time. Moreover, the appearance of an object in the sensing range is utilized for establishing or recovering the association. We introduce the particle filtering to resolve when they are at the similar line of sight from the sensor node. As the noise variance of DOA increases, the association performance is deteriorated. We also verify the proposed method under the range mismatch. The simulation result indicates that the minimum range difference is required for the best tracking and association performance. For the future work, we will investigate the effect of synchronization issue between sensors.

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An efficient approach to removing geometric degeneracies Our simis to perturb the input so that art algorithm designed under the hypothesis of input non-degeneracy can execute on arbitrary instances. The Algorithms in computational geometry are typically designed for input instances in general position.. The treatment of degenerate cases is tedious and intricate, thus *Supported by a David and Lucile Packard Foundation Fellowship and by NSF Presidential Young Investigator Grant IRI-8958577.

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Introducing Privileged Words: Privileged Complexity of Sturmian Words In this paper we study the class of so-called privileged words which have been previously considered only a little. We develop the basic properties of privileged words, which turn out to share similar properties with palindromes. Privileged words are studied in relation to previously studied classes of words, rich words, Sturmian words and episturmian words. A new characterization of Sturmian words is given in terms of privileged complexity. The privileged complexity of the Thue-Morse word is also briefly studied. This work concerns a new class of words named privileged words which have previously been researched only a little. The motivation for defining these words comes from the research of socalled rich words [Gle+09] which are words having maximum number of distinct palindromes (thus the name, rich words are rich in palindromes). An important property of rich words is that a word is rich if and only if every complete first return to a palindrome is a palindrome. It's equivalent to say "every palindrome is a complete first return to a shorter palindrome". By a slight alteration of this condition we define privileged words: a word is privileged if it's a complete first return to a shorter privileged word. Moreover we need to define that the empty word and the letters of the alphabet are privileged. The effect of this modification is that every word is rich in privileged words, i.e. every word w has exactly |w| + 1 distinct privileged factors whereas a rich word w has exactly |w| + 1 distinct palindromes (there exist words which have strictly less palindromic factors). It turns out that privileged words and palindromes have some similar properties. This paper introduces the basic properties of privileged words, and questions regarding so-called privileged complexity of Sturmian words, episturmian words and the ThueMorse word are studied.. After introducing the notations and definitions, in Section 3 privileged words and their basic properties are presented. These basic results emphasize the analogue between palindromes and privileged words. Moreover privileged words are studied in relation to rich words.. Section 4 studies the number of distinct privileged factors in finite words. There's also discussion how privileged words fit into a recent work of G. Fici and Z. Lipták [FL12] .. Various complexity functions of infinite words have been previously considered. In Section 5 the notion of privileged complexity is defined. This section contains the main result of this paper: a characterization of Sturmian words using privileged complexity. As a by-product of the methods used in the proof of the main result, we obtain with little extra effort some previously known results, namely the fact that Sturmian words are rich, and partially a result of X. Droubay and G. Pirillo concerning the palindromic complexity of Sturmian words [DP99] . The section is concluded with a brief study of the privileged complexity of episturmian words.. The last section studies briefly the privileged complexity of the Thue-Morse word. It's proven that the Thue-Morse word doesn't contain a privileged factor of odd length greater than three. However the even case is left open. Some numerical data and a conjecture are provided.

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