bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ant-Based Delay-Sensitive Query Processing for Wireless Sensor Networks
Authors: Yu Jianping , Lin Yaping , Hu Yupeng 
Published: January 2009

The technologies of wireless sensor networks (WSNs) have been developed rapidly in the most recent years. As WSNs are characterized by data-centric storage and routing under most circumstances, any application involved requires data management and processing technologies, especially the query processing mechanisms. The WSNs are often deployed in diverse application specific contexts, which can be treated as distributed databases. The event-involved responses can be obtained by issuing queries to this kind of database. Certain of the applications with real-time requirement have tight constraints on query delay. However, the existing query algorithms are not satisfied with them. The problem we focus on can be simply described as: once an event has happened, how to optimize the replication energy cost due to storing the event data from the event source to multiple positions and how to optimize the searching energy cost and query delay due to finding one replica of the event and copying the event data on demand if subsequent queries for the event are performed. Ant algorithms adopt a group of intelligent agents called ants to carry out local search, using the historical information obtained to guide the ongoing search and having characteristics of collective intelligence, it can find better routing paths without knowing the global information of the network. Aiming at the real-time applications, an ant-based delay-sensitive query processing algorithm (ADSQP) taking advantage of ant colony optimization with the characteristics of self-organization and positive feedback is proposed, in which the priority-based multiple-ring storage scheme and the ant-based distributed search mechanism are adopted to improve the integrated performance of the energy-efficiency, delay, and query success rate. To reduce the replication cost of ADSQP, the cluster-based aggregation approach and the ring-based storage method according to the importance level of the events are proposed, in which the aggregated events with higher priority will be stored in the nodes on the farther ring to the aggregation nodes. To reduce the search cost and the query delay of ADSQP, the ant-based search mechanism for the queried events and the second replication approach for the found events are also proposed. The simulation results demonstrated that not only the performance of energy-efficiency and query success rate can be improved but also significant smaller query delay can be achieved by the ADSQP when comparing with other query processing algorithms. Moreover, the new algorithm is flexible and demands merely local information to find queried events efficiently and determine the number and allocation of replicas adaptively.
SVM Based Classification Mapping for User Navigation
Authors: Yuan Jing-Ling , Yu Yang , Xiao Xuan , Li Xiao-Yan 
Published: January 2009

In order to implement active service, a kind of user navigation based on Support Vector Machine (SVM) classification was proposed which solved many traditional problems such as lack of rules and adaptability and so on. Especially, this paper completed a dual classified coordination between user attribute classification and SVM user classification using mapping matrix. In our SVM based user navigation, we first regard User interest Set as input, then apply the SVM classifier to sort out users on the basis of their interests or attributes, and what is more, combine the merit that user attributes classification promise better service being offered to users whose using frequency is not high, a dual-classified collaborating navigation between user attribute classification, and SVM user classification by using mapping matrix is being proposed. We use the mapping method to mix their advantages of common classification methods which lead them to collaborate and to provide the new and old custom with navigation. Using Classification T to statistic the latest and the most frequently used demands of each user type, then applying a mapping from user attribute class (A) to user interest class (T) with the purpose to judge what kind of user type in Classification T has the most possibility the user might belong, to and then to provide the user with the latest services according to their interests. From the experiments, the fitting degree of A and T classification and the true personality of users are derived by tracking the demand of 50 users. We can see that with the increase of frequency in use, the matching degree between Users Attribute Classification (A) and real types of user are essentially the same, and User Personalized Classification (T) is gradually reaching saturation. Regarding the certain point as a dividing line, after using classification mapping, the user's true extent of matching has a broader applicability. SVM have excellent generalization performance and minimum structural risk, which is a good machine learning method that elicits objective regulation from complex statistical dates. So we have improved the user model of active service navigation system and user navigation combined with User Attribute Classification A and SVM User Interest Classification T by mapping matrix. Classification A and T using mapping matrix to bounding them can satisfy the requirement of a different user. The records in the Classified Statistic Library can provide feedback date and research information for further study between a personalized user and user attribute.
A New Replica Placement Algorithm for Improving the Performance in CDNs
Authors: Zhang Lei , Tian Hui , Steglich Stephan 
Published: January 2009

With the advent of services and applications over the Internet, speed and reliability have become critical issues for clients, and the Internet currently is not well suited for the purpose of the emerging new service delivery contemplated by today's applications. In response to these challenges, commercial Content Distribution Network (CDN) deploys a set of proxy servers called replicas and improves the content delivery performance by replicating the content to multiple replicas in the Internet. These issues motivate us to do research in how to efficiently place replicas in the network, and then propose a cost-based replica placement algorithm which selects replica locations using a greedy fashion iteratively. We evaluated that it can yield close to optimal performance at low management and computation cost among several replica placement strategies. The key contributions of this paper are threefold: A practical cost function from the game theoretic perspective is designed, and is limited by various parameters and constraints. It can minimize either its clients' latency or its total bandwidth consumption. A cost-based replica placement integrating a greedy algorithm is proposed, which can provide CDNs with the performance close to optimal. The performance of the diversified replica placement algorithms is evaluated by simulating their behavior on synthetic and real network topologies. To the best of our knowledge, there are few studies on this subject. In summary, we study the online problem of placing web replicas in CDNs to minimize the cost for clients to access data replicated from the original web servers. The novel cost-based replica placement is designed combining with the minimum k-median heuristic greedy algorithm. We evaluate the performance of the different replica placement algorithms by simulating their behavior on both synthetic and real network topologies. Based upon simulation results, we conclude that our cost-based greedy algorithm for web server replica placement can provide CDNs with performance that is close to optimal. Although the greedy algorithm depends upon estimation, we find it is a viable and practical algorithm to use in the general Internet environment. As for future work, we are interested in exploring incremental versions of the placement algorithms that also take into account the cost of changing the set of replica sites. Ideally, for placement strategies with similar performance, we prefer the one that incurs the least amount of perturbation to the system.
A Novel Group Management Protocol for IP Multicast (LW-IGMPv3)
Authors: Jiwen Liu , Wendong Wang , Xiangyang Gong , Hui Liu , Wei Cao , Xuesong Gao 
Published: January 2009

With the deployment of multicast service, people gradually find that hardly any practical application uses Exclude filter mode to block sources. For this reason it is generally unnecessary to support the filtering function to block sources. In addition, the newly proposed SSM service model has defined several modifications to IGMPv3; therefore certain modifications to IGMPv3 must be performed before it can be deployed in the SSM model. On the basis of the above analysis, LW-IGMPv3 is designed as a simplified version of IGMPv3 by Huawei Technology Co., which has been accepted by the IETF Mboned working group as a new draft. LW-IGMPv3 follows the query/response model adopted by all the previous IGMP versions. Therefore the network overhead of LW-IGMPv3 is basically the same with IGMPv3. The major difference between IGMP and LW-IGMPv3 is below. First, the reception state for each attached network maintained by the multicast router is simplified as: (multicast address, group timer, (source records)); second, most record types have the same operation rule in both ASM and Include state, and only the TO_IN record type need to vary its operation according to the value of its group timer; third, the forwarding suggestion rule no longer needs to take the filter mode into consideration. Functional research is performed, in which protocol states and message operation procedures are analyzed and compared to those of IGMPv3. A simulation is conducted with our developed C++ simulator to generate network traffic and LW-IGMPv3 and IGMPv3 protocols deployed on the open source router platform XORP in order to compare router performance of LW-IGMPv3 and IGMPv3. During the simulation, the performance, which was measured by CPU processing time and Memory occupancy, of the device running LW-IGMPv3 is improved substantially compared to the one running IGMPv3 and the value of all the parameters of both IGMP protocol and multicast routing protocol are the same. Also, a simulation environment is established and a series of test cases is designed to verify the compatibility of LW-IGMPv3. The result shows that LW-IGMPv3 is not only compatible with old versions of IGMP, but also shows great improvements in router performance and scalability.
Some Issues of the Paradigm of Multi-Learning Machine - Modular Neural Networks
Authors: Wang Pan , Feng Shuai , Fan Zhun 
Published: January 2009

This paper addresses some issues on the weighted linear integration of modular neural networks (MNN: a paradigm of hybrid multi-learning machines). First, from the general meaning of variable weights and variable elements synthesis, three basic kinds of integrated models are discussed that are intrinsic-factors-determined, extrinsic-factors-determined, and hybrid-factors-determined. The authors point out: integrations dominated by both of the internal and external elements are highly correlative with not only the historical quality of the sub-networks, but also with the environment in which the information is processed. In the sense of the mean of square error (MSE), several sufficient conditions to improve the whole system's performance are given while deleting one/some sub-networks in all the networks population. Meanwhile, when the whole performance of the current MNN system possesses is unsatisfactory, a corresponding improved strategy which need add one/some sub-networks is presented. For the optimal weights vector under the framework of the weighted sum of the sub-networks' outputs, we point out some constraints forms of the sub-networks' integrated weights are unreasonable and present a general form while the corresponding computational algorithms are described briefly. The authors present a new training algorithm of sub-networks named “‘Expert in one thing and good at many’ (EOGM).” In this algorithm, every sub-network is trained on a primary dataset with some of its near neighbors as the accessorial datasets. Simulated results with a kind of dynamic integration methods show the effectiveness of these algorithms, where the performance of the algorithm with EOGM is better than that of the algorithm with a common training method.
One-Dimensional Localization Algorithm Based on Signal Strength Ratio
Authors: Yang Xinyu , Kong Qingru , Xie Xiaoyang 
Published: January 2009

Localization algorithm in wireless sensor networks has attracted significant interest in recent years. The RSSI approach is considered as the cheapest solution allowing coarse-grain, yet effective for many applications in outdoor environments. However, when environments change, there exists a big localization error using RSSI without a reconstructing data set. In order to solve the problem of reestablishing the data set when the environments change, a novel one-dimensional localization algorithm based on received signal strength ratio (1-DIM-RSSR) is proposed for the one-dimensional wireless sensor network applications, such as road surveillance and pipeline transmission. While synthetically considering accuracy, power consumption, localization time, and device costs, we can only use coordinate x to locate the nodes by defining y as 0. Our algorithm is based on the theory as follows: the values of Signal Strength vary from one environment to another. When environments change, even the distance between the transmitter and the receiver remains unchanged, but there is still at least 10dBm's difference. On the contrary, the ratio of the received signal strength from two base stations varies little in the condition of the unchanged distance, and thus it avoids reconstructing the dataset when environments change. 1-DIM-RSSR comprises of two phases: the data set construction phase and the localization phase. In the first phase, N reference nodes are uniformly distributed between the two base stations BS1 and BS2. We collect the signal strength RRi1 and RRi1 from BS1 and BS2 respectively and get signal strength ratio Ri = RRi1/RRi2 at each point, where i ϵ [1, N] corresponding to the N references nodes. In the localization phase, we record the signal strength ratio Rʹ of mobile nodes and pick the one that best matches the observed signal strength ratio. Our idea is to compute the distance | Ri - Rʹ| at a fixed set of locations, and then pick the location that minimizes the distance. Simulation and experiment results show that localization precision of the proposed algorithm compared with the RSSI algorithm is improved when the environments change. The proposed method is easy to operate, and need not reconstruct the dataset when the environments change. So this method holds the promise for many applications such as monitoring product lines, road surveillance, and pipeline transmission. Meanwhile, since our algorithm is based on 1-D localization, how to extend this conception to 2-D or even 3-D localization will be our ongoing work.
Bayesian Network-Based Service Context Recognition Model
Authors: Qiao Xiuquan , Li Xiaofeng 
Published: January 2009

Service context refers to the environmental information which influences the service execution. The processing of service context information is the foundation of the future intelligent telecommunication services in the ubiquitous convergent network. As the complexity and variability of the real world, there exists a large number of uncertain service context information, such as the imprecise information collected by sensors, data noise, and inaccurate location by different location technologies. Hence, it is crucial to recognize the correct service context environment based on unreliable context information. In recent years, context computing and context-awareness have become a major topic of research in an ubiquitous computing field. Ontology technology is often used to support context modeling and reasoning. And the probability theory, especially the Bayesian network, is adopted to deal with uncertainty. However, much of the existing relevant research work mainly concentrated on the modeling and reasoning of context information. But the way to construct and evolve the service context recognition model supporting uncertain reasoning effectively and systematically has not involved. In addition, most of the relative work is only the qualitative analysis, and lacks the quantitative performance analysis and experimental verification. What is more, the research on how to apply context-awareness technology to the telecommunication field and support the intelligence and individualization of the service is scarce. In this article, we combine context-awareness technology with telecommunication service network, and discuss the mechanism of service intelligence in ubiquitous convergent network environment. Then a construction method of the service context recognition model based on the Bayesian Network is put forward. The process of constructing the Bayesian network-based service context recognition model is mainly divided into the following steps: First, according to different service requirements and scenarios, the specific context problem domain should be specified; second, constructing the service context recognition model, which includes the determination of the topology structure and the node probability distribution of Bayesian network; third, when the preliminary Bayesian network-based service context recognition model is constructed, it could be initially applied to the practical system to do the clustering or causality analysis; and last, when the model cannot satisfy the need, the model update should be performed based on the feedback information of the evaluation step and the newly-generated plentiful sample data. This approach has been applied to intelligent access adaptation processing of call service in the office environment. The experimental results show that this approach can strengthen the intelligence of service and compensate for restrictions of certain reasoning.
The Reuse Policy in Developing Multi-Agent System
Authors: Xiao Xue , Lina Yao , Junwei Luo 
Published: January 2009

The agent-oriented (AO) methodology is an effective means for constructing distributed systems. Despite a great deal of research, a number of challenges still exist before making agent-based computing a widely accepted paradigm in software engineering practice. The problem of “difficult to implement agent-based system” originates from the gap between design models and system implementation to a high degree. Developers often feel that those characteristics depicted in agent design models are too abstract and difficult to implement. In order to solve this problem, the paper presents a hierarchical development architecture (HDA) approach to facilitate building up a new agent system. The HDA consists of two parts (analysis and design part, and the system implementation part), covering the entire development lifecycle. Each phase of the HDA is further categorized into a layered model structure. Based on the goal and the task of each layer, the user can fill different method fragments into the appropriate layers to handle different kinds of quality attributes. Instead of creating incompatible techniques, models and CASE tools for each methodology, modular and reusable models can be created once, and shared within different methodologies. It represents significant savings in the development cost and the learning cost. As the supporting tool, the method engineering process and design patterns play the key role in the HDA. In order to build a new method based on the reuse policy, we adopted (and extended) the method engineering paradigm. According to this approach, a new method is built by assembling pieces of method fragments from a method repository, which is a structural representation of the method fragments that compose the actual AO method with their composing relationships. In this way we could obtain the best method for our specific needs. In our view, the excellent design patterns will be a good choice for developers to customize their own infra-structure, which is flexible and pluggable. Therefore, a layered-structure is presented, aimed at giving an explicit guide about how to apply those patterns and an order of examination of pattern application. Through applying the HDA-based design patterns, developers can build applications from third party off-the-shelf solution components conveniently. To exemplify its feasibility and effectiveness, the construction of the C4I system is presented as a case study. An agent-oriented new approach derived from HDA is applied and the experimental result is satisfactory.
A Global Reputation Model for Grid Computing
Authors: Mei Yiduo , Guan Shangyuan , Gao Zhixing , Ma Siyuan , Dong Xiaoshe 
Published: January 2009

Trust and reputation are important decision-making factors in large-scale distributed systems. The Constellation Model is one of our previous works about grid resource management. Since local feedback plays an important role in aggregating global reputation, a new local feedback metric is introduced to reflect the dynamic feature of trust. This paper introduces our recent effort of combining reputation into the Constelltaion Model. We propose a novel global reputation model for grid systems such as Constellation Model. We model the relationship between global reputation and the nodes' feedback credibility. A node's feedback credibility which is calculated by similarity measurement will impact on its reputation in a direct way. In our model, to promote a node's reputation, there exist two possible ways: the first one is to provide high-quality services to others. The second way is to provide authentic feedbacks towards others. In addition, to evaluate a node's local feedback trustiness, approach based on similarity measurement is employed. If local feedback trustiness is too low, compensation calculated by exponential smoothing is applied. This design is employed to combat malicious collectives and slandering in large-scale communities. The computational framework of EigenTrust which is proposed by S. D. Kamvar at Stanford University is used to compute global reputations of all the nodes in the Constellation Model. In the Constellation Model, nodes (stars) in a solar system can be organized using a Peer-to-Peer way. Distributed Hash Table protocol such as Chord which is proposed by I. Stoica, et al. at University of California, Berkeley can be used to implement the distributed ranking mechanism. We have implemented a prototype of Constellation Model. Experimental results show that, our model can reflect dynamic characteristics of trust better. Our model can also improve the evaluation accuracy of global reputation by leveraging feedback credibility. In Comparison with EigenTrust, our model shows an improved robustness with the presence of malicious behaviors in the Constellation Model.