Completeness by Forcing Abstract. The completeness of the infinitary language L ω 1 ,ω was proved by Carol Karp in 1964. We express and prove the completeness of infinitary firstorder logics in the institution-independent setting by using forcing, a powerful method for constructing models. As a consequence of this abstraction, the completeness theorem becomes available for the infinitary versions of many "first order" logical systems that appear in the area of logic or computer science. The goal of this paper is to prove the completeness theorem for infinitary first order logics in the framework of institutions and then apply the general results to a couple of different concrete institutions. Although we emphasize the results obtained for infinitary logics, we will also obtain completeness results for finitary logics. However our results for the finitary case is weaker than the known completeness results for finitary first order logic [17] as it requires a countable number of of symbols in a signature. A paper with similar objectives dedicated to finitary logics that captures the case of uncountable signatures is [21] . The institutional approach to solving completeness problems has two main motivations. Firstly, it allows us to obtain in an uniform way completeness results for the infinitary versions of many specific logics like first order logic, order sorted logic, or logics for partial algebras. Secondly, the pattern of institutional reasoning is to find categorical definitions of the conditions that are sufficient for proving the desired results. The small and natural set of conditions that we identify for the proof of Theorem 2 helps in understanding at an abstract level "why" an infinitary logic is complete. As in [21] , we separate the deduction rules into two sets, rules that deal with the specific syntax of the atomic sentences and rules that deal with first order connectives and with quantification. This is a first step towards the idea that "first order logics" freely extend their "atomic" subpart in all regards: syntactically, semantically and as proof systems, and soundness and completeness are preserved by this free extension. A way to formalize this by means of institution morphisms is left to future investigation. The present paper introduces the forcing technique in institution-independent model theory, applies it for proving the completeness result, and points out some particular cases. One of the most important contribution of our study is the formalization of forcing in abstract model theory, thus providing an efficient tool for obtaining new results and showing the significance of the top-down approach towards model theory. Forcing is a technique invented by Paul Cohen, for proving consistency and independence results in set theory [4, 5] . A. Robinson [23] developed an analogous theory of forcing in model theory, and Barwise [2] extended Robinson's theory to infinitary logic and used it to give a new proof of Omitting Types Theorem. A general treatment of the Omitting Types Theorem may be found also in [19] . In Section 2 we present the notions of institution and entailment system. These will constitute the base for expressing the soundness and completeness condition for a logic, i.e. the semantic entailment is the same as the syntactic entailment. After presenting some well known examples of institutions we give the definitions of some important concepts that are used in this paper. Section 3 shows how logical connectives and their meaning can be attached to the definition of institution. In Section 4 we present an institutional version of the definition of a forcing relation. The main theorem of this section says that every generic set of properties has a model. In Section 5 we do the last step in setting the framework for expressing the completeness: we define what is a first order entailment system. The completeness theorem will be proved in the next section, i.e. Section 6. The last section relevant to this result, Section 7, lists a number of examples and shows how the abstract theorem of completeness can be instantiated to concrete cases. We have introduced the notion of forcing parameterized by a set of sentences in institution-independent model theory. Using this we have proved the completeness of the first order entailment systems in an abstract institutional framework and then we have instantiated the result to several concrete examples of institutions. A sound and complete entailment system for FOL, POA, OSA and PA may be derived from [21] , however we are not aware of similar completeness results for EQLN, QfFOL ω 1 , POA ω 1 ,ω , OSA ω 1 ,ω and PA ω 1 ,ω . The area of applications of Theorem 2 is much wider. For example we may consider variations of the institutions presented above such as first order logic with transitions or order sorted algebra with relations. A limitation of this presentation is that the signatures morphism used for quantifications are non-void. In future work we plan to eliminate this condition and also to make the theorem applicable to signatures with uncountable symbols but with finitary conjunctions. An institutional version of the Omitting Types Theorem is also considered for future research.

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On the strongly generic undecidability of the Halting Problem It has been shown in [J.D. Hamkins, A. Miasnikov, The halting problem is decidable on a set of asymptotic probability one, Notre Dame J. Formal Logic 47(4) (2006) 515-524] that the classical Halting Problem for Turing machines with one-way tape is decidable on a ''large'' set of Turing machines (a so-called generic set). However, here we prove that the Halting Problem remains undecidable when restricted to an arbitrary ''very large'' set of Turing machines (a so-called strongly generic set). Our proof is independent of a Turing machine model.

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Authentication Theory and Hypothesis Testing By interpreting message authentication as a hypothesis testing problem, this paper provides a generalized treatment of information-theoretic lower bounds on an opponent's probability of cheating in one-way message authentication. We consider the authentication of an arbitrary sequence of messages, using the same secret key shared between sender and receiver. The adversary tries to deceive the receiver by forging one of the messages in the sequence. The classical two types of cheating are considered, impersonation and substitution attacks, and lower bounds on the cheating probability for any authentication system are derived for three types of goals the adversary might wish to achieve. These goals are (a) that the fraudulent message should be accepted by the receiver, or, in addition, (b) that the adversary wishes to know or (c) wants to even choose the value of the plaintext message obtained by the legitimate receiver after decoding with the secret key. Message authentication is concerned with providing evidence to the receiver of a message that it was sent by a speci ed legitimate sender, even in the presence of an opponent who can intercept messages sent by the legitimate sender and send a fraudulent message to the receiver. Authenticity (like con dentiality) can be achieved by cryptographic coding based on a secret key shared by sender and receiver.. The security of cryptographic systems can be classi ed according to the assumed computational resources of an adversary. Security that holds when one assumes a suitable restriction on an adversary's computing power is called computational security while security that holds even when no bound on the adversary's computing power is assumed is called information-theoretic security.. This paper is concerned with information-theoretically secure message authentication, i.e., we consider a scenario in which the opponent has unlimited computing power and knows everything about the system, except for the secret key. We consider bounds on how e ciently a secret key shared by sender and receiver can be used or, more precisely, we derive lower bounds on an opponent's cheating probability that no authentication system with a given key size can overcome.. Compared to the theory of secrecy, de nitions in authentication theory are more subtle. For instance, while Shannon's de nition of perfect secrecy 15], which means that ciphertext and plaintext are statistically independent, is obviously the strongest possible de nition of secrecy, it is not clear how perfect authenticity should be de ned; the cheating probability can be made arbitrarily small by using a secret key of su cient size, but it can never be reduced to zero. Shannon 15] proved the well-known result that for any perfect cipher the secret key must be at least as long as the plaintext or, more precisely, that H(K) H(M) where M and K denote the message and the secret key, respectively. We refer to 8] for a generalization of Shannon's treatment of secrecy.. The rst lower bound results in message authentication were purely combinatorial 4], 3]. In 1984, Simmons 16 ] initiated a sequence of research activities on information-theoretic lower bounds in authentication theory 2 The goal of this paper is give a generalized and considerably simpli ed treatment of lower bound results in authentication theory. The key to this simpli cation is the natural observation that authentication, i.e. deciding whether a received message is authentic or not, is a hypothesis testing problem. The receiver is faced with two possible hypotheses: either the message was generated by the legitimate sender knowing the secret key, or by an opponent without a priori knowledge of the secret key. The joint probability distribution of the authenticated message and the secret key is di erent in both cases, and this may allow the receiver to distinguish between the two hypotheses. The goal of the paper is similar in spirit to some of Sgarro's work (cf. 13], 14]) who also investigated a general approach to authentication frauds, based on rate-distortion theory, showing that some of the known bounds follow from a more general result. Like Shannon's lower bounds 15] on the size of a secret key of a perfect secrecy system, the bounds of this paper show the impossibility of obtaining an arbitrary amount of security with a secret key of xed size. Constructions of authentication systems are not discussed in this paper, but there exists a substantial body of literature on that topic.. In Section II we discuss the message authentication problem and various cheating strategies. The literature is brie y reviewed in Section III, and hypothesis testing is described in Section IV. Lower bounds on the cheating probability for impersonation and substitution attacks are derived in Sections V and VI, respectively, and these results are combined in the concluding Section VII.

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A verifiable protocol for arguing about rejections in negotiation Recently argumentation-based approaches to negotiation have become popular [3]. The idea is that if negotiating agents exchange reasons for their proposals and rejections, the negotiation process may become more efficient and the negotiation outcome may be of higher quality. This paper especially focuses on reasons given for rejections of proposals. If an agent explains why he rejects a proposal, the other agent knows which of her future proposals will certainly be rejected so she will not waste effort at such proposals. Also, if a reason for rejection can be disputed, the negotiation process may be of higher quality since flawed reasons may be revised as a result. Accordingly, the aim of this paper is to formulate a protocol for negotiation with embedded persuasion dialogues about the reasons for rejecting a proposal. The key idea is that the propositional commitments incurred by the agents in the embedded persuasion dialogue constrain their behaviour in the surrounding negotiation dialogue. Recently argumentation-based approaches to negotiation have become popular [3] . The idea is that if negotiating agents exchange reasons for their proposals and rejections, the negotiation process may become more efficient and the negotiation outcome may be of higher quality. This paper especially focuses on reasons given for rejections of proposals. If an agent explains why he rejects a proposal, the other agent knows which of her future proposals will certainly be rejected so she will not waste effort at such proposals. Also, if a reason for rejection can be disputed, the negotiation process may be of higher quality since flawed reasons may be revised as a result. Accordingly, the aim of this paper is to formulate a protocol for negotiation with embedded persuasion dialogues about the reasons for rejecting a proposal. The key idea is that the propositional commitments incurred by the agents in the embedded persuasion dialogue constrain their behaviour in the surrounding negotiation dialogue. In this paper we have presented a verifiable protocol for negotiation with embedded argumentation. In doing so, we have exploited the general format of [1, 2] of dialogue systems. In the resulting dialogue game reasons for rejections can be asked and, when given, can constrain further offers unless the offering agent can persuade the rejecting agent that the reason is not tenable. Thus a negotiation is sometimes more efficient since offers that will certainly be rejected can be avoided, and it is sometimes of higher quality since flawed reasons can be revised. The persuasion protocol is flexible in that it allows for different underlying logics, for alternative replies and for postponing replies, sometimes even indefinitely. Yet a strong focus of dialogues is maintained through the requirement of relevance.

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Security Analysis of a Single Sign-On Mechanism For Distributed Computer Networks Single sign on mechanisms allow users to sign on only once and have their identities automatically verified by each application or service they want to access afterwards. There are few practical and secure single sign on models, even though it is of great importance to current distributed application environments. Most of current application architectures require the user to memorize and utilize a different set of credentials (eg username/password or tokens) for each application he/she wants to access. However, this approach is inefficient and insecure with the exponential growth in the number of applications and services a user has to access both inside corporative environments and at the Internet. Single sign on (SSO) is a new authentication mechanism that enables a legal user with a single credential to be authenticated by multiple service providers in distributed computer networks. Recently, Chang and Lee proposed a new SSO scheme and claimed its security by providing well organized security arguments. In this paper, however, it is shown that their scheme is actually insecure as it fails to meet security during communication, in order to provide a secure authentication digital signature with hash function is researched for future work. A distributed computer system consists of multiple software components that are on multiple computers, but run as a single system. The computers that are in a distributed system can be physically close together and connected by a local network, or they can be geographically distant and connected by a wide area network. A distributed system can consist of any number of possible configurations, such as mainframes, personal computers, workstations, minicomputers, and so on. The goal of distributed computing is to make such a network work as a single computer. Distributed systems offer many benefits over centralized systems, including the following: We demonstrated two effective impersonation attacks on Chang and Lee's single sign-on (SSO) scheme. The first attack shows that their scheme cannot protect the privacy of a user's credential. The second attack violates the soundness of authentication .we proposed an improved Chang-Lee scheme to achieve soundness and credential privacy.It is shown that their scheme is actually insecure as it fails to meet security during communication, in order to provide a secure authentication digital signature with hash function is researched for future work.

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Design-in-play: improving the variability of indoor pervasive games Abstract Treasure is a pervasive game playing in the context of people's daily living environments. Unlike previous pervasive games that are based on the predefined contents and proprietary devices, Treasure exploits the "design-in-play" concept to enhance the variability of a game in mixed-reality environments. Dynamic and personalized role design and allocation by players is enabled by exploring local smart objects as game props. The variability of the game is also enhanced by several other aspects, such as user-oriented context-aware action setting and playing environment redeployment. The effectiveness of the "design-in-play" concept is validated through a user study, where 15 subjects were recruited to play and author the trial game. The development of wireless sensor networks (WSNs) has propelled various innovative applications in smart environments. Pervasive gaming, a new genre in the field of entertainment, is one of its productions. By blending of real and virtual elements and enabling users to physically interact with their surroundings during the play, people can become fully involved in pervasive games and attain better gaming experience [15] .. A number of projects or prototypes on pervasive games have been built [2] [3] [4] [5] [6] [7] [8] 16 ] (see Section 2 for details). Existing systems have greatly contributed to pervasive gaming research by emphasizing different natures of ubiquitous interaction. However, as the contents and game settings in these games are all predesigned by game developers (we call it the "design-before-play" paradigm), the variability of them is quite low, which may lead negative user experience to players during repeated plays. Broadly speaking, a typical pervasive game consists of five key elements: the playing field, physical props (roles acted by physical objects, like a magic wand), roles acted by players, game rules, and multimedia contents. Benefiting from the pervasive nature of pervasive games, the playing field can be changed from different places (e.g., from one room to another [3, 6, 16] , from one street to another [2, 4, 7] ). Nevertheless, because the physical props used in these games are proprietary (particular designed flags [5] , cottage and hand icons [16] , etc.), they should be deployed into the new environment when the playing field changes. In addition, as the props are proprietarily offered and limited on numbers, players are not allowed to add new prop-based roles. The unchangeable props reduce the variability of the games. The latter three elements, on the other hand, are logical or virtual contents pre-specified or provided by game developers, which are also unalterable to players.. The system presented in this paper, called Treasure, makes an attempt to address the issues mentioned above. Treasure is a treasure-hunting game playing in the context of people's daily life. Different from the previous "design-before-play" paradigm enabled games, it seeks to improve the pervasive game's variability by introducing the "design-inplay" concept, which allows people to generate variations of a meta-game before playing it. The following attempts were made to achieve a big variability:. & Dynamic role design and allocation by employing local everyday objects. According to Weiser's vision on ubiquitous computing [19] , homes in the near future will be filled with sensor-augmented everyday objects, called smart objects. By analyzing the data from the attached sensors (e.g., location sensors [11] , acceleration sensors [1] , pressure sensors [18] , RFID tags [20] ), smart objects can provide various assistance to people's life, such as helping people quickly locate them [11, 20] , or identifying indoor human behaviors [1, 18] . Unlike providing particularly-designed game props, we exploit the prospect of using smart objects in pervasive games. Leveraging local smart objects as game props provides the following merits: (1) The normal, plentiful nature of smart objects allows users to dynamically add new prop-based roles into the game and select interested objects to play the new roles (e.g., choosing a smart pen to play the 'magic wand' role); (2) it enhances the variability of the game by letting different objects to play the same role (replacing the smart pen by a smart phone to play the 'magic wand' role). & Player configurable context-aware action setting. Players play the game by physically interacting with prop-based roles distributed in the house, such as moving a 'magic wand' or opening a drawer. For each detected human-prop interaction context, a player can specify a preferred multimedia action to respond (e.g., playing a narrative or displaying an adventure animation).. & Reconfigurable game environment setting. The game environment consists of a playing field and physical props. As the whole smart house is used as the playing field, players can reconfigure the game environment by rearranging the object-based props in the house, for example, placing a prop to a particular place (e.g., hiding the 'magic wand' in a drawer), etc.. To the best of our knowledge, research on playing and player-authoring of smart-object based games has not been explored by previous studies. In the following sections, we firstly review related work on pervasive gaming. The Treasure game will then be described, followed by the technical support for the implementation of this game. The effectiveness of our system is evaluated through a user study, with users to perceive and test different support to enhance game variability. Treasure represents our early efforts to increase the variability of pervasive games in mixedreality environments. The "design-in-play" principle, which allows end users to create or alter contents before each game play, is proposed to achieve this. To support dynamic and personalized role design, we explore the numerous smart everyday objects in smart homes as props. Treasure further allows players to configure the context-aware actions of the roles they created and reorganize the physical objects in the gaming environment. The evaluation results from an initial user study reveal that diverse gaming experiences can be generated and better user experience can be attained by allowing users to configure different elements of a meta-pervasive-game. Based on the feedback from the subjects, we intend to make the authoring kit more userfriendly by introducing more graphical elements. In view of the fact that user content sharing has been a trend in the social networking era, we plan to create a general platform that enhances user cooperation and content sharing in the development of indoor pervasive games. Mechanisms will also be provided that allow users to create simple games and share their experiences with their peers. Different approaches and varied forms have been explored in developing pervasive games. One approach is to augment traditional, real-world games with computing functionality. The enabled games include smart toys [8] , storytelling games [3, 16] , and augmented outdoor games [5] . Another approach, on the contrary, attempted to map computer games onto realworld settings, as demonstrated by Touch Space [6] and Human Pacman [7] . There are also a few location-aware games [2, 4] , where a building, a street, or even a city becomes a game board and the players become playing pieces. Treasure follows the first approach, which aims at augmenting traditional treasure hunt game with computing functionalities.. There are several types of treasure hunt games which can have one or more players who try to find hidden articles or places by using a series of clues. Gold Miner (http://www. goldminergame.net/) is a video-based treasure hunt game designed for children. The locationaware game presented in Chalmers et al. [4] allows players to collect virtual coins that are hidden in the game area based on GPS information. Compared with these systems, the Treasure game provides better user experience by allowing them to hunt physical 'treasures'.. There have been several studies that examine pervasive gaming in normal, daily settings. SupaFly [13] is a mobile-phone based virtual community game, where players can create characters and interact through them by sending SMS commands. The player's goal is to reach the highest level of status in the community by socially interacting with others (e.g., meeting nearby players, making new friends). NEAT [21] is a pervasive game that seeks to encourage physical activity in the daily routing of players. Data from player-equipped sensors is logged to the cell phone and control the animation of an avatar that represents the player in a virtual race game with other players over the cellular network. These systems demonstrate well how pervasive games affect our daily livings. Treasure is also a game playing in daily settings. Different from the prior two systems, we particularly concern how plentiful everyday resources and user participation can extend the variability of game experiences in smart homes.. User content creation is not new to video games, which has been used in commercial games like Tank 1990 (developed by Nintendo), Counterstrike (a first-person shooter game), and academic game studies like Storytelling Alice [14] . Users are either allowed to create game maps or author stories in them. Treasure extends the user creation concept used in these video games by enabling users to handle a number of gaming elements in mixedreality environments, such as everyday-object based role design and real-world game environment setting. Due to the nascent of the field, there are quite few studies about user creation in pervasive games. StoryRoom [16] is a storytelling game that allows children to create simple If-Then rules that facilitates story telling. The game is played in a particular designed storytelling corner and limited proprietary props are provided. The context-aware rules are created through a physical programming method, which can build connections between a prop-touch event and an actuator-based action. The EU-IP iPerg project [12] explores a text-messaging method that allows players to remotely control the activities of their "avatars" (e.g., changing locations/destinations, communicating with other players) on a physical game board in the "Day of the Figurines" game. There are also on-the-spot operators (co-producers) that can modify the game state, give response to messages from players. Comparing with StoryRoom and iPerg, Treasure opens up a wider space to increase game variability. First, it extends the game field from particular-designed game board to the whole end users' living environments (i.e., smart houses). Second, considering that different houses have different layout and physical/virtual resources (smart objects, multimedia contents, etc.), exploring smart objects as props and allowing multimediaaction settings enhances the diversity of enabled games. Third, the scope of participants on game authoring is much wider in our system. StoryRoom is designed for children for storytelling. iPerg, however, explores fixed operators (staffs, game designers) while not normal players to co-produce the game. Finally, our system allows users to freely add new roles (by exploring various smart objects in smart houses). The two prior systems only allow children to alter the behaviors of existing roles.

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


Modeling short-lived TCP connections with open multiclass queuing networks Abstract. In this paper we develop an open multiclass queuing network model to describe the behavior of short-lived TCP connections sharing a common IP network for the transfer of TCP segments. The queuing network model is paired with a simple model of the IP network, and the two models are solved through an iterative procedure. The combined model needs as inputs only the primitive network parameters, and produces estimates of the packet loss probability, the round trip time, the TCP connection throughput, and of the average TCP connection completion time (that is, of the average time necessary to transfer a file with given size over a TCP connection). The model presentation is centered on TCP-Tahoe, but the model of TCP-Reno is also available and results are presented. The analytical performance predictions are validated against detailed simulation experiments in a realistic networking scenario, proving that the proposed modeling approach is accurate. Modeling the TCP behavior is receiving great attention both from the academic and the industrial community. The reason for such enormous interest is essentially one: The behavior of TCP drives the performance of the Internet. Over 90% of the Internet connections use TCP, and over 95% of the bytes that travel over the Internet use TCP; hence, the availability of an accurate model of TCP is a necessity for the design and planning of Internet segments and corporate Intranets.. Models appeared so far in the literature can be grouped in two classes:. 1. Models that assume that the RTT and the loss characteristics of the IP network are known, and try to derive from them the throughput (and the delay) of TCP connections; to this class belong works as [1, 2, 3] ; 2. Models that assume that only the primitive network parameters (topology, number of users, data rates, propagation delays, buffer sizes, etc.) are known, and try to derive from them the throughput and the delay of TCP connections, as well as the RTT and the loss characteristics of the IP network; to this second class belong the works in references [4, 5, 6, 7, 8] and many others. Often, models in the second class incorporate a model similar to those of the first class, together with a simplified model of the network that carries the TCP segments and the two models are jointly solved through a fixed point iterative procedure. This situation is illustrated by Fig. 1 , where the 'TCP sub-model,' describes the behavior of TCP connections, and the 'network sub-model,' focuses on the underlying IP network. The TCP sub-model computes the offered load to the system, given the average RTT and loss probability. The network sub-model estimates the RTT and the loss probability, given the offered load to the system.. With reference to our previous work, the contribution of this paper lies in the detailed presentation of the Open Multiclass Queueing Network method applied to TCP. The work presented in [7] assumed greedy connections using a closed queueing model. The work presented in [9] was concerned with a performance comparison between TCP-Tahoe and TCP-NewReno; results were obtained with OMQN models; however, the models themselves were not discussed. In [10] , finally, we presented an overview of the modeling technique presented here, but a detailed application of the OMQN technique to a specific protocol, describing service times derivation and queues transition probabilities was not discussed in detail.. In this paper we use open multiclass queuing networks to develop a model that describes the behavior of an arbitrarily large number of short-lived TCP connections sharing a common infrastructure for the transfer of TCP segments. The model needs as inputs only primitive network parameters, and produces estimates of the packet loss probability, the RTT, the TCP connection throughput, and of the average TCP connection completion time. The TCP model presented here allows an unprecedented modeling accuracy for interacting short-lived TCP connections, yet maintaining a computationally simple solution. The level of insight in TCP dynamics offered by the model is also very high.. We use simulation experiments to validate our modeling approach, showing that the performance estimates that our models can generate are extremely accurate. In this paper we have developed an OMQN model to very accurately describe the behavior of short-lived TCP connections that exploit a common IP network for the transfer of finite-size files.. Starting from the primitive network parameters, the queuing network model is solved together with a simple model of the IP network, through an iterative procedure, and the average time for the completion of the file transfer is estimated, along with the TCP connection throughput and goodput.. The presented modeling approach was applied to TCP-Tahoe, and TCP-Reno (which is also shortly discussed in [8] ), and it is currently being extended also to TCP-SACK.. The analytical performance predictions generated by the model for realistic networking scenarios have been validated against detailed simulation experiments, proving that the proposed modeling approach is extremely accurate and flexible, besides providing an excellent insight into TCP dynamics and behavior.. Results validating the model discussed in the paper were obtained for relatively slow networks (10-45 Mbit/s bottlenecks) due to the impossibility of obtaining reliable simulation results with higher speeds. It must be noted, however, that the model complexity is independent from the network speed. Hence OMQN models are a good means to ferecast the bahavior of protocols like TCP in very high speed netorks.

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From enzyme kinetics to epidemiological models with Michaelis-Menten contact rate: Design of nonstandard finite difference schemes We consider the basic SIR epidemiological model with the Michaelis-Menten formulation of the contact rate. From the study of Michaelis-Menten basic enzymatic reaction, we design two types of Nonstandard Finite Difference (NSFD) schemes for the SIR model: Exact-related schemes based on the Lambert W function and schemes obtained by using Mickens's rules of more complex denominator functions for discrete derivatives and nonlocal approximations of nonlinear terms. We compare and investigate the performance of the two types of schemes by showing that they are dynamically consistent with the continuous model. Numerical simulations that support the theory and demonstrate computationally the power of NSFD schemes are presented. One of the most basic enzymatic reaction was proposed more than a century ago by Michaelis and Menten. Following [1] in this introductory section, the process involves a substrate S that reacts with an enzyme E to form a complex ES which in turn is converted into a product P and the enzyme. This is represented schematically by. where k 1 , k −1 and k 2 are positive constant parameters associated with the rates of reaction. Denoting, as usual in biochemistry, by [X] the concentration of a reactant X, the mass action principle leads to the following model for this basic enzymatic reaction:. The system (1)- (4) . In order to study the dynamics of the complex system (1)-(4), the tradition is to make the so-called Standard Quasi Steady -State Assumption (sQSSA). That is, at the initial stage of the complex [ES] , formation is very fast after which it is essentially at equilibrium i.e., This paper is an extension of the authors' work [9] to the basic SIR epidemiological model where the contact between the susceptible individuals and the infected individuals is expressed by a nonlinear term which is similar to the right-hand side of the Michaelis-Menten ordinary differential equation. Using the specific form of the nonlinear term, we introduced new NSFD schemes based on the one hand on Mickens' rules [6] and on the other hand on the exact scheme of the M-M equation defined via the Lambert W function. We showed theoretically and computationally that the new NSFD schemes are dynamically consistent with the continuous model. The NSFD schemes that are not exact perform as efficiently as the exact-related schemes, confirming thus the power of the nonstandard approach. In addition, the designed schemes are very efficient compared to standard schemes. This is due mainly to the structure of the denominator function φ i (∆t), which reflects the dynamics of the continuum models and which has very large permissible step size compared to standard schemes. In particular, all simulations were performed on an Intel Core Quad CPU, 2.50GHz, 2.0GB RAM, with a typical run requiring less than 2 seconds of computation time. The fact that the computer time is not a concern for NSFD schemes was also observed for complex and chaotic phenomena such as vibro-impact problems, see [22] .. Our future interest is in the extension of the results of this study to more complex epidemiological models. In line with [23] , a typical model we have in mind is the spread of diseases in space governed by the following advection-reaction-diffusion system:. When there is no diffusion, c = 0, NSFD schemes can be obtained from the discrete advection schemes (35)-(37) combined with the approach in Section 4.

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Interorganizational coordination and awareness in a nonprofit ecosystem Nonprofit organizations working with high-risk vulnerable populations such as human trafficking victims often need to engage in a significant level of interorganizational collaboration. Given the importance for nonprofits to be able to work with many different organizations, and given the importance of awareness in initiating and facilitating such collaborations, we conducted a field study to explore existing practices around coordination and awareness across a specific ecosystem of nonprofit organizations. In this paper, we provide an in-depth reflection on interorganizational issues among a cross-section of nonprofits. We identify four aspects of the interorganizational context in which these nonprofits must operate, as well as challenges they may encounter. Our goal is to illuminate first steps towards finding appropriate technological solutions for supporting coordination and awareness between these organizations so they can be more effective in accomplishing their mission. Nonprofit organizations that serve high-risk vulnerable populations (HRVPs) comprise some of the more challenging subsectors within the nonprofit sector. These populations, which include the homeless, victims of human trafficking, and others, are often illiterate, unable to access what mainstream users come to view as basic technologies such as phones or computers, and frequently require a level of services and care that demands complex and orchestrated resources from a wide-range of organizations over a period of months or even years. Since no single organization can provide the diverse set of resources and services necessary to serve HRVPs, public sector and nonprofit organizations try to cope through collaborative interorganizational efforts.. Research by Ugarte et al. [11] demonstrate the critical importance of such interorganizational collaboration needed by organizations to effectively accomplish their mission. In one case study, they enumerate 21 different organizations that had to be involved in the identification, intervention, and subsequent rescue of a 15-year old victim of sex trafficking [11] . These organizations ranged from government agencies such as the Mexican Judicial Federal Police, the Desarrollo Integral de la Familia to investigate the victim's family, the Mexican Consulate Minor Protection, the US attorney's office to help prosecute the traffickers, a group home in Georgia to provide shelter in case management, the FBI, the San Diego Sherriff's Department, and so forth. This list demonstrates the extent to which organizations working with HRVPs often must coordinate with other organizations.. However, such interorganizational collaboration also means that they must grapple with the significant complexity added by having to cooperate across international borders, and different state and city jurisdictions. Particular to the case of human trafficking, the mobility of many victims means that they cross jurisdictional lines, requiring coordination among both nonprofits and the legal establishment in several locales in order to provide service and prosecute traffickers. The diffuse nature of the human trafficking problem escalates the complexity of the coordination required and can lead to inefficient interorganizational cooperation where there is confusion, unnecessary redundancy, and gaps in services. According to the U.S. State Department, human trafficking is a significant issue globally, as well as in major cities across the U.S. (e.g., New York City, San Francisco, Atlanta, Los Angeles, New Orleans, Seattle, Philadelphia, Chicago, and Dallas among others); there are potentially 27 million victims of trafficking worldwide [38] . Those who engage in human trafficking tend to prey on the vulnerable such as young children, women who were orphans and the impoverished. For example, in one Southeast Asian country, a child can be purchased from a destitute family for a few dollars to be a sex-slave at a brothel [2] . The complexity in coordinating to address such a wide-spread problem is further increased by the specialization or "siloing" present in this (and many other) nonprofit subsectors: specific nonprofits may focus on narrow slices of the overall service picture, such as victim counseling, immigration assistance, job placement, child care, and so forth [11, 17] .. While settings in which complex coordination work takes place have often been a topic of CSCW-related research (e.g., [1, 15, 24, 3, 41] ), few studies have focused specifically on the challenges of coordination in the interorganizational context, specifically when this coordination may involve radically different types of organizations, such as nonprofits, policy makers, and legal authorities. To better understand the unique challenges and opportunities in this context, we began our work with nonprofits in early 2008, focusing specifically on a HRVP subsector known to involve a range of different stakeholders that must collaborate out of necessity: organizations dedicated to mitigation of human trafficking, and support for victims of trafficking. Our goals were both to characterize current interorganizational coordination practices and challenges, and identify opportunities for technology to support cross-organizational information sharing.. During that time, we were told by many of our study participants of the challenges faced by their organizations in not only coordinating action but also in even knowing which relevant other organization might exist in the first place. Our participants described a "felt need" in the antitrafficking community for a means to help members of the public and other organizations "find each other." In other words, the challenges faced by these organizations included not just problems in coordinated action, but also what might be termed interorganizational awareness-knowing what other organizations might be out there that could help with a particular case. This awareness of other organizations plays a critical role in the ability of nonprofits to initiate and facilitate collaborations needed in their work [11, 37] .. To investigate the coordination and awareness challenges among nonprofits, we conducted a field study over a period of five weeks of 17 different organizations, including nonprofits, governmental agencies, policy makers, and police departments. This paper presents the results of that fieldwork. We organize the findings along the following four themes: 1) pockets of awareness between nonprofit networks, 2) conflict in interorganizational collaboration modes, 3) power asymmetries between donors and organizations, and 4) challenges in general for nonprofits.. Our research contributions are two-fold. First, we provide insight into a problem domain that has not been widely studied in CSCW, yet which has a high need for collaboration and coordination. Second, we explore how specific characteristics of this problem domain-including structural, factors, technological factors, and organizational factors-pose challenges for simply applying technological solutions that may work in the for-profit world. These insights illuminate opportunities for addressing the unique set of collaboration challenges and opportunities that exist in this domain. To summarize, we investigated interorganizational coordination and awareness issues among a group of nonprofit organizations engaged in anti-trafficking work. We were motivated by the fact that anti-trafficking work is necessarily highly collaborative and also by the specific challenges to collaboration that exist in this environment, which prevent coordinated action and even basic existence awareness of other organizations.. Our work has illuminated a number of aspects of the collaborative context for one particular ecosystem-the network of nonprofits, governmental agencies, policy makers, and enforcement authorities involved in coordinated action against human trafficking. Despite the necessity of coordinated action within this ecosystem, brought about by specialization among agencies, the spanning of geographic boundaries, and other causes, a number of factors limit the efficacy of organizations working together. These factors are structural (hinging on factors in the ecosystem itself, such as inherent competitiveness due to funding pressures), technological (such as asymmetry in ICT access), organizational (reliance on volunteer workforce), and individual (hinging on personal motivations and trust relationships among individuals).. The four themes that emerged as part of the context point to particular nuances of the nonprofit context that should be considered in designing solutions to facilitate collaborations between organizations. The primacy of individuals over organizations indicates that a direct translation of an organization's contacts list of other organizations into something online may be insufficient for conveying adequate interorganizational awareness. A straightforward sharing of contact information loses aspects of the trust relationship that are essential in this subsector. Additionally, the high turnover in organizational population introduces a temporal element into the coordination dynamic, since the rapid decay in data "freshness" complicates interorganizational awareness. The dynamics of power asymmetry and "saving face" and having to fight a crisis under "normal conditions" indicate that simple lists posted in a publicly accessible way will likely be insufficient to convey the rich interorganizational awareness data that our participants must necessarily rely on to accomplish their mission.. Our data characterizing this ecosystem points to the need to facilitate interorganizational collaboration -particularly for nonprofit subsectors that must go beyond one-to-one collaborations with organizations. Further research is needed to identify the specific dimensions of coordination and awareness information that are useful for facilitating collaboration that spans the full range of interorganizational relationships [16] . Having examined collaboration and interorganizational awareness issues across a cross-section of nonprofits enabled us to identify a larger pattern of collaboration challenges than would have been possible by focusing on just one or two organizations.. The challenges our participants faced in interorganizational coordination and awareness may be indicative of an emergence of a nonprofit network. That is, since the organizations we studied must necessarily pursue a high degree of interorganizational interactions, one possible interpretation of the findings based on interorganizational theory is that the nonprofits we studied may be part of an emerging network organizational form. As described in [36] , a network organizational form is composed of a collection of actors, such as independent nonprofits, "that pursue repeated, enduring exchange relations with one another and, at the same time, lack a legitimate organizational authority to arbitrate and resolve disputes that may arise during the exchange." What seems to drive the emergence of a network organizational form among the nonprofits we studied could be explained by task interdependence [27] and resource dependence [35] . Our finding regarding the differing collaboration modes potentially augments existing interorganizational theory regarding these drivers for the emergence of the network organizational form by identifying a goal-based driver. It is also possible that the challenges we identified such as operating in pockets of awareness would be indicative of any group of organizations in an emerging network state.. In interpreting our findings regarding interorganizational coordination and awareness challenges as being indicative of an emerging network organizational form, we believe that more research will be needed to understand the exact nature of these nonprofits as a network. The work by Denning and Hayes-Roth regarding Hastily Formed Networks and the levels of networks identified in [8, 9] may provide some guidance in this regard. Often the interorganizational coordination and awareness needs of the nonprofits we studied were beyond that supported in the design of many systems primarily created to facilitate collaboration within an organization. We believe that this points to potential future work in understanding how coordination and awareness can be better supported beyond the individual to the interorganizational and inter-network contexts. Intra-organizational, rather than inter-organizational, coordination and awareness has been studied extensively, particularly in the context of groupware system use [1, 14, 19, 23] . However for clarification, we reiterate here two key differences in our work from this existing research. The first is that in our work, we do not evaluate any system designed as a solution to address coordination and awareness problems. The second and more importantly, is that our study focused on coordination and awareness between nonprofit organizations rather than between persons within a corporate organization (such as individual knowledge experts as in systems like AnswerGarden, and Eureka [1, 3] ). While our interorganizational focus differs from the work we mention, this prior research helps us to delineate the collaboration boundaries that needed to be considered in our study.. In the context of interorganizational literature, our research is informed by two sets of theories regarding coordination between organizations: the first is collective action research on networks of organizations [19, 22] , and the second is exchange and resource dependency theories [35] . With regard to collective action research, we draw upon Marwell and Oliver's designation of collective action as actions surrounding "mutual interests and the possibility of benefits from coordinated action" [22] . Based on literature on antitrafficking work, we see much opportunity for coordination between organizations (as explained by collective action theory) to be motivated by the mutual interest of mitigating human trafficking as well as benefits from coordinated action such as joint funding pursuits.. Although much of the literature [14, 27] focuses on overcoming obstacles to collective action within existing ties within an interorganizational network, we seek to contribute to this work with an in-depth examination of a context where interorganizational ties may not yet exist and the capability of developing such ties is hindered by external factors and challenges such as lack of awareness. Our intent is to provide a better understanding of the prior conditions needed to help organizations form effective network ties in pursuing collective action.. With regard to exchange and dependency theories of coordination between organizations, we understand through such theories that there are drivers for collaboration that act as catalysts for establishing ties between organizations. Two drivers identified in the literature that are particularly relevant to our work are task interdependency [27] and resource dependence [35] . Although we found evidence of these two drivers operating in the nonprofits we studied, our work complements this research by identifying what seems to be a goal-based driver for motivating coordination ties between organizations (this is discussed further in the second theme of the Findings section below).

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


LBM based flow simulation using GPU computing processor Objective: coupling efficiently the two approaches 1 A double population lattice Boltzman method with non-uniform mesh for the simulation of natural convection in a square cavity, Int. Due to the market (realtime and high definition 3-D graphics), GPU has evolved into highly parrallel, multithreaded, multi-core. The bandwidth of GPU has also evolved for faster graphics purpose.

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Semi-automated schema integration with SASMINT The emergence of increasing number of collaborating organizations has made clear the need for supporting interoperability infrastructures, enabling sharing and exchange of data among organizations. Schema matching and schema integration are the crucial components of the interoperability infrastructures, and their semi-automation to interrelate or integrate heterogeneous and autonomous databases in collaborative networks is desired. The Semi-Automatic Schema Matching and INTegration (SASMINT) System introduced in this paper identifies and resolves several important syntactic, semantic, and structural conflicts among schemas of relational databases to find their likely matches automatically. Furthermore, after getting the user validation on the matched results, it proposes an integrated schema. SASMINT uses a combination of a variety of metrics and algorithms from the Natural Language Processing and Graph Theory domains for its schema matching. For the schema integration, it utilizes a number of derivation rules defined in the scope of the research work explained in this paper. Furthermore, a derivation language called SASMINT Derivation Markup Language (SDML) is defined for capturing and formulating both the results of matching and the integration that can be further used, for example for federated query processing from independent databases. In summary, the paper focuses on addressing: (1) conflicts among schemas that make automatic schema matching and integration difficult, (2) the main components of the SASMINT approach and system, (3) in-depth exploration of SDML, (4) heuristic rules designed and implemented as part of the schema integration component of the SASMINT system, and (5) experimental evaluation of SASMINT. The increase in the number of databases has entailed the management of related data in different formats across these databases. In order for organizations to use other organizations' data for better decision-making and success, they need to understand the semantics and retrieve from these other distributed and heterogeneous data sources. As a result, the need for integrating or interconnecting these databases or enabling interoperability between them has become apparent. This requirement has become clearer with the increasing demand for collaboration among organizations.. More and more organizations understand the need to work together in order to better achieve their common goals. As a result of this tendency towards collaboration, during the recent years, information and communication technologies (ICT) have been focusing on how to make the collaboration among organizations easier by providing some supporting tools. In order to facilitate collaboration among organizations, one of the requirements that need to be met is enabling transparent access to heterogeneous data shared by other organizations.. A variety of approaches have been defined in research aiming at database sharing and integration, such as multidatabases and federated databases. There is however no single definition for these approaches, rather different varieties of each are addressed in publications. In this paper, we use the following definitions: A multidatabase system is a distributed database system, where databases can be either homogeneous or heterogeneous. According to the classification of Sheth et al. [58] , there are two types of multidatabase systems: non-federated and federated. Component database systems in a non-federated database system are not autonomous. On the other hand, the components in a federated database system preserve their autonomy while also sharing their data in a partial and controlled manner. Federated databases are further categorized by Sheth et al. [58] as loosely coupled and tightly coupled. In loosely coupled systems, there is no single global schema and the aim is to make databases interoperable. On the other hand, in a tightly coupled system, there is a single global schema or multiple federated schemas if it has multiple federations. For generating both the global schema in a tightly coupled system and the federated schema(s) in a loosely coupled system, schema integration is required.. Schema integration has been a fundamental issue in data sharing among distributed, heterogeneous, and autonomous databases. With the increasing number of databases, integration problem has become more apparent. Schema integration aims at finding a unified representation of schemas by merging them. In order to integrate schemas, syntactic, semantic, and structural relationships among elements of these schemas need to be identified.. Schema integration has been the subject of intensive research in databases. Two types of schema integration are defined: (1) View Integration, which is performed during the database design process, for example at the conceptual design phase, and (2) Database Integration, which produces the global schema of a number of databases [8] . Considering the goals of our work, we focus on the database integration. Database integration has been an important problem that needs to be tackled within the increasing number of distributed databases.. Research on schema integration has resulted in a number of methodologies. In Batini et al. [8] several methodologies, including Batini and Lenzerini [7] , Dayal and Hwang [17] , ElMasri et al. [20] , Mannino and Effelsberg [43] , Motro and Buneman [49] , are described for schema integration. In all of the cases, there is an assumption of full semantic and structural knowledge available to the integrator. Furthermore, most of the methodologies do not aim at developing semi-automated systems. However, since schema integration is a difficult and complex task, there is a need to help users with this complicated task by providing some semi-automatic mechanisms.. A number of recent efforts focused on semi-automatic schema integration or merging, including Chiticariu et al. [14] , Melnik et al. [45] , Pottinger and Bernstein [52, 53] , Saleem et al. [56] . However, proposed solutions are not generic enough. Instead of generating a comprehensive system and providing a complete solution, each work focuses on a specific subject. It is most of the time assumed that correspondences among source schemas are already given. Furthermore, it is not clear how to use the results of schema integration, for example for query processing over the integrated schema.. The most challenging part of schema integration is the identification of correspondences between elements of schemas from heterogeneous databases, which is referred to as schema matching. Matching problem has been tackled in different domains besides schema matching, such as matching media data [13] . Schema matching itself is identified as a fundamental process in variety of areas. Besides schema integration, schema matching is required for data warehousing, data integration, and peer-to-peer data management. Furthermore, schema matching is also correlated with ontology matching. Ontology matching has been an active research area especially with the increasing popularity of Semantic Web and peer-to-peer networks. For example, Haase et al. [31] uses ontology matching for peer selection. A large number of ontology matching systems have been proposed, as surveyed in Choi et al. [15] , Euzenat and Shvaiko [22] , Kalfoglou and Schorlemmer [36] .. Although large numbers of efforts have focused on providing access to distributed, autonomous, and heterogeneous databases, including the PEER system [1, 59] , the Mediator EnvirOnment for Multiple Information Sources project (MOMIS) [10] , the InfoSleuth project [9] , the SIMS project [4] , the Observer system [46] , the Stanford-IBM Manager of Multiple Information Sources (TSIMMIS) system [26] , and the COntext INterchange (COIN) project [28] , they mostly lack the step of semi-automated schema matching and thus require a large amount of manual work. Schema matching has been considered as a separate research problem and its related challenges have been addressed by a number of research and development projects, including Aumueller et al. [5] , Do and Rahm [18] , Giunchiglia et al. [27] , Li and Clifton [39] , Li et al. [40] , Madhavan et al. [41] , Melnik et al. [44] , Miller et al. [47] , Wang et al. [64] . In addition to these projects, there are several other efforts that consider some specific features of schema matching. For example, Bernstein et al. [11] , Embley et al. [21] , Rahm et al. [54] ) focused on matching large schemas or extensibility of the developed schema matching system. Furthermore, the main goal of Doan et al. [19] , Gal [24, 25] , Nottelmann and Straccia [50] is to manage uncertainty in schema matching. Each of these efforts considers a different aspect of uncertainty. For instance, Nottelmann and Straccia [50] proposes a probabilistic framework, which combines the machine learning, information retrieval, and heuristic techniques for learning a set of mapping rules. Uncertainty is an important subject especially considering large amounts of semantics involved in schemas. However, there are still open issues related to this subject, such as the need for adequate user interfaces, as addressed in Magnani and Montesi [42] . Furthermore, since their main focus is on uncertainty, other requirements of schema matching are not considered.. It is not reasonable to think of a fully automatic system for schema matching due to the huge amount of semantics involved in designing schemas. Nevertheless, most of the previous schema matching systems have provided limited solutions. For example, only a narrow set of matching algorithms are used by these systems. Although user interaction needs to be considered as a fundamental subject, either a very primitive or no Graphical User Interface (GUI) is provided. Furthermore, the past research has typically taken into account the schema matching as a separate problem area and has not combined it with the needed schema integration.. In this respect, the Semi Automatic Schema Matching and INTegration (SASMINT) approach and system [60] [61] [62] described in this paper is designed and implemented to enable semi-automated matching of relational schemas by using a combination of metrics and algorithms from Natural Language Processing (NLP) and Graph Theory. Furthermore, after the schema matching is executed, SASMINT allows its user to modify and approve the results. Once results are validated or corrected, the system then automatically performs the schema integration, by utilizing the results of schema matching and applying a number of schema derivation rules. The result of schema integration also requires user validation. Since it is not possible to determine all kinds of schema conflicts automatically, SASMINT provides a sophisticated GUI for modifying both the match and the integration results. All user interaction with the system is handled by means of this GUI. Finally, results of schema matching and integration are captured and formulated for persistent storage as the SASMINT Derivation Markup Language (SDML) representation. Compared to previous work, addressed above, there are several main contributions of SASMINT, which can be summarized as follows:. • Extending existing schema matching approaches and elevating the accuracy of schema matching: SASMINT extends the existing approaches for schema matching such that it requires minimal user input and advances the level of results accuracy, by utilizing a large set of metrics and algorithms from NLP and Graph theory and combining them with a weighted sum.. • Enabling semi-automatic identification of suited weights for algorithms: It is important to assign an appropriate weight to each NLP metric and algorithm used in schema matching, bearing in mind that each metric is suitable for different types of strings. SASMINT provides the SAMPLER component to semi-automatically identify the appropriate weight for each NLP metric or algorithm used in the system. • Enabling semi-automatic schema integration: SASMINT interrelates schema matching results directly with the schema integration. Heuristic rules are defined that run on the results of the schema matching and generate the derivation formalism for an integrated schema automatically. We assess this as a novel contribution, providing a strong competitive edge for the research on the SASMINT system. • Definition and incorporation of an XML-based language for enabling unambiguous interpretation of schema match/integration results: Within the SASMINT system, we did devise an XML-based derivation language, which we call as SDML, for capturing and persisting schema match and integration results. The value of this language is addressed in Sect. 4.1.. • Enabling user-friendly interaction by means of a GUI editor: It is not possible to automatically extract all types of semantic and resolve all kinds of structural conflicts. Therefore, a suitable user-friendly GUI editor is provided for supporting both modifications of the results of schema matching and schema integration processes as well as their storage for further use.. The rest of this paper is organized as follows: Section 2 addresses different types of schema conflicts. Section 3 introduces the SASMINT system and addresses its main functionalities. Section 4 describes the schema integration step of SASMINT. Section 5 gives some information about the experimental evaluation of the SASMINT system and provides the results of its comparison with the COMA++ system. Finally, Sect. 6 summarizes the main conclusions of the paper and presents possible future improvements. In this paper, we focus on an important challenge: semi-automatic schema matching and schema integration, for enabling data sharing among collaborating organizations. We address different types of linguistic and structural conflicts that need to be resolved when dealing with this challenge. Then, we introduce the SASMINT System to support schema matching and schema integration as automatically as possible. Unlike other approaches to database interoperability, which use a limited number of metrics and algorithms, SASMINT uses different types of metrics and algorithms for schema matching and thus generates more accurate results. It also provides the Sampler component for semi-automatically identifying the appropriate weight for each Linguistic Matching metric. The result of matching process is ultimately displayed to the user who can validate, modify, and store the final mappings. After that, SASMINT generates an integrated schema based on the validated match results and using a number of derivation rules. As another contribution, an XML-based derivation language, called SDML, is defined to capture and persist the match and integration results. In future work, we plan to support domain ontologies in addition to the use of WordNet. Therefore, if there is ontology available for that domain, SASMINT will use this ontology in order to identify semantic similarities, which will enable it to resolve more types of semantic conflicts. This ontology may also be automatically extended with newly identified semantic relationships. In this case, another important issue to consider is how to build ontologies [51] . As another future work, Sampler will be further extended to utilize the machine learning techniques. The "select all above threshold" strategy could be further extended to consider uncertainty and provide support for probabilistic schema matching, based on the active work in this field. Another future work could be creating a benchmark for schema matching and integration. Currently, there is no benchmark available, which necessitates each work to generate its own set of test schemas and do its own test for evaluation purposes. Therefore, creation of such a benchmark would be valuable. We carried out experimental evaluation of schema matching using six pairs of relational test schemas; from purchase order (PO), hotel (HOTEL), biology (SDB), and university domains (UNIV-1, UNIV-2, UNIV-3). Hotel and SDB schemas are the modified versions of the ones used for the evaluation tests of MAPONTO [3] and UNIV-3 is the one used in the tests of the Similarity Flooding project. For the purpose of evaluating schema integration, three pairs of schemas from the university domain (UNIV-1, UNIV-2, UNIV-3) were integrated. We compared the schema matching component of SASMINT against one of the state of the art schema matching systems, called COMA++ [5] . We used the COMA++ 2005 binary version that was the most recent version available at the time of our evaluation tests. We selected COMA++, because it was the most complete schema matching tool available at the time, providing a library of variety of matching algorithms and a sophisticated GUI. SASMINT and COMA++ are comparable as they both support matching of relational schemas and provide similar functionalities.. Before starting the evaluation tasks, we inserted a number of abbreviations and their expanded forms into the abbreviation lists of both systems. One important difference between SASMINT and COMA++ is that SASMINT uses WordNet for semantic matching, whereas COMA++ requires the user to add all synonyms in schema domains manually. Since WordNet might not contain all semantic relationships among the concepts of schemas either, we did not make any addition to the COMA++'s synonyms list, in order to make a fair comparison.. Combination of different metrics or algorithms was done in two systems as follows:. • SASMINT: We selected the default strategy for combining the metrics or algorithms, which is the weighted sum of them with equal weights used for each metric or algorithm (i.e. averaging). Although assigning appropriate weights for each match task would give better results, we decided to use the default strategy in order to make a fair comparison with COMA++.. • COMA++: We used the default matching strategy of COMA++, which is called as COMA. The COMA matcher combines the name, path, leaves, parents, and siblings matchers, by averaging them. In their tests, this combination was the winner and that is why we selected it.. As for the selection of match results, we used two different approaches that we call as "select all above threshold" and "select max above threshold", as detailed below:. (1) Select All above Threshold: Selecting all match pairs that have the similarity above a certain threshold value. We set the threshold as 0.5 in the experiments. (2) Select Max above Threshold: Selecting the pairs with the maximum similarity. In SASMINT, whenever there is more than one concept matching a concept of a schema, the one with the higher similarity is selected as the matching candidate. If the difference between the similarity values is smaller than 0.01, then all such matches are selected. For clarity, if an element X has been found as similar to Y and Z with similarity values of 0.6 and 0.7 respectively, then only (X, Z ) pair is shown in the results as similar. For the column-column matches, if there is a third element W that has been also found as similar to X with the value of 0.7, but if the parent table of W is not similar to that of X , while the parent table of Z is similar to that of X , then (X, Z ) pair is selected as the similar pair. However, if there is no parent table similarity, both (X, Z ) and (X, W ) are selected as similar pairs. COMA++'s default selection strategy for the COMA matcher works as follows: When there is more than one match to the same concept, the one with the higher similarity is selected if the difference between the similarity values is more than 0.0080, if not, all of the highest similarity matches are selected.. Although we compared SASMINT with COMA++ for the purpose of schema matching, we could not carry out functionality comparison for schema integration. COMA++ provides a simple schema merging functionality, but it is limited and not comparable to SASMINT's schema integration. To the best of our knowledge, there is no other system supporting both schema matching and schema integration. Therefore, we evaluated the integration component of SASMINT alone. For this purpose, we used six schemas from the university domain (UNIV-1, UNIV-2, UNIV-3).

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