Secret sharing is a method for distributing a secret among a party of participants. Each of them is allocated a share of the secret, and the secret can only be reconstructed when the shares are combined together. We have been proposing a secret sharing distributed database system (SSDDB) that uses a secret sharing scheme to improve confidentiality and robustness of distributed database systems. This paper proposes a vertical partitioning algorithm for the SSDDB, and evaluates the algorithm by computational experiments.

Coalition formation in multi-agent systems (MAS) is becoming increasingly important as it increases the ability of agents to execute tasks and maximize their payoffs. Dependence relations are regarded as the foundation of coalition formation. This paper proposes a novel dependence theory namely transitive dependence theory for dynamic coalition formation in multi-agent systems. Transitive dependence is an extension of direct dependence that supports an agent's reasoning about other social members during coalition formation. Based on the proposed transitive dependence theory, a dynamic coalition formation framework has been worked out which includes information gathering, transitive dependence based reasoning for coalition partners search and coalition resolution. The nested coalitions and how to deal with incomplete knowledge while forming coalitions are also discussed in the paper.

Petri nets are a well-known graphical and modeling tool for concurrent and distributed systems, and there have been many results on the theory, and also on practical applications. In the last decade, various Object-Oriented Petri nets (OO-nets) are proposed. As object orientation was adopted for programming languages, extension to OO-nets inspired from object-oriented programming is a natural flow. This article presents state-of-the-art on OO-nets.

The traffic congestion problem in urban areas is worsening since traditional traffic signal control systems cannot provide] efficient traffic regulation. Therefore, dynamic traffic signal control in Intelligent Transportation System (ITS) recently has received increasing attention. This study devised a multi-agent architecture, the Adaptive and Cooperative Traffic light Agent Model (ACTAM), for a decentralized traffic signal control system. The proposed architecture comprises a data storage and communication layer, a traffic regulation factor processing layer, and a decision-making layer. This study focused on utilizing the cooperation of multi-agents and the prediction mechanism of our architecture, the Forecast Module, to forecast future traffic volume in each individual intersection. The Forecast Module is designed to forecast traffic volume in an intersection via multi-agent cooperation by exchanging traffic volume information for adjacent intersections, since vehicles passing through nearby intersections were believed to significantly influence the traffic volume of specific intersections. The proposed architecture can achieve dynamic traffic signal control. Thus, total delay time of the traffic network under ACTAM can be reduced by 37% compared to the conventional fixed sequence traffic signal control strategy. Consequently, traffic congestion in urban areas can be alleviated by adopting ACTAM.

Mobile agent systems are essential in the next generation of electronic commercial applications. However, existing solutions for mobile agents to sign documents without user intervention are problematic because there is no restriction on who can generate the signatures. In this paper, we present a modified version of undetachable signature scheme with which the power to generate digital signatures can be designated to a neutral party. We also give a transaction model to support the scheme. Discussions regarding the security of the signature scheme as well as some attacks on its application in our model are presented too.

The new Internet has to provide the Quality of Services to converged multimedia services, in which each one may choose its own requirements. Managing such a dynamic network is not an easy task. A more intelligent and adaptive behavior is required from network management. We argue that agents are able to realize this task by dynamically adapting management mechanisms to the current network conditions. This article presents a Behavioral Multi-Agent-based model for QoS-enabled Internet. Based on this behavioral approach, we analyze network management mechanisms (or "elementary behaviors") in terms of performance and applicability profile. We use simulation to observe services performances when submitted to diverse QoS management elementary behaviors.

Migration transparency is considered in the context of multi-agent systems. A mobile agent architecture is proposed with an Availability service and a Transparency interface. We define mobility as explicit (or proactive) when the agent decides when and where to move and define mobility as implicit (i. e. , transparent or reactive) when it is a consequence of changes in the environment. Implicit mobility of agents is explored in addition to the usual explicit mobility. The search for a target agent (or agency) follows a transparent location and selection. The client agent preferably moves towards the target agent. If not possible, the target agent will move towards the client agent when calling back. If both agents can not move then the execution takes place remotely or is abandoned. Transparency is goal oriented.

The need for responsive, flexible agents is pervasive in many application domains due to their complex, dynamic, and uncertain nature. Dynamic Adaptive Autonomy allows Sensible Agents to reorganize themselves during system operation to solve different problems in the face of these complex and dynamic environments. This paper presents both functional and implementation architectures for Sensible Agent systems. The functional architecture supports concepts from the distributed computing community by separating internal agent functionality into a discrete set of modules whose interactions are formally specified using the Interface Definition Language (IDL) from the Common Object Request Broker Architecture (CORBA). These four modules are: (1) Perspective Modeler--which contains the agent's explicit model of its local, subjective view of the world, (2) Autonomy Reasoner--determines the appropriate decision-making framework for each of the agent's goals, (3) Action Planner--interprets domain-specific goals, plans to achieve these goals and executes the generated plans, and (4) Conflict Resolution Advisor--identifies, classifies, and recommends possible solution strategies for resolving conflicts between this agent and other agents. The implementation architecture has been realized in a testbed that promotes (1) language and platform independence, (2) parallel development, (3) rapid integration of evolving representations and algorithms implementing agent functionality, (4) repeatable experimentation and testing, (5) environment and agent visualization, and (6) inter-domain application portability. The testbed uses the Inter-Language Unification (ILU) ORB from Xerox to provide the CORBA layer of inter-module and inter-agent communication. A three-dimensional visualization of the domain is provided with a CORBA-connected Virtual Reality Modeling Language (VRML) model while low-level data collection is accomplished using a CORBA-connected Java application. The combination of a distributed functional architecture with a distributed implementation architecture provides a high level of flexibility, visualization ability and experimental fidelity for evaluating the performance of Sensible Agents in complex, dynamic and uncertain environments.