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We propose a novel approach for shortest path routing in wireless mobile networks. The approach makes use of n mobile agents initially launched from n mobile nodes forming the network. The agents move randomly from node to node and update routing information as they go. The approach is presented in this paper with two protocols. Both of them exhibit good performance in terms of the network and computing resource consumptions. The first protocol relies on independent mobile agents and imposes a minimum bandwidth requirement on individual mobile agents. Each agent carries the link state of its creator and this information remains unchanged except when the mobile agent returns to the home node. The second protocol is a refinement of the first protocol, with some form of interaction between the mobile agents. Each agent maintains the routing table of its creator instead of link state. The randomly walking agents spread the update information and compute the shortest paths via exchanging network state information between the routing tables they carry and the routing tables at the nodes they traverse. The correctness of the protocols is proven. Our analysis shows that the agent cooperation improves the system performance when dealing with topology and link cost changes.

We consider the problem of decontaminating a network infected by a mobile virus. The goal is to perform the task using as small a team of antiviral agents as possible, avoiding recontamination of disinfected areas. In all the existing literature, it is assumed that the immunity level of a decontaminated site is nil; that is, a decontaminated node, in absence of an antiviral agent on site, may be re-contaminated by any infected neighbour. The network decontamination problem is studied here under a new model of immunity to recontamination: we consider the case when a decontaminated vertex, after the cleaning agent has gone, will become recontaminated only if a majority of its neighbours are infected. We study the impact that the presence of local immunity has on the number of antiviral agents necessary to decontaminate the entire network. We establish both lower and upper bounds on the number cleaners in the case of (multidimensional) toroidal meshes, graphs of vertex degree at most three (e.g., cubic graphs, binary trees, etc.), and of tree networks. In all cases the established bounds are tight. All upper-bound proofs are constructive; i.e., we exhibit decontamination protocol achieving the claimed bound. We also analyze the total number of moves performed by the agents, and establish tight bounds in some cases.

The evolution of cultural diversity in some social systems can be observed as the oppositional patterns in different levels, namely, the directions of the trends of diversity in different levels are opposite. In this paper, we propose a payoff-driven metapopulation modeling framework to investigate the origin of the oppositional patterns in the trends of cultural diversity. This model considers the mobile agents in multiple communities, and the cultural characteristics of an agent are represented by a vector. The diffusion of cultural characteristics is driven by two opposite effects: the communication cost positively depending on cultural difference between agents, and the cultural attractiveness single-peak-functional correlating on cultural difference. In the numerical simulations of the model, the polarization is observed in the case with the homophily principle, and two types of the oppositional patterns can emerge in the case with time-varying mobility of agents. These findings efficiently explain the emergence of the oppositional patterns and help to understand the evolution of diversity under the dynamics of both synchronization and variation.

Net-Console is an integrated program development environment that can be used as a front-end for High Performance Computing (HPC) sites. It consist of an MPI-aware editor, an execution console, a debugger, monitoring tools and an account and file manager. Using Net-console the user is able to edit, execute, debug and evaluate the performance of parallel programs from anywhere in the Internet. The user interface is done through a normal Java-enabled browser. Net-console can also support processing through wireless and lightweight devices with the use of mobile agent technologies. The tools included in Net-console and their functionality, the languages used and the overall structure of the project are presented in this paper.

We examine the problem of gathering $k\ge 2$ agents (or multi-agent rendezvous) in dynamic graphs which may change in every round. We consider a variant of the $1$-interval connectivity model [9] in which all instances (snapshots) are always connected spanning subgraphs of an underlying graph, not necessarily a clique. The agents are identical and not equipped with explicit communication capabilities, and are initially arbitrarily positioned on the graph. The problem is for the agents to gather at the same node, not fixed in advance. We first show that the problem becomes impossible to solve if the underlying graph has a cycle. In light of this, we study a relaxed version of this problem, called weak gathering, where the agents are allowed to gather either at the same node, or at two adjacent nodes. Our goal is to characterize the class of 1-interval connected graphs and initial configurations in which the problem is solvable, both with and without homebases. On the negative side we show that when the underlying graph contains a spanning bicyclic subgraph and satisfies an additional connectivity property, weak gathering is unsolvable, thus we concentrate mainly on unicyclic graphs. As we show, in most instances of initial agent configurations, the agents must meet on the cycle. This adds an additional difficulty to the problem, as they need to explore the graph and recognize the nodes that form the cycle. We provide a deterministic algorithm for the solvable cases of this problem that runs in $O(n^2+nk)$ number of rounds.

In this paper, we propose a middleware system for building adaptive migratory continuous media applications. In future computing environments, a variety of objects at home and in offices will embed computers, and various applications will be moved among these computers according to the user's locations. For example, a computer that executes an application may be changed to another computer according to the location of the application's user for monitoring his behavior. However, since the computers may have dramatically different hardware and software configurations, the application cannot be moved without taking into account the configurations of the computers that the application is migrated. Therefore, migratory applications should be aware of environments where they are executed.

The paper focuses on middleware for building adaptive migratory continuous media applications that are one of the most important classes of migratory applications. Our middleware consists of three components. The first component is an environment server that monitors computing environments that applications run, and it notifies the changes of the environments to the applications. The second component is a continuous media toolkit that enables us to build adaptive migratory continuous media applications easily. The toolkit enables us to build continuous media applications in a highly configurable way. This makes applications to be adapted to every computing environment by changing their configurations. The third component is a migration manager that makes applications migratory. We also show an example of a migratory application, and describe some experiences with building the application.

With increasing requirements of distributed software systems, software agents are becoming a mainstream technology for software engineering and data management. Scalability and adaptability are two key challenges that must be addressed. In this work a new model is introduced for building large-scale distributed software systems with high dynamics, using a hierarchy of homogeneous agents that has the capability of service discovery. The performance of the agent system can be improved using different combinations of optimisation strategies. A modelling and simulation environment has been developed to aid the performance evaluation process. Two case studies are given and simulation results are included that show the impact of the agent mobility and the choice of performance optimisation strategies on the overall system performance.

A mobile agent system is a special distributed system with moving programs in networks. Mobile agent systems provide a powerful and flexible paradigm for building high performance distributed systems. Due to dynamic configuration property, assuring quality of a mobile agent system is a challenge work. Formal specification and analysis of a mobile agent system provides one of the best approaches to ensure the correctness of a system design. However, it is difficult to find a formal specification tool for modeling a mobile agent system with an easy to understand and concise model. In addition, it is a challenge but also important work to provide an automatic formal analysis approach for verifying whether a system specification correctly meets certain requirements in a mobile agent system. In this paper, a framework for specification and analysis of mobile agent systems is defined. First, Predicate/Transition nets are extended with dynamic channels for modeling mobile agent systems. The formalism has the expressive power to naturally model the software architecture of a mobile agent system, and easily capture the properties especially the mobility, mobile communication and dynamic configuration of a mobile agent system. Then, model checking is instrumented to the framework for automatically verifying the correctness of the specification of a mobile agent system. In order to illustrate the capability of the formalism and the verification strategy, a medical image processing system using mobile agents is modeled using the extended Predicate/Transition nets and system properties are verified using the SPIN model checker.

Given the undeniable popularity of the Web, providing efficient and secure access to remote databases using a Web browser is crucial for the emerging cooperative information systems and applications. In this paper, we evaluate all currently available Java-based approaches that support persistent connections between Web clients and database servers. These approaches include Java applets, Java Sockets, Servlets, Remote Method Invocation, CORBA, and mobile agents technology. Our comparison is along the dimensions of performance and programmability. Our findings point out that best performance is not always achievable with high programmability and low resource requirements. Moreover, the mobile agent technology needs to improve its programmability while giving particular emphasis on its infrastructure.

Standard client-server workflow management systems are usually designed as client-server systems. The central server is responsible for the coordination of the workflow execution and, in some cases, may manage the activities database. This centralized control architecture may represent a single point of failure, which compromises the availability of the system. We propose a fully distributed and configurable architecture for workflow management systems. It is based on the idea that the activities of a case (an instance of the process) migrate from host to host, executing the workflow tasks, following a process plan. This core architecture is improved with the addition of other distributed components so that other requirements for Workflow Management Systems, besides scalability, are also addressed. The components of the architecture were tested in different distributed and centralized configurations. The ability to configure the location of components and the use of dynamic allocation of tasks were effective for the implementation of load balancing policies.

Two significant performance factors in Mobile Agent Planning (MAP) for distributed information retrieval are the number of mobile agents and the total execution time. Using fewer mobile agents results in less network traffic and consumes less bandwidth. Regardless of the number of agents used, the total execution time for a task must be kept to a minimum. A retrieval service must minimize both these factors for better system performance, and at the same time, it must be able to supply the required information to users as quickly as possible. In this paper, we propose heuristic algorithms, called Cost-Effective MAP (CEMAP), to minimize both the number of mobile agents and the total execution time under the condition that the turnaround time is kept to a minimum. Although these algorithms tend to slightly increase the planning cost, a simulation study shows that these algorithms enhance the system performance significantly. By adopting these algorithms, systems can maintain lower network traffic while satisfying the minimum turnaround time.

The use of mobile agent technology has been proposed for various fault-sensitive application areas, including electronic commerce and system management. A prerequisite for the use of mobile agents in these environments is that agents have to be executed reliably, independent of communication and node failures.

In this article, we present two approaches improving the level of fault-tolerance in agent execution. The introduction of an itinerary concept allows to specify an agent's travel plan flexibly and provides the agent system with the possibility to postpone the visit of currently unavailable nodes or to choose alternative nodes in case of node failures.

The second approach is a recently proposed fault-tolerant protocol to ensure the exactly-once execution of an agent. With this protocol, agents are preformed in stages. Each stage consists of a number of nodes. One of these nodes executes the agent while the others monitor the execution. After a summary of this protocol, we focus on the construction of stages. In particular, we investigate how the number of nodes per stage influences the probability of an agent to be blocked due to failures and which nodes should be selected when forming a stage to minimize the protocol overhead.

Reliability estimation of mobile agent-based systems remains a difficult task due to the characteristics of mobile agents that include distributed and asynchronous execution, autonomy, and mobility. In this paper we present an analytical approach to estimate the reliability of mobile agent-based systems. We define the reliability of a mobile agent in terms of the processor execution time required to perform agent's tasks at each processing node and the transmission or communication time needed to transfer the agent from one processing node to another via a network to complete its mission. The failure of entire components causes failure of the agent. Simulation experiments have been conducted using stochastic Petri Nets modeling. We investigate the effect of different component reliability and availability models (processors and links) on the system throughput. The results we have obtained demonstrate the impact of different reliability and availability models on the system throughput.

We introduce a method of analyzing entanglement-enhanced quantum games on regular lattices of agents. Our method is valid for setups with periodic and non-periodic boundary conditions. To demonstrate our approach we study two different types games, namely the Prisoner's dilemma game and a cooperative Parrondo's game. In both cases we obtain results showing, that entanglement is a crucial resource necessary for the agents to achieve positive capital gain.

In a network environment supporting mobile entities (called robots or agents), a black hole is a harmful site that destroys any incoming entity without leaving any visible trace. The black-hole search problit is the task of a team of k > 1 mobile entities, starting from the same safe location and executing the same algorithm, to determine within finite time the location of the black hole. In this paper, we consider the black hole search problit in asynchronous ring networks of n nodes, and focus on time complexity. It is known that any algorithm for black-hole search in a ring requires at least 2(n - 2) time in the worst case. The best known algorithm achieves this bound with a team of n - 1 agents with an average time cost of 2(n - 2), equal to the worst case. In this paper, we first show how the same number of agents using 2 extra time units in the worst case, can solve the problit in only time on the average. We then prove that the optimal average case complexity of can be achieved without increasing the worst case using 2(n - 1) agents. Finally, we design an algorithm that achieves asymptotically optimal both worst and average case time complexities itploying an optimal team of k = 2 agents, thus improving on the earlier results that required O(n) agents.

Choosing the best way for describing physical reality has always been standing in focus of research. Several methodologies have been developed based on classical mathematics, or statistics and also new disciplines — such as soft-computing techniques — appeared. Petri Nets as one of the most naturalistic modeling methodologies are well suited to describe complex process in general. However in some fields of modeling the describing power of basic Petri Nets proved not to be robust enough, therefore several extensions were made to the original concept. Colored tokens (Colored Petri Nets), stochastic delayed streaming of mobile entities (Stochastic Petri Nets), object oriented architecture (Object Oriented Petri Nets), numerical (Numerical Petri Nets) and linguistic attributes (Fuzzy Petri Nets) broaden the range of capabilities. In some fields of problem solving, usage of static and mobile knowledge bases is needed: e.g., flexible manufacturing systems, or intelligent traffic simulation. These problems to be investigated involved new conceptual developments of Petri Nets and led to the introduction of Knowledge Attributed Petri Nets. At the same time distributed control in simulation appeared, intelligent agents supported the connection of mobile knowledge bases and static inference engines in an effective way. The mentioned extensions brought general support in model synthesis, but some unsolved questions remained related to the implementation of intelligent mobile entities. This paper highlights a new level of AI controlled simulation introducing the Extended Knowledge Attributed Petri Nets that offer the capability of easy implementation of mobile inference engines and knowledge base, providing general mobile AI in Petri Nets.

Compared to today’s traditional distributed systems, the mobile computing environment is very different in many respects. Limited battery life and high communication prices are bottlenecks in mobile computing, so a new method is urgently needed to resolve such problems. This paper proposed a new framework to meet the demands of future wireless applications. In the framework we propose Asynchronous Access Pattern (AAP) and Service Configure File (SCF) supporting disconnection (include voluntarily and involuntarily) operations for mobile clients. AAP allow a mobile user voluntarily disconnect itself from the server to save its battery life and avoid high communication prices. And new wireless applications are easy to be developed/deployed based on SCF in our framework.

A new modeling method of classification engine based on unidentified short sequences of system calls is proposed. Mobile agents can carry the classification engine easily in the distributed multi-agent intrusion detection systems. The classification engine has the advantages of the concise pattern set, high accuracy, fast transportation and easy comprehension. The core spirit of the modeling method is that the local behavior characteristic hidden in the unidentified short sequences of system calls can be exactly distinguished on the statistic meaning with the help of adjacent correlative information. Experiment results indicate that the classification engine clearly improves detection accuracy against known and unknown attacks.