Development, Analysis and Evaluation of Performance Models for Mobile Multi-Agent Networks

Mobile agents have a number of interesting features such as creation, disposal of agents, execution of services at various network nodes, migration to other network nodes and communication with other agents. Such features are related to the performance area. Based on some examples, scenarios, or case studies,Petri netmodels (ordinaryPetri net, coloredPetri net or predicate/transitionnet),mathematical models,simulationmodelsandqueuingmodelshavebeendevelopedintheliterature.Suchresearchworks concentrate on studying the performance of mobile agent networks with much attention on deadlock problems, dynamic behavior problems and the calculation of response time problems. In order to better understandhowtodesigndistributed systemsusing themobile agentparadigmandhow tobuild amodel with thecapabilityof studyingall suchperformanceproblems inaneasyandarealisticway,weproposea newmobile agent performancemodel using the capability of the generalized stochastic Petri net (GSPN) modeling technique. We amended this model with new mobile agent behaviors to fully describe the dynamic behavior of the mobile agent network when it manipulates parallel/multiple agents, and uses some of the most important agent communications (e.g. remote, local, direct, indirect and parallel). Furthermore, the proposed model describes the creation process of new agents during the migration process, theexecutionof tasksamongthenetworknodes, thewayofhandlingtheagentanditsservice task ateachnodeandtheinteractionofagroupofagents(asacollectiveresultofthebehaviorsofeachindividual agent). To the best of our knowledge, suchaspects arenot included into onemodel because it is difficult to describeall theseaspects intoonemodel.Therefore, thedevelopedGSPNmobilemodelgivesthefacilityto study the performance of mobile agent networks with more details. In the performance analysis, we developfourstudiestoinvestigatetheeffectofdifferentparameterssuchasagentcommunicationtime,size ofmobileagent,numberofmobileagentsandnumberofhopsontheperformanceofmobileagentnetworks. Byperformanceofmobileagentnetworks,wemeantheresponsetimeoftheuser’srequest.Tothebestofour knowledge, such four performance studies are not investigated previously by the GSPNmodeling technique. Finally, we propose a reduction-modeling methodology to facilitate the modeling process of the practical mobile agent network that incorporates a large number of network nodes, a large number of users,andsubsequentlyalargenumberofparallel/multipleagents.Suchmethodologyreducestheoriginal model to a simpler one while preserving the basic features and properties of the original model.