Analysis of Mobile Agent Systems Performance Using Linear Prediction Model

نویسندگان

  • FAIZ AL-SHROUF
  • AIMAN TURANI
چکیده

Mobile Agents are considered an interesting technology to develop applications for distributed systems. Thus they present features, such as autonomy and capability to roam to hosts, process data, and save remote communications. Many mobile agent platforms have been developed for research purposes while other platforms have been deployed as commercial products. Some platforms have been outdated; others continue releasing new versions that fix bugs detected or offer new features. A common problem when one wants to benefit from mobile agent platform is the decision about which platform to use. In this paper, we provide up-to-date evaluation of existing mobile agent platforms. We derive linear prediction model to compare and forecast mobile agent platform's performance and their interested behavior. The study uses six mobile agent systems: JAMES, Odyssey, Swarm, Grasshopper, Aglets, and Voyager.

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تاریخ انتشار 2012