A FRAMEWORK FOR DEPLOYMENT OF MOBILE AGENTS AS WINDOWS OPERATING SYSTEM SERVICE FOR INFORMATION RETRIEVAL IN DISTRIBUTED ENVIRONMENTS

ABSTRACT

Mobile Agent Technology (MAT), remote method invocation and remote procedure calling are the three most widely used techniques for information storage and retrieval in network environments. Previous studies have shown that MAT provides a more efficient and dynamic approach to information storage and retrieval than others. However, for mobile agents to effectively perform their various tasks, a static agent platform must be installed on the computers. These platforms consume more memory, increase access time and prevent other tasks from running on the computer. Therefore, an alternative framework that will eliminate the problems associated with agent platform is imperative. Consequently, this work was aimed at developing a more efficient framework for mobile agent system deployment as an operating system service. Two classes of existing information retrieval agents were adapted to develop Embedded Mobile Agent (EMA) system. The EMA was embedded into the Windows Operating System (OS) kernel, so that it could run as a service for information retrieval. This was done to eliminate the overheads associated with the middleware provided by agent platforms. The targeted OS were Windows XP, Windows Vista and Windows7. Mathematical models were simulated to assess the performance of EMA by measuring service delay, memory utilisation, fault tolerance, turn around time at fixed bandwidth with varying number of network nodes, and percentage denial of service. Denied services were generated by a random number generator modelled after the Bernoulli Random Variable with 0.1 probability of failure. The model‟s performance was then compared with Java Agent DEvelopment framework (JADE), a widely used open-source existing mobile agent system running on platforms. The implementation was done using four computer systems running the targeted Windows on an existing local area network. Analysis of data was done using descriptive statistics and independent t-test at p = 0.01. The EMA model effectively retrieved information from the network without the agent platform, thereby reducing access times and saving memory, regardless of the version of the Windows OS. The mean service delay for EMA (15067.5 ± 8489.6 ms) was lower than that of JADE (15697.0 ± 8844.5 ms). The embedded agent requires 3 KB of memory to run compared to JADE platform requiring 2.83 103 KB. The mean fault tolerance in terms of fault recovery time for EMA was approximately 50% that of JADE (327.8 ± 193.1 ms). The mean turn around time for EMA was 499.7 ± 173.0 ms and JADE was 843.3 ± 321.6 ms consequential to the time JADE spent activating platforms. The mean percentage denial of service for EMA was 14.3 ± 9.8 while JADE was 24.7 ± 18.5. Memory requirements and service delay increased with increasing number of nodes while others show no systematic change. For all the parameters tested, there were significant differences between the two schemes. The embedded mobile agent provided more efficient, dynamic and flexible solution compared to Java Agent DEvelopment framework for distributed information retrieval applications. It could be incorporated into new versions of operating systems as operating system service for universal distributed information retrieval.