Model of Load Balancing Using Reliable Algorithm with Multi-agent System

Massive technology development is linear with the growth of internet users which increase network traffic activity. It also increases load of the system. The usage of reliable algorithm and mobile agent in distributed load balancing is a viable solution to handle the load issue on a large-scale system. Mobile agent works to collect resource information and can migrate according to given task. We propose reliable load balancing algorithm using least time first byte (LFB) combined with information from the mobile agent. In system overview, the methodology consisted of defining identification system, specification requirements, network topology and design system infrastructure. The simulation method for simulated system was using 1800 request for 10 s from the user to the server and taking the data for analysis. Software simulation was based on Apache Jmeter by observing response time and reliability of each server and then compared it with existing method. Results of performed simulation show that the LFB method with mobile agent can perform load balancing with efficient systems to all backend server without bottleneck, low risk of server overload, and reliable

Lightweight Agents, Intelligent Mobile Agent and RPC Schemes: A Comparative Analysis

This paper presents the performance comparison of Lightweight Agents, Single Mobile Intelligent Agents and Remote Procedure Call which are tools for implementing communication in a distributed computing environment. Routing algorithms for each scheme is modeled based on TSP. The performance comparison among the three schemes is based on bandwidth overhead with retransmission, system throughput and system latency. The mathematical model for each performance metric is presented, from which mathematical model is derived for each scheme for comparison. The simulation results show that the LWAs has better performance than the other two schemes in terms of small bandwidth retransmission overhead, high system throughput and low system latency. The Bernoulli random variable is used to model the failure rate of the simulated network which is assumed to have probability of success p = 85% and the probability of failure q = 15%. The network availability is realized by multiplicative pseudorandom number generator during the simulation. The results of simulation are presented

Autonomous mobile agent routing for efficient server resource allocation

Mobile agents are becoming increasingly important in the highly distributed applications frameworks seen today. Their routing/dispatching from node to node is a very important issue as we need to safeguard application efficiency, achieve better load balancing and resource utilization throughout the underlying network. Selecting the best target server for dispatching a mobile agent is, therefore, a multi-faceted problem that needs to be carefully tackled. In this paper we propose distributed, adaptive routing schemes (next node selection) for mobile agents. The proposed schemes overcome risks like load oscillations, i.e., agents simultaneously abandoning a congested node in search for other, less saturated node. We try to induce different routing decisions taken by agents to achieve load balancing and better utilization of network resources. We consider five different algorithms and evaluate them through simulations. Our findings are quite promising both from the user/application and the network/infrastructure perspective. © 2008 Elsevier Inc. All rights reserved