ENHANCED LOAD BALANCING STRATEGY IN HETEROGENEOUS PEER-TO-PEER NETWORKS

Abstract

Existing P2P systems provide a Duty Cycle Data Appropriation (DCDA) Technique allocate objects based on ranking among “peer nodes” in a method that result in various nodes containing times as numerous objects as the standard node. Further disparity might effect owing to non-uniform allocation of objects in the identifier break and a high amount of heterogeneity in objective loads and node capabilities. With that, a node’s load might differ seriously over time as the system can be projected to practice incessant operations of objects. Introduced an algorithm for load balancing in such heterogeneous, active P2P systems. Foremost contributions are: (1) suggest a fully dispersed method to preserve the record of file access information. This information is employed to forecast the prospect file access frequencies and sustain the load allocation and redeployment operations; (2) Plan a novel load balancing algorithm, which obtains the file access record and peer heterogeneity properties to establish the load allocation. Enhanced Load Balancing Strategy in Heterogenous P2P Network (ELBSHN) algorithm engender the best load allocation resolution when a novel peer enters, it also be capable to vigorously achieve the load redeployment through system running time if congested peers emerged. In ELBSHN algorithm, no virtual servers are employed; consequently encompass less processing overhead on the exclusive routing metadata preservation. An experimental evaluation is conducted using the Heterogeneous peer networks data extracted from the large internet service providers to estimate the performance of the proposed enhanced load balancing strategy. Simulation results illustrate that in the features of quick onsets and exits of objects of extensively changeable load, algorithm attains load balancing for system utilizations as high as 90% while affecting only regarding 8% of the load that appears into the system.