Paper Presentation & Seminar Topics: The Server Reassignment Problem for Load Balancing in Structured P2P Systems

The Server Reassignment Problem for Load Balancing in Structured P2P Systems


Application-layer peer-to-peer (P2P) networks are considered to be the most important development for next-generation Internet infrastructure. For these systems to be effective, load balancing among the peers is critical. Most structured P2P systems rely on ID-space partitioning schemes to solve the load imbalance problem and have been known to result in an imbalance factor of ├░logN├× in the zone sizes. This paper makes two contributions. First, we propose addressing the virtual-server-based load balancing problem systematically using an optimization-based approach and derive an effective algorithm to rearrange loads among the peers. We demonstrate the superior performance of our proposal in general and its advantages over previous strategies in particular. We also explore other important issues vital to the performance in the virtual server framework, such as the effect of the number of directories employed in the system and the performance ramification of user registration strategies. Second, and perhaps more significantly, we systematically characterize the effect of heterogeneity on load balancing algorithm performance and the conditions in which heterogeneity may be easy or hard to deal with based on an extensive study of a wide spectrum of load and capacity scenarios.

Existing System:-

• Some peers may be large servers with plenty of computing power and large storage access through a reliable and high-speed network, whereas other peers may be handheld devices with wireless connections that have limited storage, computing power, and unreliable connections. Although there are approaches that are effective in partitioning the ID space according to node capacities these approaches cannot adapt to dynamic workload changes in real networking conditions.

Proposed System:-

• Here we performed in-depth analysis of the effect of capacity and workload heterogeneity on algorithm performance in both static and dynamic environments and the qualitative relationship between static and dynamic environments.

Hardware Specification:

• Processor : Pentium Iv 2.6 Ghz
• Ram : 512 Mb Dd Ram
• Monitor : 15” Color
• Hard Disk : 20 Gb

Software Specification:

• Front End : Java, Swing
• Tools Used : JBuilder
• Operating System : WindowsXP