Jinlin Wang

A Local Rarest-Random-Heuristic Data Scheduling for P2P VoD System

Data scheduling is the key issue in peer-to-peer streaming system, especially in peer-to-peer VoD system. This paper mainly focuses on data chunks’ priority definition of data scheduling in peer-to-peer VoD system. After carefully studying the meanings of regular rarest first scheduling and random scheduling, a Local-Rarest-Random-Heurist (LR2H) scheduling is proposed in order to fully use the resources of strong peers in the system. LR2H fully considers the meanings of rarest first priority and random priority. It brings abundant copies of data chunks in the system by using part of rarest priority and it also avoids the concentrate request in some data chunks which have same rarest priority by adding a random jitter, and then maximize total priority of every scheduling by using heuristic algorithm. Simulation proves that LR2H has achieved a scheduling effect about 30% better than normal rarest first or random scheduling.

Real-Time Performance vs. Server Bandwidth Cost in Peer-to-Peer Streaming System

In P2P streaming system, real-time performance is very important for evaluating quality of service, which directly determines the user experience. However, real-time performance is restricted by server bandwidth cost. Based on the proposed data transmitting model, this paper investigates the recursiveness of real-time performance through theoretical analysis, and computes its relationship with server bandwidth cost. The impact of system scale and service capacity of peer is also discussed. Especially, we consider both overlay diameter and the one hop delay in the investigation, hence can obtain more exact results. Our findings are of great importance for the design and deployment of P2P streaming system.