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A scheduling and load balancing scheme for dynamic P2P‐based system
Author(s) -
Zhang Ming,
Ajaltouni Elie El,
Boukerche Azzedine
Publication year - 2010
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1578
Subject(s) - computer science , distributed computing , load balancing (electrical power) , scheduling (production processes) , dynamic priority scheduling , round robin scheduling , fair share scheduling , peer to peer , computer network , quality of service , engineering , operations management , grid , geometry , mathematics
Scheduling and load balancing have been one of the key issues in distributed systems due to their significant impact on system performance as well as system resource utilization. With the rapid development of Peer‐to‐Peer (P2P) network technology, traditional scheduling and load balancing techniques are facing new challenges because P2P‐based systems require more dynamic mechanisms for task scheduling and load balancing among heterogeneous network computing nodes. In this paper, we propose a scheme for dynamic scheduling and load balancing in a P2P‐based environment. Our scheme aims at Service‐Oriented P2P‐based distributed systems, however, it can be applied to traditional distributed architecture straightforwardly. Furthermore, we evaluate the performance of our scheme using simulation experiments in a cluster‐based distributed computing environment. Indeed, our results show that our scheme can achieve significant system performance gain compared to commonly used random and round robin scheduling algorithms in P2P‐based systems. Meanwhile, we use a real‐time distributed simulation to evaluate our algorithm, which can provide more trustful results in terms of performance evaluation. Indeed, the ease of using a distributed real‐time simulation, to measure the real‐time performance of the algorithm can promote more flexible and efficient methods for the development of load balancing algorithms. This is especially the case for the hard‐to‐predict P2P‐based distributed systems. Copyright © 2010 John Wiley & Sons, Ltd.