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AbstractQuality of service (QoS) is attracting more and more attention in many areas, including entertainment, emergency services, transaction services, and so on. Therefore, the study of QoS‐aware systems is becoming an important research topic in the area of distributed systems. In terms of load balancing, most of the existing QoS‐related load balancing algorithms focus on Routing Mechanism and Traffic Engineering. However, research on QoS‐aware task scheduling and service migration is very limited. In this paper, we propose a task scheduling algorithm using dynamic QoS properties, and we develop a Genetic Algorithm‐based Services Migration scheme aiming to optimize the performance of our proposed QoS‐aware distributed service‐based system. In order to verify the efficiency of our scheme, we implement a prototype of our algorithm using a P2P‐based JXTA technique, and do an emulation test and a simulation test in order to analyze our proposed solution. We compare our service‐migration‐based algorithm with non‐migration and non‐load‐balancing approaches, and find that our solution is much better than the other two in terms of QoS success rate. Furthermore, in order to provide more solid proofs of our research, we use DEVS to validate our system design. Copyright © 2010 John Wiley & Sons, Ltd.
distributed decision, stochastic bounds, Informatique générale, TinyOS, [INFO] Computer Science [cs], performance evaluation, 004, [INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF], monitoring, [INFO.INFO-PF] Computer Science [cs]/Performance [cs.PF], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO]Computer Science [cs], wireless sensor networks, Web services
distributed decision, stochastic bounds, Informatique générale, TinyOS, [INFO] Computer Science [cs], performance evaluation, 004, [INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF], monitoring, [INFO.INFO-PF] Computer Science [cs]/Performance [cs.PF], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO]Computer Science [cs], wireless sensor networks, Web services
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 26 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |