Providing Quantitative Scalability Improvement of Consistency Control for Large-Scale, Replication-Based Grid Systems

Providing Quantitative Scalability Improvement of Consistency Control for Large-Scale, Replication-Based Grid Systems

Yijun Lu (University of Nebraska-Lincoln, USA), Hong Jiang (University of Nebraska-Lincoln, USA) and Ying Lu (University of Nebraska-Lincoln, USA)
DOI: 10.4018/978-1-60566-370-8.ch005
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Abstract

Consistency control is important in replication-based-Grid systems because it provides QoS guarantee. However, conventional consistency control mechanisms incur high communication overhead and are ill suited for large-scale dynamic Grid systems. In this chapter, the authors propose CVRetrieval (Consistency View Retrieval) to provide quantitative scalability improvement of consistency control for large-scale, replication-based Grid systems. Based on the observation that not all participants are equally active or engaged in distributed online collaboration, CVRetrieval differentiates the notions of consistency maintenance and consistency retrieval. Here, consistency maintenance implies a protocol that periodically communicates with all participants to maintain a certain consistency level; and consistency retrieval means that passive participants explicitly request consistent views from the system when the need arises in stead of joining the expensive consistency maintenance protocol all the time. The rationale is that it is much more cost-effective to satisfy a passive participant’s need on-demand. The evaluation of CVRetrieval is done in two parts. First, by analyzing its scalability and the result shows that CVRetrieval can greatly reduce communication cost and hence make consistency control more scalable. Second, a prototype of CVRetrieval is deployed on the Planet-Lab test-bed and the results show that the active participants experience a short response time at expense of the passive participants that may encounter a longer response time.

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