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IDEA: An infrastructure for detection-based adaptive consistency control in replicated services

By Yijun Lu, Ying Lu and Hong Jiang


In Internet-scale distributed and replicated services, poor consistency results in poor QoS or even monetary loss. Recent research focuses on enforcing a certain consistency level, instead of perfect consistency, to strike a balance between consistency guarantee and system’s scalability. In this paper, we argue that it is equally, if not more, important to achieve adaptability. I.e., the system adjusts its consistency level on the fly to suit applications’ ongoing need. This paper presents IDEA (an Infrastructure for DEtection-based Adaptive consistency control), a protocol that adaptively controls consistency in replicated services by detecting inconsistency among nodes in a timely manner via an inconsistency detection framework and resolving the detected inconsistencies efficiently when necessary. Through experimentation on Planet-Lab, IDEA is evaluated from two aspects: its adaptive interface and its performance of inconsistency resolution. Results show that IDEA achieves adaptability by adjusting the consistency level according to users’ preference on-demand, and it achieves low inconsistency resolution delay and incurs minimal communication cost

Topics: Performance, Design, Experimentation, Human Factors Keywords Inconsistency Detection, Consistency Control, Adaptability, Replicated Services
Year: 2007
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