Web services on the cloud have to serve a huge amount of users from all over the world simultaneously and usually deploy a large amount of servers to share the incoming workloads.
Traditional centralized load-balancing approaches with single dispatcher cannot scale well under such a large-scale of servers. Therefore, distributed dispatching structure has been developed for efficient request processing through a set of dispatchers working independently.
However, traditional load-balancing algorithms, such as Join-the-Shortest-Queue (JSQ), cannot be implemented efficiently under such distributed dispatching structure. Effective and efficient distributed load balancing thus becomes a crucial research issue for large-scale cloud services. A recent research by Lu et al. proposed a Join-Idle-Queue (JIQ) algorithm for efficient distributed load balancing. However, JIQ is not effective when system load is moderate or high and no servers are idle. In this thesis, we propose a Join-Queue-Anytime (JQA) mechanism with four variations: JQA_RR, JQA_NT, JQA_Radnom and JQA_LV, aiming for resolving the inefficiency of JIQ under moderate or high system load. The proposed mechanism has been evaluated through a series of simulation experiments implemented with the CloudSim toolkit. The experimental results indicate that the proposed JQA mechanism outperforms JIQ significantly, achieving up to 31% performance improvement in terms of average request response time.
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