Information Flow Queue Optimization in EC Cloud
Yangyang Tao, Shucheng Yu, Junxiu Zhou · 2018 International Conference on Computing, Networking and Communications (ICNC) · 2018
With the proliferation of big data applications, Erasure Codes (EC) have been increasingly adopted by distributed storage systems because of the space efficiency and high reliability. However, tail latency remains as a major limitation with EC which is responsible for long response times of many emerging Web applications. To combat tail latency of EC, one approach is to introduce real-time data displacement, which would cause additional latency due to data displacement itself. Queue models are frequently adopted for data scheduling. However, current queue model approaches usually overlook the real-time properties of requests and hence only provide suboptimal solutions. In this paper we consider the natures of real-time requests and the bipartite property of the network graph. We formulate the problem as a k-marriage flow queue model and optimize the scheduling strategy according to user preference (Service Level Agreement (SLA)) with multi-object optimization (MOO). Comprehensive simulation results show admissible improvement of the proposed method on tail latency as compared to the state of the art including the data displacement approach.