WPS: A Workload-Aware Placement Scheme for Erasure-Coded In-Memory Stores
Shuang Wang, Jianzhong Huang, Xiao Qin, Qiang Cao, Changsheng M. Xie · 2017
Data-intensive applications are increasingly depending on in-memory stores to meet high-I/O-performance requirements. To be resilient to server failures and in turn achieve high availability, both replication and erasure codes are introduced to in-memory stores. Since erasure codes have an advantage of memory efficiency over replication, we focus our work on erasure-coded in-memory stores and investigate placement schemes to address the issue of workload fluctuation. To mitigate the I/O imbalanced incurred by workload skew and maximize the utilization of all nodes, we proposed a Workload-aware Placement Scheme called WPS for Reed-Solomon-coded in-memory stores. WPS accomplishes balanced I/Os as follows: it divides in-memory data blocks into multiple groups based on access characteristics (e.g., popularity), and classifies all nodes into several groups according to nodes' access performance (e.g., indicated by available bandwidth), and places or migrates high-access-popularity in-memory data blocks to high-performance nodes without violating the essential principle of fault tolerance. The comparative experiments indicate that WPS can significantly improve load balancing for RS-coded in-memory stores exhibiting workload popularity skew; meanwhile, WPS achieves comparable mean, median, and tail latencies relative to two candidate placement schemes.