首页|Game-Based Scheduling Algorithm to Achieve Optimize Profit in MapReduce Environment
Game-Based Scheduling Algorithm to Achieve Optimize Profit in MapReduce Environment
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
MapReduce is a programming model and an associated implementation for processing and generating large data sets。 Providing MapReduce as a service is the development future trend。 By leveraging the game theory， this paper proposes a scheduling algorithm to deal with the competition for resources between multiple jobs in MapReduce。 Firstly， we present a model that could estimate job executing time， and then a utility function of job and an optimization objective are brought forward; thirdly， we present a game model to solve the optimization problem。 The proof and the solution are also present。 Finally， we implement the algorithm and experiment it in a hadoop cluster。 The result shows the present algorithm could schedule jobs rational。
schedulingMapReducegame modelQoS
Cong Wan、Cuirong Wang、Ying Yuan、Haiming Wang
展开 >
College of Information Science and Engineering, Northeastern University, Shenyang 110044, China
NETL
