High Availability Green Gear-shifting Mechanism in Cloud Storage System

Abstract

The energy problem is one of the serious problems in the current large-scale storage systems need to be addressed urgently. In order to reduce the energy consumption of cloud storage system, and to meet the performance needs of users, this paper purposed a cloud storage system integrated high availability green gear-shifting mechanism (HGLG): The frame designed a new data partitioning strategy, data replication management strategy and proposed energy gear-shifting mechanism based on the data partition and data replication management. Data partitioning strategy divide data into cold data, hot data, seasonal data and the new data and place it in the appropriate zone through green data classification strategy based on anticipation (AGDC). Depending on the nature of the data, the paper accordingly designed replica placement and replica number. Based on the above data partitioning, data replication management, this paper presents energy gear-shifting mechanism, which automatically gear-shifting through neural network model predicting follow-up period assignments. Experiments based on Grid Sim show that: the energy consumption of gear-shifting mechanisms cost effective, which saved about 43% average energy at the expense of about 1.6ms average response time and the maximum energy savings is about 70%.