An activity-based replica placement method of energy-conservation

Abstract

Aiming at the problems of increasing energy consumption of cloud storage, big environmental resources pressure, exist research on replica placement lacking of focus on energy consumption, this paper proposes a energy conservation replica placement method ECRP(Energy Conservation Replica Placement, ECRP). Based on the three main different levels of energy consumption of hardware components, the data node is divided into hot zone, warm zone and cold zone three logical zone, each zone uses different power management strategies and replica placement strategies, and after building a file activity prediction model which based on the simulated annealing BP neural network, files are stored in the data nodes on different zone according to the type of file activity, and then calculate the file activity periodically, when file activity exceeds a certain threshold, the file begins flow among the hot zone, warm zone and cold zone step by step in the two-way. Experiment results show that this method better solve the problems of replica placement and energy consumption optimization, have good energy saving effect.

A Low Energy Consumption Storage Method for Cloud Video Surveillance Data Based on SLA Classification

“…It shuts down or suspends redundant nodes by reasonable deployment according to improved schedules or policies. Usually, nodes are turned off in certain time under the premise of having a certain degree of fault tolerance or performance lost [19,20]. A research group at Stanford University has successfully shut down more idle nodes in Hadoop by improving the strategy of replica placement [19].…”

“…But its data availability is to be verified for the CVS system. An energy conservation replica placement method is proposed in [20]. DataNodes are separated into three logical zones according to the forecast results: hot, warm, and cold.…”