On Energy Efficiency Data Access and Backup for Cloud Computing Networks

One feature of cloud computing is to let users share data with each other at anytime from anywhere. How to reduce energy consumption has become an important research issue. This study considers the location-aware cloud storage (CS) selection to implement a remote data backup as a strategic to tackle energy efficiency. To satisfy the green computing, a tradeoff between user access (which locates in several locations) and backup (which stores the data at least in two data centers) were balanced to minimize the energy consumption. The objective of minimum energy consumption subjects to the required link and nodal capacity, service level, access proportion, delay, and CSs selection. This work has developed network, access distribution, delay, and energy consumption models as well as proposed a remote backup mechanism. The related methods, which are weighted access percentage CS (WAP), approximation method (AM), and group-based heuristic (GBH), are evaluated to show how the control variable affect the green cloud computing networks.