A Proposed Approach for Efficient Energy Utilization in Cloud Data Center

Abstract

Cloud computing has transmuted the IT industry on the whole and made easy to access the resources from anywhere and at anytime. These resources can be accessed as a service rather than as a product. Clients pay for the service used as per their requirement. The huge demand of cloud computing has given rise to the creation of hefty amount of data centers. These data centers consist of different types of resources and each resource is bound to its own power consumption scenario. Besides a number of benefits; Cloud data centers also pose the problem of large amount of power consumption. Lots of techniques and methods have been developed to solve this issue out of which load balancing is one such technique. This paper discusses load balancing using a nature inspired algorithm known as Particle Swarm Optimization (PSO) algorithm. A different nature inspired algorithm known as Firefly Algorithm (FA) is proposed to solve the above said issue.

Problem Based Learning on Cloud Economics Analysis Using Open Source Simulation

“…These are in line with previous research [12,13] claimed that DVFS scheme would not give significant impact on network of less than 100 servers and switches since the scheme mainly manages voltage and frequency being used by servers and switches up and down and let them use the power although in idle state. In other study, it was reported that DVFS works fine to considerably reduce cloud energy consumption up to 1000 servers [14].…”

A Review on Secure and Energy Efficient Approaches for Green Computing

“…Also, the servers should be kept switch off whenever they are not having any load and are idle [12]. Scaling (either up or down) of the servers dynamically aims for improvising the resource utilization and implementing the technique of load balance [19]. By applying all these ways, energy savings can be increased without affecting the efficient working of the servers.…”

“…1), the rate of increase, with respect to survey done in year 2003, 2007 and 2014, in the energy consumption [19] by the various sectors of the data centers is indicated.…”

“…So, this solution technique is discussed which can decrease the consumption of energy by making more effective and efficient use of the hardware and optimize the performance of the system. An efficient resource scheduling and management scheme is the base to performance optimization, an on-demand resource allocation, load balancing and energy saving [19]. The various techniques used for the resource utilization prediction on the basis of which a new cloud resource provisioning scheme are also highlighted to accomplish the target of energy-efficiency [6].…”

Impact of Energy-Efficient and Eco-Friendly Green Computing

“… Carbon Aware Green Cloud Architecture [17]  Cloud Broker Architecture [25]  LPT and FPRRT [6]  Live Migration [13], including Server Consolidation [26] and Load Balancing [27].…”