An Energy Efficient and QoS Achieved Through MapReduce in Cloud Environment

This paper presents an energy-efficient and quality of service achieved through MapReduce in cloud environment. Although decrease in operating costs residue to be a key desire for movement to Cloud environments, Power consumption is a big thing for data centers and cloud service providers. Many big data applications execute on Hadoop MapReduce framework for handling large workloads. Cloud computing, Virtual machine allocation policy is an important aspect while dealing with multiple component architectures. Data allocation, privacy allocation, resource optimization are challenging task in any architecture. Traditional algorithm faces either a long computation time or high cost over the computation. In this approach which is Hadoop driven matrix based architecture is used for data processing. A hybrid combination of both the approach makes user able to process data effectively with time and cost. The approach is performed on Ubuntu 16.04, HDFS and Java API and maximum power consumption of 112 W as a result.