Hadoop MapReduce framework is an important distributed processing model for large-scale data intensive applications. The current Hadoop and the existing Hadoop distributed file system’s rack-aware data placement strategy in MapReduce in the homogeneous Hadoop cluster assume that each node in a cluster has the same computing capacity and a same workload is assigned to each node. Default Hadoop d...

In a distributed network of computing hosts, the performance of the system can depend crucially on dividing up work effectively across the participating nodes. Dynamic load balancing have the potential of performing better than static strategies, they are inevitably more complex. The overheads involved are much more. But one can not negate their benefits. Load balancing is found to reduce signi...

In recent years, renewable energy sources have been considered the most encouraging resources for grid and off-grid power generation. This paper presents an improved current control strategy for a three-phase photovoltaic grid-connected inverter (GCI) under unbalanced and nonlinear load conditions. It is challenging to suppress the harmonic content in the output current below a pre-set value in...

Although a large number of users are using P2P systems, the ability of these systems to provide services with quality is questioned. A load balanced P2P system can provide services with smaller failure rate and better performance; hence, service quality of the system can be improved. Cluster systems have been adopted for services which are tolerant to faults. Although a cluster structure improv...

Grid computing has become conventional in distributed systems due to technological advancements and network popularity. Grid computing facilitates distributed applications by integrating available idle network computing resources into formidable computing power. As a result, by using efficient integration and sharing of resources, this enables abundant computing resources to solve complicated p...