Cloud Computing is computing where in several groups of servers are networked for providing online access to users. Several factors which influence cloud computing such as scalability, security etc are discussed by many researchers. Now a days usage of internet resources is widely increasing resulting in the increase of workload exponentially. In order to make cloud computing efficient and impr...

MapReduce is a famous model for data-intensive parallel computing in shared-nothing clusters. One of the main issues in MapReduce is the fact of depending its performance mainly on data distribution. MapReduce contains simple load balance technique based on FIFO job scheduler that serves the jobs in their submission order but unfortunately it is insufficient in real world cases as it missed man...

The main purpose of this paper was to find a simple solution for load balancing and fault tolerance in OSGi. The challenge was to implement a highly available web application such as a shopping cart system with load balancing and fault tolerance, without having to change the core of OSGi. Keywords—Fault tolerance, load balancing, OSGi, shopping cart system.

With the rapid development of high-speed wide-area networks and powerful yet low-cost computational resources, grid computing has emerged as an attractive computing paradigm. The space limitations of conventional distributed systems can thus be overcome, to fully exploit the resources of under-utilised computing resources in every region around the world for distributed jobs. Workload and resou...

The Supergen HiDEF (Highly Distributed Energy Future) project focuses on possibilities for decentralising five features of energy systems: resources, control, network infrastructure, participation (markets and commercial arrangements) and policy. This paper concentrates on participation, and the practicalities of an ‘active demand side’. It examines four potential means of altering network and ...

This paper describes predictive load balancing schemes designed for use with parallel adaptive finite element methods. We provide an overview of data structures suitable for distributed storage of finite element mesh data as well as software designed for mesh adaptation and load balancing. During the course of a parallel computation, processor load imbalances are introduced at adaptive enrichme...

Data collection is performed by using the combination of compressive sensing and score based load balancing algorithm. To make the energy efficient network, the score based load balancing algorithm finds the path for routing the data towards the destination. The sensor nodes are divided into clusters and each cluster has one cluster head depending on their energy. The compressive sensing compre...

The load balancer is a fundamental building block for implementing high-throughput applications on multi-core architectures (e.g., network processors). In this paper, we consider two canonical load balancing schemes in the context of packet processing systems: (1) packet-level load balancing that determines the mapping of a packet to processor independently for each packet; and (2) flow-level l...

This paper describes predictive load balancing schemes designed for use with parallel adaptive finite element methods. We provide an overview of data structures suitable for distributed storage of finite element mesh data as well as software designed for mesh adaptation and load balancing. During the course of a parallel computation, processor load imbalances are introduced at adaptive enrichme...

This article emphasizes on load balancing issues associated with hybrid programming models for the parallelization of tiled algorithms onto SMP clusters. Although tiled algorithms usually account for relatively regular computation and communication patterns, their hybrid parallelization often suffers from intrinsic load imbalance between threads. This observation mainly reflects the fact that m...