With the exponential increase in demands of online applications and services, cloud computing has evolved as a boon in modern information technology. Built over the base of grid and distributed computing, cloud computing offers services to cater the dynamic needs of massive user base. However, with the novelty associated with the system, cloud computing is also associated with certain issues li...

Nature Inspired Meta-Heuristic algorithms are proved to be beneficial for solving real world combinatorial problems such as minimum spanning tree, knapsack problem, process planning problems, load balancing and many more. In this research work, existing meta-heuristic approaches are discussed. Due to astonishing feature of echolocation, bat algorithm has drawn major attention in recent years an...

Load balancing is a key concern when developing parallel and distributed computing applications. The emergence of computational grids extends this problem, where issues of cross-domain and large-scale scheduling must also be considered. In this work an agent-based grid management infrastructure is coupled with a performance-driven task scheduler that has been developed for local grid load balan...

Evolutionary algorithms provide mechanisms that can achieve efficient exploration for design spaces. This way, they constitute an efficient tool for identifying the best alternatives to implement the solution of a certain problem. In this work we apply the genetic algorithms to the field of distributed load balancing in parallel computers. We have classified and parameterized the different dist...

This article proposes a design and implementation of a low cost two-tier architecture model for high availability cluster combined with load-balancing and shared storage technology to achieve desired scale of three-tier architecture for application load balancing e.g. web servers. The research work proposes a design that physically omits Network File System (NFS) server nodes and implements NFS...

In this paper, we present a load balancing protocol in the context of a CSMA/CD local area network. The main objective of this protocol is to achieve efficient load balancing among a group of homogeneous processing sites, interconnected by an Ethernet LAN. Usually when the bus load in such networks approaches bus capacity, the mean packet delay increases rapidly. Thus, some time-critical messag...

In parallel computing, a problem is divided into a set of smaller tasks that are distributed across multiple processing elements. Balancing the load of the processing elements is key to achieving good performance and scalability. If the computational costs of the individual tasks vary over time in an unpredictable way, dynamic load balancing aims at migrating them between processing elements so...

• We propose a new optimal automatic load balancing criterion for parallel iterative applications. introduce an algorithm finding the time at which dynamic should be triggered. Our outperforms state-of-the-art criteria by up to 17.6%, while being, on average, 4.9% faster. show that are most 42% slower than optimum. Parallel applications often suffer from imbalance, one of critical performance d...

Grid Computing involves coupled and coordinated use of geographically distributed resources for purposes such as large-scale computation and distributed data analysis. With the Grid becoming a viable high-performance alternative to the traditional supercomputing environment, a suitable and efficient load balancing algorithm is needed to equally spread the load on each computing node in the grid...

| Parallel scheduling is a new approach for load balancing. In parallel scheduling, all processors cooperate together to schedule work. Parallel scheduling is able to accurately balance the load by using global load information at compile-time or runtime. It provides a high-quality load balancing. This paper presents an overview of the parallel scheduling technique. Particular scheduling algori...