A grid is a wide-area computing environment for cross-domain resource sharing and service integration. Software agents are one of mainstream technologies for management of geographically distributed grid resources. In this work, self-organization mechanisms are investigated for multiple agents to cooperate with each other so that an overall grid load balancing and resource scheduling can be ach...

Cloud computing is internet-based computing in which large groups of remote servers are networked to allow the centralized data storage, and online access to computer services or resources. Major issue of cloud computing is in its load balancing. In this proposed work, an efficient dynamic load balancing algorithm for cloud environment is introduced. So many clients requesting for same resource...

Structured peer-to-peer (P2P) systems address the load balancing issue in a rather naive way, by simply resorting to the uniformity of the hash function utilized to generate object IDs. Such a random choice of object IDs could result in O(logN) load imbalance. In this position paper, we propose an efficient, proximity-aware load balancing algorithm for such systems. To our knowledge, this is th...

Increasingly large-scale clusters of SMPs continue to become majority platform in HPC field. Such a cluster environment, there may be load imbalances due to several reasons and mis-placement of data which bring performance bottlenecks. To overcome these problems, some dynamic load balancing mechanisms are needed. In this paper, we report our ongoing work on dynamic load balancing extention to O...

Over the past three decade, parallel and distributed computing witnessed major growth due to the declined cost of hardware, advancement in communication technology, explosive growth of internet and need to solve large-scale problems. These systems often face the problem of load imbalance, which can degrade the performance of the system. Load balancing improves the system performance by dividing...

Computational Fluid Dynamics (CFD) applications are “highly parallelizable” and can be distributed across a cluster of computers. However, because computation time can vary with the distributed part (mesh), the system loads are unpredictable and processors can have widely different computation speeds. Load balancing (and thus computational efficiency) across a heterogeneous cluster of processor...

Due to popularity of Cloud computing environment, the cloud computing users are increasing day by day and that has become one of the important challenge for the cloud providers in terms of load balancing. Load balancing distributes the traffic evenly over multiple paths. In this research work, we have proposed the Dynamic Improved PSO Load balancing algorithm and implement it over CloudSim tool...

This paper presents the results of an experimental study of load balancing using job initiation and process migration, carried out on Amoeba. The results indicate the need for a load balancing facility in a distributed system to improve system performance, e.g., the average response time of processes. A number of load balancing algorithms, including the bidding and neighbouring algorithms, have...

This paper deals with the problem of load balancing in SPMD parallel applications. Based on the study of recent work in the area, we propose a taxonomy that provides a terminology and a framework for describing and classifying the growing number of SPMD load balancing algorithms. This allows more thorough and systematic comparison studies of diierent load balancing techniques, helping designers...

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