P2P Grids could solve large-scale scientific problems by using geographically distributed heterogeneous resources. However, a number of major technical obstacles must be overcome before this potential can be realized. One critical problem to improve the effective utilization of P2P Grids is the efficient load balancing. This chapter addresses the above-mentioned problem by using a distributed l...

Cloud Computing is demand based service model where services, information, software and resources hosted on datacenters which are geographically distributed. Load balancing is very important due to the increase in cloud services traffic. Load Balancing is techniques are used that the whole load is distributed among total available datacenters in a distributive cloud system. So there should not ...

Load balancing is the process of redistributing the work load among nodes of the distributed system to improve both resource utilization and job response time while also avoiding a situation where some nodes are heavily loaded while others are idle or doing little work. A dynamic load balancing algorithm assumes no a priori knowledge about job behavior or the global state of the system, i.e., l...

This technical report discussed load balancing algorithms for AMR and the implementations of load balancers currently available in Uintah, the multi-physics framework, developed by the Center for Accidental Fires and Explosions (C-SAFE) to aid the simulation of fires and explosions. We designed several experiments to compare these load balancers by the execution time, the balance of work load d...

The workload on a cluster system can be highly variable, increasing the difficulty of balancing the load across its nodes. The general rule is that high variability leads to wrong load balancing decisions taken with out-of-date information and difficult to correct in real-time during applications execution. In this work the workload variability is studied from the perspective of the load balanc...

Load balancing algorithms play critical roles in systems where the workload has to be distributed across multiple resources, such as cores in multiprocessor system, computers in distributed computing, and network links. In this paper, we study and evaluate four load balancing methods: random, round robin, shortest queue, and shortest queue with stale load information. We build a simulation mode...

Cloud computing requires more reliable, efficient and scalable load balancing algorithm to survive. As one of the main challenges in cloud computing, load balancing facilitate dynamic workload across multiple nodes ensuring that no single node get overloaded. With proper load balancing, resource consumption is maintained at minimum level, enabling scalability, avoiding bottleneck and overprovis...

—This paper proposes a new load balancing strategy, called Comet, for fast multi-agent cluster computing. We use a new load index that takes into account the cost of inter-agent communications. Agents with predictable workload are assigned statically to cluster nodes, whereas agents with unpredictable workload are allowed to migrate dynamically between cluster nodes using a creditbased load bal...

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...

Load balancing plays an effective role on performance in cloud computing environment. Efficient load balancing makes cloud computing more efficient and improves performance of the entire system. In our existing system achieves load balancing with the help of load rebalancing algorithm using DHT protocol.But the existing solutions are not efficient for load balancing so that the various methods ...