One common assumption of existing models of load balancing is that the weights of resources and I/O buffer size are statically configured and cannot be adjusted based on a dynamic workload. Though the static configuration of these parameters performs well in a cluster where the workload can be modeled and predicted, its performance is poor in dynamic systems in which the workload is unknown. In...

Cloud computing is a new paradigm for hosting and delivering services on demand over the internet where users access services. It is an example of an ultimately virtualized system, and a natural evolution for data centers that employ automated systems management, workload balancing, and virtualization technologies. Live virtual machine (VM) migration is a technique to achieve load balancing in ...

While previous CPUor memory-centric load balancing schemes are capable of achieving the effective usage of global CPU and memory resources in a cluster system, the cluster exhibits significant performance drop under I/O-intensive workload conditions due to the imbalance of I/O load. To tackle this problem, we have developed two simple yet effective I/O-aware load-balancing schemes, which make i...

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...

Multiple-GPU systems have become ubiquitously available due to their support of massive parallel computing and more device memory for large scale problems. Such systems are ideal for In-Situ visualization applications, which require significant computational power for concurrent execution of simulation and visualization. While pipelining based parallel computing scheme overlaps the execution of...

With nearest neighbor load balancing algorithms, a processor makes balancing decisions based on localized workload information and manages workload migrations within its neighborhood. This paper compares a couple of fairly well-known nearest neighbor algorithms , the dimension-exchange (DE, for short) and the diiusion (DF, for short) methods and their several variants|the average dimension-exch...

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...

Achieving high performance in virtualized data centers requires both deploying high throughput storage clusters, i.e. based on Solid State Disks (SSDs), as well as optimally consolidating the workloads across storage nodes. Nowadays, the only practical solution for cloud storage providers to offer guaranteed performance is to grossly over-provision the storage nodes. The current workload schedu...

Workload and resource management are two essential functions provided at the service level of the Grid software. To improve the global throughput of these environments, effective and efficient load balancing algorithms are fundamentally important. Although load balancing problem in classical distributed systems has been intensively studied, new challenges in Grid computing still make it an inte...

In a multicluster architecture, where jobs can be submitted through each constituent cluster, the job arrival rates in individual clusters may be uneven and the load therefore needs to be balanced among clusters. In this paper we investigate load balancing for two types of jobs, namely non-QoS and QoSdemanding jobs and as a result, two performance-specific load balancing strategies (called ORT ...