Abstract –– General–purpose programmers have come to expect a high degree of portability among widely varying architectures. Advances in run–time systems for parallel programs have been proposed in order to harness available resources as efficiently as possible. Simultaneously, advances in algorithmic ways of dynamically balancing computational load have been proposed in order to respond to var...

Load balancing is a technique in which workload is distributed across multiple computers or other resources to get optimal resource utilization, minimum time delay, maximize throughput and avoid overload. Mainly in operation of parallel and distributed computing systems, load balancing problem arises. Load balancing scheme can be characterized as: static and dynamic load balancing. This paper r...

Distributed processing can be used for solving large computation intensive problems. A distributed system may include parallel supercomputers, networked workstations and PCs. This paper discusses load balancing of a parallel job in a distributed computation environment. The information necessary for load balancing is studied. The software tools that automatically collect the information and per...

In this paper, we present a game theoretic framework for obtaining a user-optimal load balancing scheme in heterogeneous distributed systems. We formulate the static load balancing problem in heterogeneous distributed systems as a noncooperative game among users. For the proposed noncooperative load balancing game, we present the structure of the Nash equilibrium. Based on this structure we der...

In this paper, we consider a Long Term Evolution (LTE) network. The user equipment (UE) nodes connect to the Internet through packet gateway nodes. Multiple P-GWs in the LTE core network forward these packets. Thus, based on how the sessions are established, different gateways may handle different levels of network traffic. If proper load balancing algorithms are not used, the load on some gate...

Multiprocessor load balancing aims to improve performance by moving jobs from highly loaded processors to more lightly loaded processors. Some schemes allow only migration of new jobs upon arrival, while other schemes allow migration of jobs in progress. A difficulty with all these schemes, however, is that they require continuously maintaining detailed state information. In this paper we consi...

Cloud computing is an emerging field of computer science, where heterogeneous services such as applications, servers and storage are delivered to an individual or organization's computer and devices through the Internet. In the proposed research work, a load balancing algorithm is designed, to provide proper utilization of all resources while processing the requests received from the users. We ...

Based on ServiceBSP model, a hierarchical resource load balancing algorithm with Multi-Agent is put forward in this paper which achieves the goal of dynamic load balancing and favorable Fault-tolerant. The algorithm calculates the load value according to the attributes of resource and scheduling tasks relies on the load value, while updating the load information dynamically depending on Multi-A...

In IEEE 802.11 networks composed by multiple APs, before a station can access the network it needs to make a decision about which AP to associate with. Usually, legacy 802.11 stations use no more than the signal strength of the frames received from each AP to support their decision. This can lead to an unbalanced distribution of stations among the APs, causing performance and unfairness problem...

This paper presents a new approach that uses neural networks to predict the performance of a number of dynamic decentralized load balancing strategies. A distributed multicomputer system using any distributed load balancing strategy is represented by a unified analytical queuing model. A large simulation data set is used to train a neural network using the back–propa-gation learning algorithm b...