In this paper, we develop load balancing strategies for scalable high-performance parallel A* algorithms suitable for distributed-memory machines. In parallel A* search, ineeciencies such as processor starvation and search of non-essential spaces (search spaces not explored by the sequential algorithm) grow with the number of processors P used, thus restricting its scalability. To alleviate thi...

Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. This paper presents an approach for scheduling algorithms that can maintain the load balancing and provides be...

In this paper, we present an adaptive version of our previously proposed quality equalizing (QE) load balancing strategy that attempts to maximize the performance of parallel branch-and-bound (B&B) by adapting to application and target computing system characteristics. Adaptive QE (AQE) incorporates the following salient adaptive features: (1) Anticipatory quantitative and qualitative load bala...

Feedback guided dynamic load balancing is the process of equilibrating the load of all the processors of a system during execution time based on information gathered from them. It provides better execution times by better utilizing the systems resources. In this work we have suggested a new dynamic load balancing model, named Wave Propagation Model, that is based on the diffusion balancing meth...

Load balancing is an important prerequisite to efficiently execute dynamic computations on parallel computers. In this context, this project has focussed on two topics: balancing dynamically generated work load cost efficiently in a network and partitioning graphs to equally distribute connected tasks on the processing nodes while reducing the communication overhead. We summarize new insights a...

In this paper we study diffusion schemes for dynamic load balancing on message passing multiprocessor networks. One of the main results concerns conditions under which these dynamic schemes converge and their rates of convergence for arbitrary topologies. These results use the eigenstructure of the iteration matrices that arise in dynamic load balancing. We completely analyze the hypercube netw...

GPU-based clusters are an attractive option for parallel volume rendering. One of the key issues in parallel volume rendering is load balancing, keeping a balanced workload per node is essential for improving performance. A good number of dynamic load balancing schemes have been proposed throughout the years. However, most of these approaches require runtime dynamic data movement or data duplic...

Grid computing consists of a number of heterogeneous systems sharing resources toward a common goal. Management of resource and Workload are two main functions by Grid. Grid computing is to create large and powerful self-managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources. Load balancing is used to improve scalability ...

--------------------------------------------------------------------***--------------------------------------------------------------------Abstract Cloud computing is a term, which involves virtualization, distributed computing, networking, software and web services. A cloud consists of several elements such as clients, datacenter and distributed servers. It includes fault tolerance, high avail...

0974-9756/CIIT–IJ-1443/07/$20/$100 © 2011 CiiT Published by the Coimbatore Institute of Information Technology Abstract---The Ad hoc On-Demand Distance Vector (AODV) routing protocol is an efficient Mobile Ad hoc NETworks (MANETs) routing protocol. It uses hop count as a metric for the path selection. AODV does not support Quality of Service (QoS) and neither any load-balancing mechanism. The p...