Dynamic balancing of computation and communication load is vital for the execution stability and performance of distributed, parallel simulations deployed on the shared, unreliable resources of large-scale environments. High Level Architecture (HLA) based simulations can experience a decrease in performance due to imbalances that are produced initially and/or during run time. These imbalances a...

This paper describes the design and implementation of a dynamic load balancing algorithm, Loadserver, which is the hybrid of the two common load balancing models-centralised and distributed. Loadserver exploits the advantage of these models by using low-cost global information and distributed decision making. The algorithm has been incorporated in two kernels which support divide-and-conquer an...

The Zoltan dynamic load balancing library provides applications with a reusable object oriented interface to several load balancing techniques, including coordinate bisection, octree/space filling curve methods, and multilevel graph partitioners. We describe enhancements to Zoltan’s octree load balancing procedure and its distributed structures that improve performance of the space filling curv...

Cloud Computing is growing in real time environment and provides shared resources, information, software packages and other resources as pay per use at specific time. Resources are needed to be equally balanced between various computing processes and to obtain proper utilization of resources load balancing is required. In this paper, various load balancing algorithms are compared on the basis o...

This paper describes a middleware architecture for distributed automotive systems that supports dynamic load balancing of tasks. Load balancing could be applied if an external device is added to the vehicle. The middleware architecture has to deal with the fusion of such non-built-in devices. An important factor to set up such a system is the identification of the requirements that should be ha...

We report on the improvements that can be achieved by applying machine learning techniques, in particular reinforcement learning, for the dynamic load balancing of parallel applications. The applications being considered here are coarse grain data intensive applications. Such applications put high pressure on the interconnect of the hardware. Synchronization and load balancing in complex, heter...

The paper highlights the significance of open source software for distributed computing environment and proposes an adaptive load balancing model using open source software for distributed computing environment. The load balancing strategies used by the model are based on load of the system. The proposed algorithm uses current load, response ratio and processor utilization of the nodes of the w...

We report on the improvements that can be achieved by applying machine learning techniques, in particular reinforcement learning, for the dynamic load balancing of parallel applications. The applications being considered here are coarse grain data intensive applications. Such applications put high pressure on the interconnect of the hardware. Synchronisation and load balancing in complex, heter...

In this paper, the issues in load measurement in dynamic load balancing (DLB) algorithms have been explored. We have analyzed various load indices used to estimate the load on the nodes in the system for load balancing algorithms. The simulation model has been used to address performance issues associated with load balancing. The architecture for implementation and performance evaluation of ind...

Parallel database systems have to support both inter-transaction as well as intra-transaction parallelism. Inter-transaction parallelism (multi-user mode) is required to achieve high throughput, in particular for OLTP transactions, and sufficient cost-effectiveness. Intra-transaction parallelism is a prerequisite for reducing the response time of complex and data-intensive transactions (queries...