Dynamic Load Balancing and Self-load Migration with Delay Queue in DVE

Distributed Virtual environments are gaining a lot of attention recently, due to the ever improving popularity of on the internet and social networking sites. As the variety of contingency users of a distributed virtual environment increases the critical issue is coming up, the issue describes as improving amount of work between several web servers how can be balanced to maintain real-time efficiency. The variety of load balancing methods has been suggested recently but they either try to produce high quality load balancing outcomes and become too slow or highlight on efficiency and the load balancing outcomes become less effective. In this perform, the new approach is suggested to address this issue based on the Front load balancer. The heat diffusion methods is used to develop a load balancing system after that the front load balancer will create improvements in the Dynamic load balancing of the several web servers with Delay queue. The numbers of tests are performed to evaluate the efficiency of the suggested technique. The trial outcomes show that the suggested technique works effectively in reducing server over-loading while at the same time being efficient. DOI: 10.17762/ijritcc2321-8169.15077

Decentralized load balancing in heterogeneous computational grids

With the rapid development of high-speed wide-area networks and powerful yet low-cost computational resources, grid computing has emerged as an attractive computing paradigm. The space limitations of conventional distributed systems can thus be overcome, to fully exploit the resources of under-utilised computing resources in every region around the world for distributed jobs. Workload and resource management are key grid services at the service level of grid software infrastructure, where issues of load balancing represent a common concern for most grid infrastructure developers. Although these are established research areas in parallel and distributed computing, grid computing environments present a number of new challenges, including large-scale computing resources, heterogeneous computing power, the autonomy of organisations hosting the resources, uneven job-arrival pattern among grid sites, considerable job transfer costs, and considerable communication overhead involved in capturing the load information of sites. This dissertation focuses on designing solutions for load balancing in computational grids that can cater for the unique characteristics of grid computing environments. To explore the solution space, we conducted a survey for load balancing solutions, which enabled discussion and comparison of existing approaches, and the delimiting and exploration of the apportion of solution space. A system model was developed to study the load-balancing problems in computational grid environments. In particular, we developed three decentralised algorithms for job dispatching and load balancing—using only partial information: the desirability-aware load balancing algorithm (DA), the performance-driven desirability-aware load-balancing algorithm (P-DA), and the performance-driven region-based load-balancing algorithm (P-RB). All three are scalable, dynamic, decentralised and sender-initiated. We conducted extensive simulation studies to analyse the performance of our load-balancing algorithms. Simulation results showed that the algorithms significantly outperform preexisting decentralised algorithms that are relevant to this research