Abstract
Automated advance reservation has the potential to ensure a good scheduling solution in computational Grids. To improve global throughput of Grid system and enhance resource utilization, workload has to be distributed among the resources of the Grid evenly. This paper discusses the problem of load distribution and resource utilization in heterogeneous Grids in advance reservation environment. We have proposed an extension of Partner Based Dynamic Critical Path for Grids algorithm named Balanced Partner Based Dynamic Critical Path for Grids (B-PDCPG) that incorporates a hybrid and threshold based mechanism to achieve load balancing to an allowed value of variation in workload among the resources in Partner Based Dynamic Critical Path for Grids algorithm. The proposed load balancing technique uses Utilization Profiles to store the reservation details and check the loads from these profiles on each of the resources and links. The load is distributed among resources based on the processing element capacity and number of processing units on resources. The simulation results, using Gridsim simulation engine, show that the proposed technique has balanced the workload very effectively and has provided better utilization of resources while decreasing the workflow makespan.
Highlights
Large-scale distributed and parallel computing has been changed by the growth of the Internet, powerful computing and network speed
A lot of work has been done in non-Advance reservation (AR) environment for load balancing, yet there is a little contribution by the researchers in providing a solution for load balancing in advance reservation environment [3]
We have addressed the problem of load balancing in advance reservation environment
Summary
Large-scale distributed and parallel computing has been changed by the growth of the Internet, powerful computing and network speed. It utilizes the power of wide range of heterogeneous distributed resources for execution of compute- and data-intensive applications It provides consistent, inexpensive, and pervasive access to geographically widely distributed resources to solve large scale scientific, engineering, and commerce problems. The resources joining the Grid are independent of each other in terms of performance, memory speed, and bandwidths They are owned and administered by different providers. User submitted applications are distributed among various Grid resources and executed in parallel. Consecutive reservations may leave fragments between them which cannot be used by other jobs, leaving un-used empty time slots This leads to the under utilization of Grid resources. The advantages of implementing good load balancing policies are better utilization of resources, low rejection rate, minimized wait time, high performance, maximized throughput, and reduced cost of job execution. Some of them are good for the resource providers, in terms of, resource utilization and throughput while others are good from Grid user’s perspective, in terms of, reduced cost and minimized completion time of application
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
