An Experimental Comparison of Load Balancing Strategies in a Web Computing Environment

Web Computing is a variant of parallel computing where the idle times of PCs donated by worldwide distributed users are employed to execute parallel programs. The PUB-Web library developed by us supports this kind of usage of computing resources. A major problem for the efficient execution of such parallel programs is load balancing. In the Web Computing context, this problem becomes more difficult because of the dynamic behavior of the underlying "parallel computer": the set of available processors (donated PCs) as well as their availability (idle times) change over time in an unpredictable fashion.In this paper, we experimentally evaluate and compare load balancing algorithms in this scenario, namely a variant of the well-established Work Stealing algorithm and strategies based on a heterogeneous version of distributed hash-tables (DHHTs) introduced recently. In order to run a meaningful experimental evaluation, we employ, in addition to our Web Computing library PUB-Web, realistic data sets for the job input streams and for the dynamics of the availability of the resources.Our experimental evaluations suggest that Work Stealing is the better strategy if the number of processes ready to run matches the number of available processors. But a suitable variant of DHHTs outperforms Work Stealing if there are significantly more processes ready to run than available processors.