Description

On the Design of Mutually Aware OptimalPricing and Load Balancing Strategiesfor Grid Computing Systems. Managing resources and cleverly pricing them on computing systems is a challenging task. Resource sharing demands careful load balancing and often strives to achieve a win-win situation between resource providers and users. Toward this goal, we consider a joint treatment of load balancing and pricing. We do not assume static pricing to determine load balancing, or vice versa. Instead, we study the relationship between the price that a computing node is charged and the load and revenue that it receives. We find that there exists an optimal price which maximizes the revenue. We then consider a multi-user environment and explore how the load from a user can be balanced on processors with existing loads. Finally, < Final Year Projects > we derive an optimal price that maximizes the revenue in the multi-user environment. We evaluate the performance of the proposed algorithms through simulations.