Task allocation in volunteer computing networks under monetary budget constraints

In volunteer computing networks, the peers contribute to the solution of a computationally intensive problem by freely providing their computational resources, i.e., without seeking any immediate financial benefit. In such networks, although the peers can set certain bounds on how much their resources can be exploited by the network, the monetary cost that the network brings to the peers is unclear. In this work, we propose a volunteer computing network where the peers can set monetary budgets, limiting the financial burden incurred on them due the usage of their computational resources. Under the assumption that the price of the electricity consumed by the peers has temporal variation, we show that our approach leads to an interesting task allocation problem, where the goal is to maximize the amount of work done by the peers without violating the monetary budget constraints set by them. We propose various heuristics as solution to the problem, which is NP-hard. Our extensive simulations using realistic data traces and real-life electricity prices demonstrate that the proposed techniques considerably increase the amount of useful work done by the peers, compared to a baseline technique.