A probabilistic-approach based resource allocation algorithm in pervasive computing systems

Ubiquitous technologies are indispensable for modernizing human daily life more and more. However, the technologies are not easily widespread everywhere in our world through infrastructures and other related techniques. We have worked on a project to meet these challenges with a goal to construct a framework for the coming ubiquitous society. In our previous works, we have proposed UMP-PerComp, a Ubiquitous Multiprocessor-based pipeline Processing architecture, to support development of powerful and pervasive applications. In this paper, we propose an optimized algorithm for the UMP system to improve resource allocation executed by one kind of processing nodes called the Resource Router (RR). Using the optimized algorithm, the RR can effectively find a node in the idle state, which actually processes a task assigned by the RR. As a result, the RR saves the time to search for an idle node so that total performance can be improved. Finally, we evaluate the optimized algorithm with probability analyses to show effectiveness more than the previous algorithm we used.