Characterization of the impact of resource availability on opportunistic computing

With opportunistic computing, devices are no longer restricted to using their own services and resources, but can access services and resources made available by other devices. The performance of opportunistic computing is greatly affected by the resource topology in the network: what resources/services are available, as well as when and where they can be tapped. This paper presents a preliminary investigation of the impact of the resource availability on the performance of opportunistic computing. Specifically, we propose a metric called Expected Resource Availability, ERA, that attempts to capture the impact of the topology of services and resources. The ERA offers a proxy for the applicability of opportunistic computing schemes to a given network: if the ERA is low, any opportunistic scheme can be expected to fail due to a sheer lack of resources and/or connectivity among them. On the other hand, if the ERA is high, success can be expected. To gain perspective on the properties of the ERA, we tackle the problem of service allocation in opportunistic computing, which suffers to combinatorial explosion when looking for the optimal solution. We also present some preliminary simulation results that confirm the validity of the ERA as a metric to gauge whether opportunistic computing can be achieved in a given network.