On Role Assignment for Participatory Sensing System

Mobile crowd sensing is one of the most active areas of research. Participatory sensing is part of it in which participants sense their surroundings and collaborate to accomplish a given task. The participants in reference are smartphones. We focus on location dependent tasks and a problem of role assignment. An existing work on the same defines three types of roles for the participants: broadcasters, normal participants and location information receiver. The broadcasters and normal participants turn on their GPS while location information receivers rely on broadcasters to compute their position. The existing work provides a centralized approach which uses greedy algorithm for role assignment. We propose a sorting based algorithm which minimizes 12-25% of the time for medium and large datasets. We also modify the energy model to minimize power consumption of devices. For this we provide a scheme so that only few devices turn on cellular network to contact server as cellular network consumes considerable energy of smartphones. In the existing approach if new devices join the region then they cannot participate in the ongoing sensing task until server assigns them role during the next localization phase. In addition to this, if device leaves the region then its neighbouring devices may minimize energy needs by changing their role. However, in the current work the algorithm is required to run over entire set of participants for each insertion and deletion of participant. We provide an alternative method to allocate roles adaptively to new participants and change roles for the existing devices when some devices leave the region on fly. This helps to minimize over 95-99.9% time for role assignment compared to existing state of work. In addition to this, we have also proposed a distributed approach so that devices are self-capable of assigning role to themselves based on local information. This is first work so far to relieve server from the task of role assignment. Besides proposing a method, we have also taken into account the residual energy of smartphones for assigning the role of broadcaster which has not been considered before. Our algorithm takes 70-85% less time compared to centralized approach but consumes 12-15% more energy as it does not provide optimal set of broadcasters which requires global information. All the work has been validated through extensive experiments using both real and synthetic datasets.