Co-locating services in IoT systems to minimize the communication energy cost

Ubiquitous sensing and actuating devices are now everywhere in our living environment as part of the global cyber–physical ecosystem. Sensing and actuating capabilities can be modeled as services to compose intelligent Internet of Things (IoT) applications. An issue for perpetually running and managing these IoT devices is the energy cost. One energy saving strategy is to co-locate several services on one device in order to reduce the computing and communication energy. In this paper, we propose a service merging strategy for mapping and co-locating multiple services on devices. In a multi-hop network, the service co-location problem is formulated as a quadratic programming problem. We show a reduction method that reduces it to the integer programming problem. In a single hop network, the service co-location problem can be modeled as the Maximum Weighted Independent Set (MWIS) problem. We show the algorithm to transform a service flow to a co-location graph, then use known heuristic algorithms to find the maximum independent set which is the basis for making service co-location decisions. The performance of different co-location algorithms are evaluated by simulation in this paper.