Service Home Identification of Multiple-Source IoT Applications in Edge Computing

The real-time communication requirement of the Internet of Things (IoT) applications promotes the convergence of IoT and Mobile Edge Computing (MEC). The MEC paradigm greatly shortens the IoT service delay by leveraging cloudlets (edge servers) of MEC in the proximity of IoT devices. Considering limited computing and storage resources in an MEC network, it is challenging to enable efficient IoT-enabled service provisioning in such a network. In this paper, we study the service home identification problem of service provisioning for multi-source IoT applications in an MEC network, by identifying a service home (cloudlet) of each multi-source IoT application for its data processing, querying, and storage. We consider two novel service home identification problems. We first show that both the problems are NP-hard. We then formulate an Integer Linear Programming (ILP) solution, a randomized algorithm, and an efficient heuristic algorithm for the service operational cost minimization problem. We thirdly devise an online algorithm for the online throughput maximization problem, assuming that multi-source IoT application requests arrive one by one without the knowledge of future arrivals. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising and outperform their comparison counterparts.

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