IoT service placement architecture for edge computing in smart cities

Abstract

Improved quality of service is provided by the Internet of Things (IoT) devices deployed over IoT networks that form a large part of the smart city environment. At the network’s edges, IoT devices are provided with computing abilities through a suitable and powerful paradigm termed as edge computing, which makes significant contributions to the distributed and large scale IoT network features. For the purpose of execution, in edge computing, edge computing units (ECUs) host the IoT services lessening the burden of bandwidth while providing low latency. Improving the overall execution performance of an ECU in terms of power consumption, load balance level and resource utilization is challenging. However, these parameters are essential in the service placement of IoT devices to ensure leakage of privacy information. A trust-oriented IoT service placement (TSP) scheme is presented in this paper to tackle the aforementioned challenges during edge computing in the IoT networks of the smart city environments. The privacy preservation and execution performance metrics tradeoffs are balanced by the placement strategies by enhancing the strength Pareto evolutionary algorithm. Out of the several placement strategies obtained, the optimal strategy is identified using multicriteria decision making and technique for order preference by similarity to ideal solution schemes. Further, the TSP is evaluated in terms of its reliability and efficiency through systematic experiments.