Trust-Oriented IoT Service Placement for Smart Cities in Edge Computing

Abstract

Smart city is gradually forming a large scope of Internet of Things (IoT) networks with diffusely deployed IoT devices that produce quantities of services. Considering the large-scale and widely distributed features of IoT networks, edge computing is emerged as a powerful and suitable paradigm to provide computing abilities for the IoT devices at the edge of the networks. In edge computing, the IoT services could be placed on the edge computing units (ECUs) for execution, which provides low latency and eases the burden of bandwidth. However, it is still challenging to improve the overall ECU execution performance (i.e., the resource usage, the load balance levels, and the power consumption of ECUs) and meanwhile prevent privacy leakage of the IoT devices for service placement. To tackle this challenge, a trust-oriented IoT service placement method, abbreviated as TSP, is proposed for smart cities in edge computing. Technically, improving the strength Pareto evolutionary algorithm (SPEA2) is leveraged to acquire the balanced placement strategies for the tradeoffs among the execution performance metrics with privacy preservation. Additionally, the technique for order preference by similarity to ideal solution (TOPSIS) and multicriteria decision-making (MCDM) techniques are employed to identify the optimal placement strategy among the obtained service placement strategies. Eventually, systematic experiments are conducted to verify the efficiency and reliability of TSP.