DEEDSP: Deadline‐aware and energy‐efficient dynamic service placement in integrated Internet of Things and fog computing environments

Abstract

AbstractFog computing has become adaptable and also as a promising infrastructure for providing elastic resources at the edge of the network. Fog computing reduces the transmission latency and consumption of bandwidth while processing the incoming requests from various Internet of Things (IoT) devices. Moreover, fog computing can support and facilitate geographically distributed applications with low and predictable latency. However, this technology also has significant research issues in its current stage such as successful implementation of service location models. In this article, we propose a deadline‐aware and energy‐efficient dynamic service placement (DEEDSP) technique for fog computing that supports the placement of IoT based services. Further, hyper‐heuristic algorithm based energy‐efficient service placement technique is proposed to balance the energy‐delay trade‐off based on different service placement decision criteria (eg, minimum response time or energy consumption). The proposed algorithm is able to dynamically minimize the energy consumption of the system while ensuring that the response time satisfies a given time constraint. Finally, the proposed technique is evaluated in simulated fog computing environment and experimental results show that this technique performs better than state‐of‐the‐art placement techniques in terms of energy and latency.