A QoS-Aware IoT Service Placement Mechanism in Fog Computing Based on Open-Source Development Model

With rapid developments of the Internet of Things (IoT) applications in recent years, their use to facilitate day-to-day activities in various domains for enhancing the quality of human life has significantly increased. Fog computing has been developed to overcome the limitations of cloud-based networks and to address the challenges posed by the massive growth of IoT devices. This paradigm can provide better Quality of Service (QoS) in terms of low energy consumption and fast response, and cope with latency and bandwidth limitations. Since IoT applications are offered in the form of multiple IoT services with different QoS requirements, it is essential to develop an efficient IoT service deployment mechanism in a fog environment with distributed fog nodes and centralized fog servers. This is referred to as the Fog Services Placement (FSP) problem. Hence, we propose a QoS-aware IoT services placement policy with different objectives as a multi-objective optimization problem. Given the proven effectiveness of meta-heuristic techniques in solving optimization problems, we have used the Open-source Development Model Algorithm (ODMA) to deploy IoT services on fog nodes called FSP-ODMA. FSP-ODMA uses the service cost, energy consumption, response time, latency, and fog resource utilization as objective functions to find the optimal IoT service placement plan. In addition, we propose a three-layer conceptual computing framework (i.e., cloud-fog-IoT) to describe the interactions between system components and the FSP problem-solving policy. The simulation results obtained demonstrate that the proposed solution increases the resource usage and service acceptance ratio and reduces the service delay and the energy consumption compared with the other metaheuristic-based mechanisms.