An energy efficient fog level resource management scheme for software defined cities

The proliferation of Internet of Things (IoT) and smart city services have paved the path for complex network architectures including edge and fog layer resources in order to meet such services’ Quality of Service (QoS). Such services should also be energy efficient for sustainable cities. Though energy efficiency has been widely studied over the past decade, yet most such solutions have focused on device or sensor level solutions or alternatively on cloud/datacenter level solutions. With the prominence of Software Defined Networks (SDNs) in recent times owing to its flexible and scalable network management features, SDN based fog level resource management has become an attractive alternative. This paper addresses fog level energy-aware resource management with the goal of minimizing energy consumption while QoS fulfillment by means of Virtual Machine (VM) consolidation through live migrations. Since any decent sized smart city would have millions of devices and large numbers of edge/fog instances, it would lead any solution mechanism to a NP hard problem. This paper proposes a novel set based Differential Evolutionary (S-DE) algorithm. Simulations have been carried out to test the efficacy of the proposed S-DE solution and the results demonstrate the efficiency of the proposed method.