An Efficient Switch Migration Scheme for Load Balancing in Software Defined Networking

Software-defined networking (SDN) provides increased flexibility to network management through distributed SDN control, and it has been a great breakthrough in network innovation. Switch migration is extensively used for workload balancing among distributed controllers. The time-sharing switch migration (TSSM) scheme proposes a strategy in which more than one controller is allowed to share the workload of a switch via time sharing during overloaded conditions, resulting in the mitigation of ping-pong controller difficulty, a reduced number of overload occurrences, and better controller efficiency. However, it has increased migration costs and higher controller resource consumption during the TSSM operation period because it requires more than one controller to perform. Therefore, we have proposed a strategy that optimizes the controller selection during the TSSM period based on flow characteristics through a greedy set coverage algorithm. The improved TSSM scheme provides reduced migration costs and lower controller resource consumption, as well as TSSM benefits. For its feasibility, the implementation of the proposed scheme is accomplished through an open network operating system. The experimental results show that the proposed improved TSSM scheme reduces the migration cost and lowers the controller resource consumption by about 36% and 34%, respectively, as compared with the conventional TSSM scheme

Edge/Fog Computing Technologies for IoT Infrastructure

The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies