Opt-ACM: An Optimized load balancing based Admission Control Mechanism for Software Defined Hybrid Wireless based IoT (SDHW-IoT) network

The wide network applications of Internet of Things (IoT) urge to integrate the different wireless networking technologies. However, the future generation technologies like Software Defined Networking (SDN) can be useful to alleviate the associated challenges such as security, installation issues, coverage, etc. The growing number of IoT users produce massive volume of traffic causing heavy network load conditions, resulting in the state of network congestion. The network congestion may cause severe performance degradation issues such as frequent packet drops, longer delays, low throughput, etc. Thus, a promising solution is needed to reduce and/or prevent the network congestion. This paper presents an Optimized load balancing based Admission Control Mechanism (Opt-ACM) for effective network flow management resulting in the reduced network congestion. In addition to this, the paper highlights the challenges of the existing solutions, and discusses a Software Defined Hybrid Wireless based IoT (SDHW-IoT) network architecture consisting of Software Defined Wireless Sensor Network (SDWSN) and Software Defined Wireless Mesh Network (SDWMN). To validate the efficiency of Opt-ACM, a Mixed-Integer Linear Programming (MILP) based optimization problem is formulated and tested using a well-known mathematical optimization solver called Gurobi. Additionally, Opt-ACM is also emulated in Mininet-Wifi with varying network scenarios against some traditional (OLSR and OSPF) and stateof-the-art (FACOR and EASDN) approaches. Opt-ACM achieves an overall efficiency of 9.47% and 12.32% over other approaches for Packet Delivery Ratio (PDR) and Packet Loss Ratio (PLR) respectively. Similarly, an average improved efficiency of 26.77% and 33.10% is achieved with respect to the Average Delay (AD) and Average Jitter (AJ) metrics respectively.