Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks

Abstract

Abstract-The IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack is a key part of the Internet of Things (IoT) where the 6LoWPAN motes will account for the majority of the IoT 'things'. In 6LoWPAN networks, heavy network traffic causes congestion which significantly effects the network performance and the quality of service (QoS) metrics. Generally, two main strategies are used to control and alleviate congestion in 6LoWPAN networks: resource control and traffic control. All the existing work of congestion control in 6LoWPAN networks use one of these. In this paper, we propose a novel congestion control algorithm called optimization based hybrid congestion alleviation (OHCA) which combines both strategies into a hybrid solution. OHCA utilizes the positive aspects of each strategy and efficiently uses the network resources. The proposed algorithm uses a multi-attribute optimization methodology called grey relational analysis for resource control by combining three routing metrics (buffer occupancy, expected transmission count and queuing delay) and forwarding packets through noncongested parents. Also, OHCA uses optimization theory and Network Utility Maximization (NUM) framework to achieve traffic control when the non-congested parent is not available where the optimal nodes' sending rate are computed by using Lagrange multipliers and KKT conditions. The proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements where the applications' sending rate allocation is modelled as a constrained optimization problem. OHCA has been tested and evaluated through simulation by using Contiki OS and compared with comparative algorithms. Simulation results show that OHCA improves performance in the presence of congestion by an overall average of 28.36%, 28.02%, 48.07%, 31.97% and 90.35% in terms of throughput, weighted fairness index, end-to-end delay, energy consumption and buffer dropped packets as compared to DCCC6 and QU-RPL.

RPL-Based Routing Protocols in IoT Applications: A Review

“…In and [99], the authors introduce a congestion alleviation scheme based on grey theory, it uses buffer occupancy, ETX and queuing delay in a multi attribute optimization approach. It also uses a utility function to maximize throughput in noncongested situations making it a hybrid solution that combines both traffic control and resource control.…”

Congestion Control and Traffic Differentiation for Heterogeneous 6TiSCH Networks in IIoT

“…Congested gateways share their load in a distributed fashion to achieve a global load fairness; however, the approach is not applicable in RPL networks with a single gateway. The works in [ 26 , 27 , 28 ] proposed to formulate the congestion issue as an optimization problem based on a strictly concave and continuously differentiable function, e.g., congestion cost function or a utility function, where the objective is to select the optimal sending rate to minimize the congestion level. However, this approach is not applicable in many IIoT applications where setting a predefined sending rate is crucial to maintain the network functionality and stability.…”

A Survey on Congestion Control for RPL-Based Wireless Sensor Networks

“…Since the primary role of a network layer protocol is to find a good route, RPL schemes are rarely related to adaptation of the sending rate. Nevertheless, some schemes, such as GTCC [16] and OHCA [20], adopt both resource control and traffic control approaches.…”

“…Al-Kashoash et al proposed OHCA (optimization-based hybrid congestion alleviation) which combines a resource control strategy with a traffic control strategy [20]. If a parent node detects the arrival rate exceeding the service rate, it deems the congestion condition to be met and sends its children nodes a DIO message containing congestion information.…”