Congestion Control for 6LoWPAN Networks: A Game Theoretic Framework

The Internet of Things (IoT) has been considered as an emerging research area where the 6LoWPAN (IPv6 over Low-Power Wireless Personal Area Network) protocol stack is considered as one of the most important protocol suite for the IoT. Recently, the Internet Engineering Task Force has developed a set of IPv6 based protocols to alleviate the challenges of connecting resource limited sensor nodes to the Internet. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and effects the quality of service (QoS) aspects e.g. throughput, end-to-end delay and energy consumption. In this paper, we formulate the congestion problem as a non-cooperative game framework where the nodes (players) behave uncooperatively and demand high data rate in a selfish way. Then, the existence and uniqueness of Nash equilibrium is proved and the optimal game solution is computed by using Lagrange multipliers and KKT conditions. Based on this framework, we propose a novel and simple congestion control mechanism called game theory based congestion control framework (GTCCF) specially tailored for IEEE 802.15.4, 6LoWPAN networks. GTCCF is aware of node priorities and application priorities to support the IoT application requirements. The proposed framework has been tested and evaluated through two different scenarios by using Contiki OS and compared with comparative algorithms. Simulation results show that GTCCF improves performance in the presence of congestion by an overall average of 30.45%, 39.77%, 26.37%, 91.37% and 13.42% in terms of throughput, end-to-end delay, energy consumption, number of lost packets and weighted fairness index respectively as compared to DCCC6 algorithm

Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks

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 non-congested 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 the last few years, the Internet of Things (IoT) has proved to be an interesting and promising paradigm that aims to contribute to countless applications by connecting more physical 'things' to the Internet. Although it emerged as a major enabler for many next-generation applications, it also introduced new challenges to already saturated networks. The IoT is already coming to life especially in healthcare and smart environment applications adding a large number of low-powered sensors and actuators to improve lifestyle and introduce new services to the community. The Internet Engineering Task Force (IETF) developed RPL as the routing protocol for low-power and lossy networks (LLNs) and standardized it in RFC6550 in 2012. RPL quickly gained interest, and many research papers were introduced to evaluate and improve its performance in different applications. In this paper, we present a discussion of the main aspects of RPL and the advantages and disadvantages of using it in different IoT applications. We also review the available research related to RPL in a systematic manner based on the enhancement area and the service type. In addition to that, we compare related RPL-based protocols in terms of energy efficiency, reliability, flexibility, robustness, and security. Finally, we present our conclusions and discuss the possible future directions of RPL and its applicability in the Internet of the future

Congestion analysis for low power and lossy networks

Low Power and Lossy Networks (LLNs) represent one of the interesting research areas in recent years. The IETF ROLL and 6LoWPAN working groups have developed new IP based protocols for LLNs such as the RPL routing protocol. In LLNs e.g. 6LoWPANs, heavy data traffic causes congestion which significantly degrades network performance. In this paper, we explore the impact of congestion on 6LoWPAN networks where an extensive analysis is carried out with different scenarios and parameters. Analysis results show that when congestion occurs, the majority of packets are lost due to buffer overflow as compared to channel loss. Also, we found that when the application payload length is increased since IPv6 packets are fragmented, the reassembly timeout parameter value has a significant effect on network performance. Thus, it is important to consider buffer occupancy and the reassembly timeout parameter in protocol design, e.g. RPL, to improve network performance when congestion does occur

Congestion-aware RPL for 6L0WPAN networks

IPv6 over low power wireless personal area network (6L0WPAN) is promising to be used in many different IoT applications. Recently, many protocols have been proposed for 6LoWPAN networks such as RPL routing protocol which is developed by the ROLL working group and expected to be the standard routing protocol for 6LoWPAN. Many problems are facing 6LoWPAN as it connects to the Internet such as congestion. In this paper, we propose a new RPL routing metric called Buffer Occupancy which reduces the number of lost packets due to buffer overflow when congestion does occur. Also, a new RPL objective function called Congestion-Aware Objective Function (CA-OF) is presented. The proposed objective function works efficiently when congestion occurs by selecting less congested paths. Simulation results show that CA-OF improves performance in the presence of congestion by an overall average of 37.4% in term of number of lost packets, throughput, packet delivery ratio and energy consumption