A Survey on Congestion Control Protocols for CoAP

The Internet of things (IoT) comprises things interconnected through the internet with unique identities. Congestion management is one of the most challenging tasks in networks. The Constrained Application Protocol (CoAP) is a low-footprint protocol designed for IoT networks and has been defined by IETF. In IoT networks, CoAP nodes have limited network and battery resources. The CoAP standard has an exponential backoff congestion control mechanism. This backoff mechanism may not be adequate for all IoT applications. The characteristics of each IoT application would be different. Further, the events such as unnecessary retransmissions and packet collision caused due to links with high losses and packet transmission errors may lead to network congestion. Various congestion handling algorithms for CoAP have been defined to enrich the performance of IoT applications. Our paper presents a comprehensive survey on the evolution of the congestion control mechanism used in IoT networks. We have classified the protocols into RTO-based, queue-monitoring, and rate-based. We review congestion avoidance protocols for CoAP networks and discuss directions for future work

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

Congestion control in wireless sensor and 6LoWPAN networks: toward the Internet of Things

The Internet of Things (IoT) is the next big challenge for the research community where the IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is a key part of the IoT. Recently, the IETF ROLL and 6LoWPAN working groups have developed new IP based protocols for 6LoWPAN networks to alleviate the challenges of connecting low memory, limited processing capability, and constrained power supply sensor nodes to the Internet. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects such as throughput, latency, energy consumption, reliability, and packet delivery. In this paper, we overview the protocol stack of 6LoWPAN networks and summarize a set of its protocols and standards. Also, we review and compare a number of popular congestion control mechanisms in wireless sensor networks (WSNs) and classify them into traffic control, resource control, and hybrid algorithms based on the congestion control strategy used. We present a comparative review of all existing congestion control approaches in 6LoWPAN networks. This paper highlights and discusses the differences between congestion control mechanisms for WSNs and 6LoWPAN networks as well as explaining the suitability and validity of WSN congestion control schemes for 6LoWPAN networks. Finally, this paper gives some potential directions for designing a novel congestion control protocol, which supports the IoT application requirements, in future work

Analytical modelling of congestion 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 affects the overall performance and the quality of service metrics. In this paper, a new analytical model of congestion for 6LoWPAN networks is proposed using Markov chain and queuing theory. The derived model calculates the buffer loss probability and the channel loss probability as well as the number of received packets at the final destination in the presence of congestion. Also, we calculate the actual wireless channel capacity of IEEE 802.15.4 with and without collisions based on Contiki OS implementation. The validation of the proposed model is performed with different scenarios through simulation by using Contiki OS and Cooja simulator. Simulation results show that the analytical modelling of congestion has an accurate agreement with simulation

Congestion Control for 6LoWPAN Wireless Sensor Networks: Toward the Internet of Things

The Internet of Things (IoT) is the next big challenge for the research community. The IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is considered a key part of the IoT. Due to power, bandwidth, memory and processing resources limitation, heavy network traffic in 6LoWPAN networks causes congestion which significantly degrades network performance and impacts on the quality of service (QoS) aspects. This thesis addresses the congestion control issue in 6LoWPAN networks. In addition, the related literature is examined to define the set of current issues and to define the set of objectives based upon this. An analytical model of congestion for 6LoWPAN networks is proposed using Markov chain and queuing theory. The derived model calculates the buffer loss probability and the number of received packets at the final destination in the presence of congestion. Simulation results show that the analytical modelling of congestion has a good agreement with simulation. Next, the impact of congestion on 6LoWPAN networks is explored through simulations and real experiments 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. Therefore, it is important to consider buffer occupancy in protocol design to improve network performance. Based on the analysis conclusion, a new IPv6 Routing Protocol for Low-Power and Lossy Network (RPL) routing metric called Buffer Occupancy is proposed that reduces the number of lost packets due to buffer overflow when congestion occurs. Also, a new RPL objective function called Congestion-Aware Objective Function (CA-OF) is presented. The proposed objective function works efficiently and improves the network performance by selecting less congested paths. However, sometimes the non-congested paths are not available and adapting the sending rates of source nodes is important to mitigate the congestion. Accordingly, the congestion problem is formulated as a non-cooperative game framework where the nodes (players) behave uncooperatively and demand high data rate in a selfish way. Based on this framework, a novel and simple congestion control mechanism called Game Theory based Congestion Control Framework (GTCCF) is proposed to adapt the sending rates of nodes and therefore, congestion can be solved. The existence and uniqueness of Nash equilibrium in the designed game is proved and the optimal game solution is computed by using Lagrange multipliers and Karush-Kuhn-Tucker (KKT) conditions. GTCCF is aware of node priorities and application priorities to support the IoT application requirements. On the other hand, combining and utilizing the resource control strategy (i.e. finding non-congested paths) and the traffic control strategy (i.e. adapting sending rate of nodes) into a hybrid scheme is important to efficiently utilize the network resources. Based on this, a novel congestion control algorithm called Optimization based Hybrid Congestion Alleviation (OHCA) is proposed. The proposed algorithm combines traffic control and resource control strategies into a hybrid solution by using the Network Utility Maximization (NUM) framework and a multi-attribute optimization methodology respectively. Also, the proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements

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

Data Routing for Mobile Internet of Things Applications

The Internet of things (IoT) represents a new era of networking, it envisions the Internet of the future where objects or “Things” are seamlessly connected to the Internet providing various services to the community. Countless applications can benefit from these new services and some of them have already come to life especially in healthcare and smart environments. The full realization of the IoT can only be achieved by having relevant standards that enable the integration of these new services with the Internet. The IEEE 802.15.4, 6LoWPAN and IPv6 standards define the framework for wireless sensor networks (WSN) to run using limited resources but still connect to the Internet and use IP addresses. The Internet engineering task force (IETF) developed a routing protocol for low-power and lossy networks (LLN) to provide bidirectional connectivity throughout the network, this routing protocol for LLNs (RPL) was standardized in RFC6550 in 2012 making it the standard routing protocol for IoT. With all the bright features and new services that come with the futuristic IoT applications, new challenges present themselves calling for the need to address them and provide efficient approaches to manage them. One of the most crucial challenges that faces data routing is the presence of mobile nodes, it affects energy consumption, end-to-end delay, throughput, latency and packet delivery ratio (PDR). This thesis addresses mobility issues from the data routing point of view, and presents a number of enhancements to the existing protocols in both mesh-under and route-over routing approaches, along with an introduction to relevant standards and protocols, and a literature review of the state of the art in research. A dynamic cluster head election protocol (DCHEP) is proposed to improve network availability and energy efficiency for mobile WSNs under the beacon-enabled IEEE 802.15.4 standard. The proposed protocol is developed and simulated using CASTALIA/OMNET++ with a realistic radio model and node behaviour. DCHEP improves the network availability and lifetime and maintains cluster hierarchy in a proactive manner even in a mobile WSN where all the nodes including cluster heads (CHs) are mobile, this is done by dynamically switching CHs allowing nodes to act as multiple backup cluster heads (BCHs) with different priorities based on their residual energy and connectivity to other clusters. DCHEP is a flexible and scalable solution targeted for dense WSNs with random mobility. The proposed protocol achieves an average of 33% and 26% improvement to the availability and energy efficiency respectively compared with the original standard. Moving to network routing, an investigation of the use of RPL in dynamic networks is presented to provide an enhanced RPL for different applications with dynamic mobility and diverse network requirements. This implementation of RPL is designed with a new dynamic objective-function (D-OF) to improve the PDR, end-to-end delay and energy consumption while maintaining low packet overhead and loop-avoidance. A controlled reverse-trickle timer is proposed based on received signal strength identification (RSSI) readings to maintain high responsiveness with minimum overhead, and consult the objective function when a movement or inconsistency is detected to help nodes make an informed decision. Simulations are done using Cooja with different mobility scenarios for healthcare and animal tracking applications considering multi-hop routing. The results show that the proposed dynamic RPL (D-RPL) adapts to different mobility scenarios and has a higher PDR, slightly lower end-to-end delay and reasonable energy consumption compared to related existing protocols. Many recent applications require the support of mobility and an optimised approach to efficiently handle mobile nodes is essential. A game scenario is formulated where nodes compete for network resources in a selfish manner, to send their data packets to the sink node. Each node counts as a player in the noncooperative game. The optimal solution for the game is found using the unique Nash equilibrium (NE) where a node cannot improve its pay-off function while other players use their current strategy. The proposed solution aims to present a strategy to control different parameters of mobile nodes (or static nodes in a mobile environment) including transmission rate, timers and operation mode in order to optimize the performance of RPL under mobility in terms of PDR, throughput, energy consumption and end-to-end-delay. The proposed solution monitors the mobility of nodes based on RSSI readings, it also takes into account the priorities of different nodes and the current level of noise in order to select the preferred transmission rate. An optimised protocol called game-theory based mobile RPL (GTM-RPL) is implemented and tested in multiple scenarios with different network requirements for Internet of Things applications. Simulation results show that in the presence of mobility, GTM-RPL provides a flexible and adaptable solution that improves throughput whilst maintaining lower energy consumption showing more than 10% improvement compared to related work. For applications with high throughput requirements, GTM-RPL shows a significant advantage with more than 16% improvement in throughput and 20% improvement in energy consumption. Since the standardization of RPL, the volume of RPL-related research has increased exponentially and many enhancements and studies were introduced to evaluate and improve this protocol. However, most of these studies focus on simulation and have little interest in practical evaluation. Currently, six years after the standardization of RPL, it is time to put it to a practical test in real IoT applications and evaluate the feasibility of deploying and using RPL at its current state. A hands-on practical testing of RPL in different scenarios and under different conditions is presented to evaluate its efficiency in terms of packet delivery ratio (PDR), throughput, latency and energy consumption. In order to look at the current-state of routing in IoT applications, a discussion of the main aspects of RPL and the advantages and disadvantages of using it in different IoT applications is presented. In addition to that, a review of the available research related to RPL is conducted in a systematic manner, based on the enhancement area and the service type. Finally, a comparison of related RPL-based protocols in terms of energy efficiency, reliability, flexibility, robustness and security is presented along with conclusions and a discussion of the possible future directions of RPL and its applicability in the Internet of the future

Adaptive Energy Saving and Mobility Support IPv6 Routing Protocol in Low-Power and Lossy Networks for Internet of Things and Wireless Sensor Networks

Internet of Things (IoT) is an interconnection of physical objects that can be controlled, monitored and exchange information from remote locations over the internet while been connected to an Application Programme Interface (API) and sensors. It utilizes low-powered digital radios for communication enabling millions and billions of Low-power and Lossy Network (LLN) devices to communicate efficiently via a predetermined routing protocol. Several research gaps have identified the constraints of standardised versions of IPv6 Routing Protocol for Low Power and Lossy Networks evidently showing its lack of ability to handle the growing application needs and challenges. This research aims to handle routing from a different perspective extending from energy efficiency, to mobility aware and energy scavenging nodes thereby presenting numerous improvements that can suit various network topologies and application needs. Envisioning all the prospects and innovative services associated with the futuristic ubiquitous communication of IoT applications, we propose an adaptive Objective Function for RPL protocol known as Optimum Reliable Objective Function (OR-OF) having a fuzzy combination of five routing metrics which are chosen based on system and application requirements. It is an approach which combines the three proposed implemented Objective Functions within this thesis to enable the OR-OF adapt to different routing requirements for different IoT applications. The three proposed OFs are Energy saving Routing OF, Enhanced Mobility Support Routing OF and Optimized OF for Energy Scavenging nodes. All proposed OFs were designed, implemented, and simulated in COOJA simulator of ContikiOS, and mathematical models were developed to validate simulated results. Performance Evaluation indicated an overall improvement as compared with the standardised versions of RPL protocols and other related research works in terms of network lifetime with an average of 40%, packet delivery ratio of 21%, energy consumption of 82% and End-to-End Delay of 92%