A Game Theoretic Optimization of RPL for Mobile Internet of Things Applications

The presence of mobile nodes in any wireless network can affect the performance of the network, leading to higher packet loss and increased energy consumption. However, many recent applications require the support of mobility and an efficient approach to handle mobile nodes is essential. In this paper, 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 packet delivery ratio (PDR), throughput, energy consumption and end-to-end-delay. The proposed solution monitors the mobility of nodes based on received signal strength indication (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 optimized 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

Dynamic RPL for Multi-hop Routing in IoT Applications

The Routing Protocol for Low Power and Lossy Networks (RPL) has become the standard routing protocol for the Internet of Things (IoT). This paper investigates the use of RPL in dynamic networks and presents 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 Packet Delivery Ratio (PDR), end-to-end delay and energy consumption while maintaining low packet overhead and loop-avoidance. We propose a controlled reverse-trickle timer based on received signal strength identification (RSSI) readings to maintain high responsiveness with minimum overhead and consult the objective function when a movement or an inconsistency is detected to help nodes make an informed decision. Simulations are done using Cooja with random waypoint mobility scenario for healthcare applications considering multi-hop routing. The results show that the proposed dynamic RPL (D-RPL) adapts to the nodes mobility and has a higher PDR, slightly lower end-to-end delay and reasonable energy consumption compared to related existing protocols

Hybrid game approach‐based channel congestion control for the Internet of Vehicles

Communications between the Internet of Vehicles in smart cities helps increase the awareness and safety among drivers. However, the channel congestion problem is considered as a key challenge for the communication networks due to continuing collection and exchange of traffic information in dense environments. The channel congestion problem degrades the efficiency and reliability of the ad hoc network. Therefore, the adaptation of the data rate and power control is considered as one of the effective solutions to mitigate channel congestion. This paper develops a new hybrid game transmission rate and power channel congestion control approach on the Internet of Vehicle networks where the nodes play as greedy opponents demanding high information rates with the maximum power level. Furthermore, the existence of a Nash equilibrium, which is the optimal information rate and power transmission for every vehicle, is established. Simulation results demonstrate that the proposed approach enhances the network performance by an overall percentage of 42.27%, 43.94% and 47.66% regarding of channel busy time, messages loss and data collision as compared to others. This increases the awareness and performance of the vehicular communication network

Centralized simulated annealing for alleviating vehicular congestion in smart cities

Vehicular traffic congestion is a serious problem arising in many cities around the world, due to the increasing number of vehicles utilizing roads of a limited capacity. Often the congestion has a considerable influence on the travel time, travel distance, fuel consumption and air pollution. This paper proposes a novel dynamic centralized simulated annealing based approach for finding optimal vehicle routes using a VIKOR type of cost function. Five attributes: the average travel speed of the traffic, vehicles density, roads width, road traffic signals and the roads' length are utilized by the proposed approach to find the optimal paths. The average travel speed and vehicles density values can be obtained from the sensors deployed in smart cities and communicated to vehicles and roadside communication units via vehicular ad hoc networks. The performance of the proposed algorithm is compared with four other algorithms, over two test scenarios: Birmingham and Turin city centres. These show the proposed method improves traffic efficiency in the presence of congestion by an overall average of 24.05%, 48.88% and 36.89% in terms of travel time, fuel consumption and CO2 emission, respectively, for a test scenario from Birmingham city in the UK. Additionally, similar performance patterns are achieved for the a test with data from Turin, Italy

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

Non-cooperative game based congestion control for data rate optimization in vehicular ad hoc networks

The growth of connected vehicles in smart cities increases the number of information being communicated on the Internet of Vehicle networks. This causes wireless channel congestion problems, which degrades the network performance and reliability due to the low throughput, high average delay and the high packets loss. Therefore, this paper proposes a non-cooperative game approach to control congestion in the vehicular ad-hoc network channel where the nodes behave as selfish players requesting high data transmission rates. Moreover, the satisfaction of the Nash equilibrium condition for the optimum data transmission rate for each vehicle, is proven. A utility function is introduced based on data transmission rates, the priority of vehicles and contention delay in order to obtain the optimal rates. The performance of the proposed approach has been evaluated and validated in comparison with three others approaches over two testing scenarios for highway and urban traffic. The results show that the network performance and efficiency have been improved by an overall average of 35%, 30% and 37.17% in terms of packets loss, channel busy time and number of collision messages, respectively, as compared with the state-of-the-art-strategies for the highway testing scenario. Similar performance is achieved for the urban testing scenario. Keywords: Vehicular ad hoc networks, Congestion control, Non-cooperative game approach, Data rate adaptation, IoV applications

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