A New Load-Balancing Aware Objective Function for RPL’s IoT Networks

The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has been recently standardized as the de facto solution for routing in the context of the emerging Internet of Things (IoT) paradigm. RPL, along with other standards, has provided a baseline framework for IoT that has helped advance communications in the world of embedded resource-constrained networks. However, RPL still suffers from issues that may limit its efficiency such as the absence of an efficient load-balancing primitive. In this study, we show how RPL suffers from a load-balancing problem that may harm both the reliability of the protocol and its network lifetime. To address this problem, a novel load-balancing scheme is introduced that significantly enhances the reliability of RPL and fosters the protocol’s efficiency in terms of power consumption

Comparative Analysis of Objective Functions in Routing Protocol for Low Power and Lossy Networks

Internet-of-Things (IoT), a new paradigm, has led to the extensive increase in communication among the tiny and embedded network devices. Majority of those devices are power, memory, and energy constrained and are made to work in lossy environments, thus forming an important part of Low Power and Lossy Networks (LLNs). Routing Protocol for Low Power and Lossy Networks (RPL) designed by Internet Engineering Task Force (IETF) is proved to be an effective candidate for routing in such networks. RPL defines the Objective Functions (OFs) in which a set of routing metrics (like hop count, ETX and so on) are used either in an individual or combined manner for optimal path selection between the nodes of the network in terms of various performance factors like power consumed, Packet Delivery Ratio (PDR), reliability and so on. There are two standard Objective Functions- Objective function Zero (OF0) and Minimum Rank Hysteresis Objective Function (MRHOF). The former uses the hop count and the latter uses the Expected Transmission Count (ETX) as the default routing metrics to select the optimal paths. But both of them are single metric Objective Functions (OFs) and have to face various issues regarding the energy consumed, network lifetime and so on. So a number of RPL optimizations incorporating the different routing metrics in a combined way have been proposed to enhance the performance in all respects. This paper gives the comparative analysis of existing Objective Functions that are based on different routing metrics and concludes that the use of a combination of multiple metrics will further improve the RPL performance in future

Load balancing and context aware enhancements for RPL routed Internet of Things.

Internet of Things (IoT) has been paving the way for a plethora of potential applications, which becomes more spatial and demanding. The goal of this work is to optimise the performance within the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) in the network layer.RPL still suffers from unbalanced load traffic among the candidate parents. Consequently, the overloaded parent node drains its energy much faster than other candidate parent nodes. This may lead to an early disconnection of a part of the network topology and affect the overall network reliability. To solve this problem, a new objective function (OF) has been proposed to usher better load balancing among the bottleneck candidate parents, and keep the overloaded nodes lifetime thriving to longer survival.Moreover, several IoT applications have antagonistic requirements but pertinent, which results in a greater risk of affecting the network reliability, especially within the emergency scenarios. With the presence of this challenging issue, the current standardised RPL OFs cannot sufficiently fulfil the antagonistic needs of Low-power and Lossy Networks (LLNs) applications. In response to the above issues, a context adaptive OF has been proposed to facilitate exchanging the synergy information between the application and network layers. Thus, the impact of the antagonistic requirements based on context parameters will be mitigated via rationalizing the selection decision of the routing path towards the root node.We implemented the proposed protocol and verified all our findings through excessive measurements via simulations and a realistic deployment using a real testbed of a multi-hop LLNs motes. The results proved the superiority of our solution over the existing ones with respect to end-to-end delay, packet delivery ratio and network lifetime. Our contribution has been accepted initially to be adopted within the standard body Internet Engineering Task Force (IETF)

Efficient Routing Primitives for Low-power and Lossy Networks in Internet of Things

At the heart of the Internet of Things (IoTs) are the Low-power and Lossy networks (LLNs), a collection of interconnected battery-operated and resource-constrained tiny devices that enable the realization of a wide range of applications in multiple domains. For an efficient operation, such networks require the design of efficient protocols especially at the network layer of their communication stack. In this regards, the Routing Protocol for LLNs (RPL) has been developed and standardised by the IETF to fulfil the routing requirements in such networks. Proven efficient in tackling some major issues, RPL is still far from being optimal in addressing several other routing gaps in the context of LLNs. For instance, the RPL standard lacks in a scalable routing mechanism in the applications that require bidirectional communication. In addition, its routing maintenance mechanism suffers from relatively slow convergence time, limiting the applicability of the protocol in time-critical applications, and a high risk of incorrect configurations of its parameters, risking the creation of sub-optimal routes. Furthermore, RPL lacks in a fair load-distribution mechanism which may harm both energy and reliability of its networks. Motivated by the above-mentioned issues, this thesis aimed at overcoming the RPL’s weaknesses by developing more efficient routing solutions, paving the way towards successful deployments and operations of the LLNs at different scales. Hence, to tackle the inefficiency of RPL’s routing maintenance operations, a new routing maintenance algorithm, namely, Drizzle, has been developed characterized by an adaptive, robust and configurable nature that boosts the applicability of RPL in several applications. To address the scalability problem, a new downward routing solution has been developed rendering RPL more efficient in large-scale networks. Finally, a load-balancing objective function for RPL has been proposed that enhances both the energy efficiency and reliability of LLNs. The efficiency of the proposed solutions has been validated through extensive simulation experiments under different scenarios and operation conditions demonstrating significant performance enhancements in terms of convergence time, scalability, reliability, and power consumption

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%