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)

Addressing the DAO Insider Attack in RPL’s Internet of Things Networks

In RPL routing protocol, the DAO (Destination Advertisement Object) control messages are announced by the child nodes to their parents to build downward routes. A malicious insider node can exploit this feature to send fake DAOs to its parents periodically, triggering those parents, in turn, to forward the fake messages upward to the root node. In this study, we show how this behaviour can have a detrimental side effect on the performance of the network, increasing power consumption, latency and reducing reliability. To address this problem, a new scheme is introduced to mitigate significantly the effect of the DAO attack on network performance

Cooja Simulator Manual

While Cooja has been proven to be an ideal tool for the simulation of RPL in WSNs, there are challenges involved in its use, particularly in regard to a lack of documentation. The Contiki website provides an image of Instant Contiki which can then be used with the virtualisation tool VMware. Once Instant Contiki is successfully started the Contiki website can then be referred to for brief instructions regarding a simple network setup on Cooja. However, this is the sum total of any official documentation regarding Cooja, with the majority of support being provided within Internet discussion groups. This report, therefore, aims to provide an instruction set, to enable anyone with no previous exposure to Cooja to be able to create network layouts, compile motes, examine output using the Sensor Data Collect plugin and also utilise scripts to produce more fine-grained results

Load Balancing Objective Function in RPL draft-qasem-roll-rpl-load-balancing-01

This document proposes an extended Objective Function(OF) that balances the number of children nodes of the parent nodes to avoid the overloading problem and ensure node lifetime maximization in the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). The standard OFs are used to build a Destination Oriented Directed Acyclic Graph (DODAG) where the bottleneck nodes may suffer from unbalanced traffic load. As a result, a part of the network may be disconnected as the energy of the overloaded preferred parent node will drain much faster than other candidate parents. Thus, a new RPL metric has been introduced to balance the traffic load over the network. Finally, the potential extra overhead has been mitigated using a new utilization technique

Load Balancing Objective Function in RPL draft-qasem-roll-rpl-load-balancing-01

This document proposes an extended Objective Function(OF) that balances the number of children nodes of the parent nodes to avoid the overloading problem and ensure node lifetime maximization in the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). The standard OFs are used to build a Destination Oriented Directed Acyclic Graph (DODAG) where the bottleneck nodes may suffer from unbalanced traffic load. As a result, a part of the network may be disconnected as the energy of the overloaded preferred parent node will drain much faster than other candidate parents. Thus, a new RPL metric has been introduced to balance the traffic load over the network. Finally, the potential extra overhead has been mitigated using a new utilization technique

Drizzle Algorithm

Trickle algorithm used in RPL routing protocol suffers from some issues related to power, network convergence time and overhead and load-distribution. To optimize this algorithm for Low-power and Lossy Networks (LLNs), a new algorithm called Drizzle is introduced. Drizzle uses an adaptive suppression mechanism that permits the nodes to have different transmission probabilities, which are consistent with their transmission history. Compared to Trickle, Drizzle removes the listen-only period from Drizzle's intervals, thus, leading to faster convergence time. Furthermore, a new policy for setting the redundancy coefficient has been used to mitigate the negative effect of the short-listen problem presented when removing the listen-only period and to further boost the fairness in the network

Drizzle Algorithm

Trickle algorithm used in RPL routing protocol suffers from some issues related to power, network convergence time and overhead and load-distribution. To optimize this algorithm for Low-power and Lossy Networks (LLNs), a new algorithm called Drizzle is introduced. Drizzle uses an adaptive suppression mechanism that permits the nodes to have different transmission probabilities, which are consistent with their transmission history. Compared to Trickle, Drizzle removes the listen-only period from Drizzle's intervals, thus, leading to faster convergence time. Furthermore, a new policy for setting the redundancy coefficient has been used to mitigate the negative effect of the short-listen problem presented when removing the listen-only period and to further boost the fairness in the network

Load Balancing Objective Function in RPL (Draft 2)

This document proposes an extended Objective Function(OF) that balances the number of child nodes of the parent nodes to avoid the overloading problem and ensure node lifetime maximization in the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). The standard OFs are used to build a Destination Oriented Directed Acyclic Graph (DODAG) where the bottleneck nodes may suffer from unbalanced traffic load. As a result, a part of the network may be disconnected as the energy of the overloaded preferred parent node will drain much faster than other candidate parents. Thus, a new RPL metric has been introduced to balance the traffic load over the network. Finally, the potential extra overhead has been mitigated using a new utilization technique

Load Balancing Objective Function in RPL (Draft 2)

This document proposes an extended Objective Function(OF) that balances the number of child nodes of the parent nodes to avoid the overloading problem and ensure node lifetime maximization in the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). The standard OFs are used to build a Destination Oriented Directed Acyclic Graph (DODAG) where the bottleneck nodes may suffer from unbalanced traffic load. As a result, a part of the network may be disconnected as the energy of the overloaded preferred parent node will drain much faster than other candidate parents. Thus, a new RPL metric has been introduced to balance the traffic load over the network. Finally, the potential extra overhead has been mitigated using a new utilization technique