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).
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:768483 |
| Date | January 2018 |
| Creators | Qasem, Mamoun |
| Contributors | Al-Dubai, Ahmed ; Romdhani, Imed |
| Publisher | Edinburgh Napier University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://researchrepository.napier.ac.uk/Output/1532122 |
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