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Effective and Adaptive Energy Restoration in WRSNs by a Mobile Robot

The use of a mobile charger (MC) is a popular method to restore energy in wireless
rechargeable sensor networks(WRSN), whose effectiveness depends critically on the
recharging strategy employed by the MC. In this thesis, we propose a novel on-line
recharging mechanism strategy, called Continuous Local Learning (CLL), which predicts the current energy level of the sensor nodes and dynamically updates the schedule to visit the nodes before their batteries get depleted. The strategy is based on simple computations done by the MC with little memory requirements, and the communication is strictly local (between the MC and neighbouring nodes).
In spite of its simplicity, this strategy was experimentally shown to be highly effective
in keeping the network perpetually operating, ensuring that the number of sensing
holes (i.e., non-operational sensors due to battery depletion) and their duration are
very small at any time, and achieving immortality (i.e., no node ever becoming nonoperational) under many settings even in large networks.
We also studied the flexibility of CLL under a variety of network parameters, showing
its applicability in various contexts. We particularly focused on network size, data
rate, sensors’ battery-capacity, and speed of the MC, and studied their impact on operational size and disconnection time under a wide range of values. The experiments indicate the fact that the effectiveness of CLL holds under all considered settings.
We then compared the proposed solution with the popular class of static strategies
since they share with CLL the features of simplicity, strict local communication and small memory and computational requirements. Experimental results showed that
CLL outperforms these strategies in effectiveness. Not only is the number of sensors
that are operational at any time higher under CLL, but the average duration of a
sensing hole is also significantly lower.
Finally, we studied the adaptability of CLL to a network’s sudden changes, in particular
changes in data rate, which we call spikes. We studied the impact of spikes
parameters on the performance of CLL. Experimental results showed that CLL is
capable of reacting and adapting to these sudden changes with only a slight increase
in non-operational size and disconnection time.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/42879
Date04 November 2021
CreatorsAloqaily, Osama Ismail
ContributorsFlocchini, Paola, Santoro, Nicola
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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