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.

Wireless sensor networks (WSN) are one of the most rapidly evolving technical areas right now. They can be used in a lot of different applications, environmental monitoring and health applications being two examples. The sensors can be placed in hazardous and remote environments since there is no need for cabling or manual maintenance. One of the biggest problems and constraints of today's WSNs is the limited energy capacity of the sensor nodes. Eventually they will be power-depleted, and the network will be dead. A solution to this can be wireless energy transfer technology which makes it possible to recharge sensor nodes with the help of a mobile charger and prolong the lifetime of networks.  This thesis aims to investigate how the charging completion time can be reduced by considering that the charger can charge while moving and by controlling its velocity. The charging completion time is the time from when the charger starts charging the first node until it returns to that starting point.  For this, a two-dimensional WSN was defined that contains sensor nodes and a mobile charger. Anchor nodes, which the charger travels between were defined by choosing the nodes with most neighbors within a defined charging radius. The traveling salesman problem were used to find a path that the charger travels along. A simulation environment was developed in Python to execute tests.  The results show that the charging while moving approach with controlled velocity could reduce the charging completion time with up to 20%. It was also ascertained that this approach works better in dense networks than in sparse. / Trådlösa sensornätverk är ett av de snabbast växande tekniska områdena just nu. De har många olika användningsområden, miljöövervakning och olika hälsotillämpningar är två exempel. Sensorerna kan placeras i farliga och avlägsna miljöer eftersom det inte finns något behov av kablar eller manuellt underhåll. Ett av de största problemen och begränsningarna på dagens trådlösa nätverk är den begränsade energikapaciteten hos sensornoderna. Slutligen kommer de att bli tömda på ström och nätverket kommer att dö. En lösning på detta kan vara trådlös strömöverföring vilket gör det möjligt att ladda sensorerna med hjälp av en mobil laddare och därmed förlänga livstiden på nätverket.  Syftet med detta examensarbete är att undersöka hur slutförandetiden för laddningen kan reduceras i betraktande av att laddaren kan ladda när den rör sig samt att reglera laddaren hastighet. Slutförandetiden för laddningen är den tid det tar från att laddaren börjar ladda den första sensor-noden tills att den kommer tillbaka till punkten den startade på.  För att göra detta definierades ett två-dimensionellt trådlöst sensornätverk som bestod av sensornoder och en mobil laddare. Ankarnoder, vilka laddaren rörde sig emellan, definierades genom att hitta de noder med flest antal grannar inom en bestämd laddningsradie. Handelsresandeproblemet användes för att bestämma rutten som laddaren färdas längs. En simuleringsmiljö utvecklades i Python för att utföra testerna i.  Resultaten visar att med laddaren som laddade när den rörde på sig samt hade reglerad hastighet kunde slutförande-tiden för laddning reduceras med upp till 20%. Det kunde även konstateras att detta tillvägagångssätt fungerar bättre i täta nätverk än i glesa.