Studies On Algorithms For Sink Mobility In Wireless Sensor Networks

Wireless Sensor Networks (WSNs) is an important technology that has beendeveloped in recent years and widely used in many applications, such as industry,agriculture, environmental monitoring, military, and so on. Sensors’ limit energy is asevere bottleneck that restricts network lifetime. Therefore, how to effectively usesensors’ energy and extend network lifetime is a very important issue. To resolve thisproblerm, one important approach proposed is sink mobility, which can effectively usesensors’ energy, extend network lifetime and improve other performances. In this paper,algorithms for sink mobility are studied and some algorithms are proposed aiming atdifferent types of WSNs. The author’s major contributions are outlined as follows:1. The algorithm for event-driven sensor networks with single mobile sink hasbeen studied. In this paper, it is pointed that it is impossible to forecast random events.However, a sensor can inform the sink when it detects that an event involving it beginsoccurring or the event involving it terminates. The sink can compute a new optimalposition based on the information. Then it is pointed that the sink’s optimal positionshould be the position where the sum of all sensors in event area to the sink is minimum.A heuristic geometrical centre algorithm has been proposed in this paper. The algorithmregards the geometrical centre of all the sensors in event areas as a sub-optimal positionof the sink. And the detailed method that realizes the algorithm has been proposed. Thesimulation results show that the algorithm notably improves network lifetime as well asother performances.2. The algorithm for event-driven sensor networks with multiple mobile sinks hasbeen studied. The network model and basic idea are similar with those of the algorithmfor single mobile sink proposed by us. The difference is that multiple mobile sinks aredeployed in network. In this paper, it is pointed that a sensor should select the sinkwhich is nearest to it as its target sink and report its data to the target sink. When eventsarise or terminate in network, the sinks can obtain the information and computes newoptimal positions for each sink. The sum of all the distances from all sensors in eventareas to their target sinks should be minimum. Therefore, a genetic algorithm basedalgorithm has been proposed in this paper. In the algorithm, a solution is regarded as anindividual. The following two factors are considered in the fitness function: the sum ofthe distances from all sensors in event areas to their target sinks, as well as the sum ofall sensors’ distances from their current positions to their new positions. Aftergenerations of selection, crossover and mutation, an optimal solution for all sinks’ new positions is finally obtained. The detailed method how the sinks collaborate andcoordinate to realize the algorithm has also been proposed. The simulation results showthat the algorithm notably improves network lifetime as well as other performances.3. An algorithm for the sink’s next round position selection which is based ongenetic algorithms has been proposed. The algorithm aims at periodic sensing sensornetworks with single mobile sink. A mobile sink is deployed in the network. All sensorssense and report data to the sink periodically. Each period of data gathering is referredto as a round. At the end of each round, an optimal position of the sink for the nextround is obtained depending on all sensors’ current residual energy. A genetic algorithmsbased algorithm for sink mobility has been proposed in this paper. The algorithmregards a position for the sink as an individual. It is assumed that the sink moves to theposition and make a round of data gathering. Then the variance of all sensors’hypothetical residual energy is computed, which is the fitness function value of geneticalgorithm. After generations of selection, crossover and mutation, an optimal positionfor the sink is finally obtained. The simulation results show that the algorithm notablyextend network lifetime.4. An algorithm for sink mobility based on linear programming has been proposed.A mobile sink is deployed in network. All sensors consecutively sense and report data tothe sink. In this paper, an algorithm for sink mobility based on linear programming hasbeen proposed. It is assumed that the sink sojourns at each sensor’s position andcorresponding routing tree is constructed with LET (Least Energy Tree) algorithm. Andeach sensor’s load is computed on the basis of the routing trees. Finally, the sojourn timeat each sensor are computed with linear programming. The simulation results show thatthe algorithm notably extend network lifetime.5. An algorithm for sink mobility based on dynamic buffer zone has been proposed.In order to prolong network lifetime, buffer zone has been proposed to be deployed innetwork area. The sink moves in the buffer zone. All sensors send their sensed data tothe sensors in the buffer zone. And the sensors in the buffer zone send the data to thesink. To further extend network lifetime, dynamic buffer zone data gathering (DBDG)algorithm has been proposed in this paper. The aogorithm divides the whole networkarea into some areas. The areas take turns at working as the buffer zone. And the time azone work as the buffer zone is reasonably computed with the linear programming toimprove energy efficiency and extend network lifetime. The simulation results showthat DBDG notably extend network lifetime.