Tracking Mobile Sinks via Analysis of Movement Angle Changes in WSNs

Yang, Guisong; Xu, Huifen; He, Xingyu; Wang, Gang; Xiong, Naixue; Wu, Chunxue

doi:10.3390/s16040449

Cited by 14 publications

(8 citation statements)

References 16 publications

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“…In our routing strategy, mobile sinks employ agent-based data gathering scheme [ 20 , 26 , 27 ] to collect sensed data. Our routing strategy can be described as follows.…”

Section: New Routing Protocol For Mwsnsmentioning

confidence: 99%

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

Jian-hui

Liu

Cao

et al. 2016

Sensors

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Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

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“…In our routing strategy, mobile sinks employ agent-based data gathering scheme [ 20 , 26 , 27 ] to collect sensed data. Our routing strategy can be described as follows.…”

Section: New Routing Protocol For Mwsnsmentioning

confidence: 99%

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

Jian-hui

Liu

Cao

et al. 2016

Sensors

View full text Add to dashboard Cite

show abstract

“…To further increase the flexibility of the network, another kind of approaches using random or controllable trajectories were proposed [15,16,17,18,19]. In [15], the authors proposed a high-reliability data gathering protocol based on mobile sinks, which adopts the concept of state machine to achieve efficient routing and reduce the overhead.…”

Section: Related Workmentioning

confidence: 99%

“…In [16], a sink tracking method was proposed, in which the nodes track the mobile sink by receiving the broadcast message sent by a mobile sink periodically. In order to further reduce the overhead, a sink tracking method called DAMST [17] was also proposed, in which energy efficiency was high while the overhead is cut down significantly. In [18], a continuous and optimal trajectory was proposed, in which the concept of support vector regression is used to determine the optimal trajectory of a mobile sink to maximize the network lifetime in event-driven sensor networks.…”

Section: Related Workmentioning

confidence: 99%

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs

Yang

Liu

et al. 2016

Sensors

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The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can be divided into subareas where the nodes are randomly deployed. The node densities of these subareas are quite different, which may result in a decreased packet delivery ratio and network lifetime if the movement trajectory of the mobile sink cannot adapt to these differences. To address these problems, we propose an adjustable trajectory design method based on node density for mobile sink in WSNs. The movement trajectory of the mobile sink in each subarea follows the Hilbert space-filling curve. Firstly, the trajectory is constructed based on network size. Secondly, the adjustable trajectory is established based on node density in specific subareas. Finally, the trajectories in each subarea are combined to acquire the whole network’s movement trajectory for the mobile sink. In addition, an adaptable power control scheme is designed to adjust nodes’ transmitting range dynamically according to the movement trajectory of the mobile sink in each subarea. The simulation results demonstrate that the proposed trajectories can adapt to network changes flexibly, thus outperform both in packet delivery ratio and in energy consumption the trajectories designed only based on the network size and the whole network node density.

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“…Later, SinkTrail 13 alleviates the problem by predicting sink's future location; event is transmitted to the future location of mobile sink. Yang et al 14 propose an approach that can forward data to the mobile sink along its moving trajectory, and this method can cancel some detour route by calculating mobile sink's movement angles.…”

Section: Related Workmentioning

confidence: 99%

Biased trajectory dissemination of uncontrolled mobile sinks for event collection in wireless sensor networks

Yang

Wang

Jiang

et al. 2016

International Journal of Distributed Sensor Networks

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Considering the social properties of mobile sinks, we propose a biased trajectory dissemination of uncontrolled mobile sinks for event collection in wireless sensor networks. In biased trajectory dissemination of uncontrolled mobile sink, we first divide the whole network into clusters which can be managed by cluster heads that are elected in turn for intracluster event collection and inter-cluster communication. Second, for a mobile sink, we further divide the clusters it visits into biased clusters and non-biased clusters according to its staying probability. The mobile sink will send its mobility message which shows its location as it moves into a new cluster. We then construct a biased loop which is composed of all biased clusters and some non-biased clusters to disseminate a mobile sink's mobility message only to clusters on it when the mobile sink moves into a biased cluster. We also construct query path that connects any cluster head that is not on the biased loop to a cluster head on it. An event could be transmitted to the biased loop along the query path for further forwarding to the mobile sink. Numerous simulations show the superior performance of biased trajectory dissemination of uncontrolled mobile sink compared to the representative schemes in terms of average path length, delay, and network energy consumption.

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Tracking Mobile Sinks via Analysis of Movement Angle Changes in WSNs

Cited by 14 publications

References 16 publications

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs

Biased trajectory dissemination of uncontrolled mobile sinks for event collection in wireless sensor networks

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