Visualization of dynamic fault tolerance rerouting for data traffic in wireless sensor network

Jeong, Young‐Sik; Park, Jong Hyuk

doi:10.1002/dac.2406

Cited by 2 publications

(2 citation statements)

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“…Because sensors can be deployed to monitor a certain area and can communicate with each other, a wireless sensor network can thus be constructed [1][2][3][4]. In addition, many functions are available for sensors, such as the sensing of humidity, temperature, light, pressure, sound, and data transmission.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, many functions are available for sensors, such as the sensing of humidity, temperature, light, pressure, sound, and data transmission. Because sensors can be deployed to monitor a certain area and can communicate with each other, a wireless sensor network can thus be constructed [1][2][3][4]. Today, wireless sensor networks have been widely studied for many environment surveillance applications [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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Novel methods for energy charging and data collection in wireless rechargeable sensor networks

Liu

Nguyen

Pham

et al. 2015

Int J Communication

123

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In wireless rechargeable sensor networks, sensors are responsible for sensing environment and generating sensed data, and mobile devices are responsible for recharging sensors and/or collecting sensed data to the sink. Because of the rapid development of wireless charging technology, sensors can be recharged when they are within limited charging ranges of mobile devices. In addition, because sensors' electric capacity and memory storage are often limited, sensors must be recharged, and their generated data must be collected by mobile devices periodically, or the network cannot provide adequate quality of services. Therefore, the problem of scheduling minimum mobile devices to periodically recharge and collect data from sensors subject to the limited charging range, electric capacity, and memory storage, such that the network lifetime can be guaranteed to be prolonged without limits, termed the periodic energy replenishment and data collection problem, is studied in the paper. For the problem, the grid-based algorithm, the dominating-set-based algorithm, and the circle-intersection-based algorithm are proposed to find a set of anchor points. In addition, the mobile device scheduling algorithm is proposed to schedule minimum mobile devices to visit the generated anchor points. Simulation results show that our proposed methods provide good performance.to sense the environment and obtain energy from natural energy resources in duty cycles. When the ambient energy replenishment rate has a temporal variance, efficient algorithms are proposed in [11] to track instantaneous optimal sampling rates and routes, and to maintain the battery at the desired target level. Because the natural energy is often unstable and varies with time and the environment, the WRSNs whose sensors are recharged by natural energy provide only low-rate data services.In WRSNs, wireless charging techniques are often used to charge sensors to replenish their energy. When wireless charging techniques are applied to mobile devices, the mobile devices can be scheduled to recharge sensors in WRSNs. In [12], a wireless charging system is proposed to prolong the network lifetime. In the system, the sink is responsible for collecting energy information reported by sensors. When some sensors need energy, a mobile robot is scheduled to visit the sensors for energy replenishment. In [13], a battery-aware mobile energy replenishment method is proposed to schedule a mobile device to visit locations such that the sensors within the charging range of the mobile device can be recharged. In [14], a limited number of mobile vehicles are scheduled to recharge sensors with the minimum total traveling cost of multiple vehicles when the sensors' energy status is collected by mobile vehicles. In [15], an algorithm of constructing a set of nested traveling salesman problem (TSP) tours based on sensors' energy consumption rates is proposed to minimize charger moving distance and node charging service delay. In addition, in [16], a demonstration is developed to show the perf...

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Section: Introductionmentioning

confidence: 99%