Short-range and near ground propagation model for wireless sensor networks

Yusof, Kamaludin Mohamad; Woods, John; Fitz, Steve

doi:10.1109/scored.2012.6518624

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…The attenuation model of wireless signal can be divided into free-space model and multipath fading model [17], as shown in Figure 1. A sensor node consumes energy when it is generating local data, receiving data, transmitting data, or in standby mode [18].…”

Section: Methods Descriptionmentioning

confidence: 99%

Energy-Balanced Uneven Clustering Protocol Based on Regional Division for Sensor Networks

Sha

Shen

Chen

et al. 2015

International Journal of Distributed Sensor Networks

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In view of the unbalanced energy consumption of traditional cluster-based sensor networks, this paper proposes a type of uneven clustering protocol in data collection. The network is divided into inner and outer regions according to the distance between nodes and the base station. The inner region is consisted of several layers and nodes in outer region are deployed in grids of different sizes. Sensor data is collected by nodes in outer region and then is be transmitted to the inner region. Nodes in the inner region do data fusion and forward data from the lower layer to the higher one. Simulation results show that, compared with MTP and CDFUD, the proposed algorithm performs well in balance of energy consumption and could effectively prolong the network lifetime.

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Section: Methods Descriptionmentioning

confidence: 99%

Energy-Balanced Uneven Clustering Protocol Based on Regional Division for Sensor Networks

Sha

Shen

Chen

et al. 2015

International Journal of Distributed Sensor Networks

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“…There are two types of attenuation models of wireless signal, that are free-space model and multi-path fading model. In Wireless Sensor Networks, the most commonly used method to calculate energy consumption on communication is Equation (27), which was proposed by Heinzeman [ 42 ]:

…”

Section: An Adaptive Recharging Scheme Based On Maximum Benefitmentioning

confidence: 99%

A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks

Sha

Wang

Zhang

et al. 2018

Sensors

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To reduce time delays during data collection and prolong the network lifetime in Wireless Rechargeable Sensor Networks (WRSNs), a type of high-efficiency data collection method based on Maximum Recharging Benefit (DCMRB) is proposed in this paper. According to the minimum number of the Mobile Data Collectors (MDCs), the network is firstly divided into several regions with the help of the Virtual Scan Line (VSL). Then, the MDCs and the Wireless Charging Vehicles (WCVs) are employed in each region for high efficient data collection and energy replenishment. In order to ensure the integrity of data collection and reduce the rate of packet loss, a speed adjustment scheme for MDC is also proposed. In addition, by calculating the adaptive threshold of the recharging request, those nodes with different energy consumption rates are recharged in a timely way that avoids their premature death. Finally, the limited battery capacity of WCVs and their energy consumption while moving are also taken into account, and an adaptive recharging scheme based on maximum benefit is proposed. Experimental results show that the energy consumption is effectively balanced in DCMRB. Furthermore, this can not only enhance the efficiency of data collection, but also prolong the network lifetime compared with the Energy Starvation Avoidance Online Charging scheme (ESAOC), Greedy Mobile Scheme based on Maximum Recharging Benefit (GMS-MRB) and First-Come First-Served (FCFS) methods.

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