Modeling the performance and the energy usage of wireless sensor networks by retrial queueing systems

In dense wireless sensor networks, density control is an important technique for prolonging the network's lifetime while providing sufficient sensing coverage. In this paper, we develop three new density control protocols by considering the tradeoff between energy usage and coverage. The first one, Non-Overlapping Density Control, aims at maximizing coverage while avoiding the overlap of sensing areas of active sensors. For the ideal case, a set of optimality conditions are derived to select sensors such that the sensing space is covered systematically to maximize the usage of each sensor and minimize the coverage gap. Based on theoretical optimality conditions, we develop a distributed protocol that can be efficiently implemented in large sensor networks. Next, we present a protocol called Non-Overlapping Density Control Based on Distances that does not require location information of the nodes. This protocol is more flexible and easier to implement than existing location-based methods. Finally, we present a new range-adjustable protocol called Non-Overlapping Density Control for Adjustable Sensing Ranges. It allows heterogenous sensing ranges for different sensors to save energy consumption. Extensive simulation shows promising results of the new protocols.

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On the application of wireless sensor networks in condition monitoring and energy usage evaluation for electric machines

31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005. ◽

10.1109/iecon.2005.1569329 ◽

2005 ◽

Cited By ~ 16

Author(s):

B. Lu ◽

L. Wu ◽

T.G. Habetler ◽

R.G. Harley ◽

J.A. Gutierrez

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Condition Monitoring ◽

Electric Machines ◽

Wireless Sensor ◽

Energy Usage ◽

Usage Evaluation

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MODELING AND SIMULATION OF THRESHOLD ANALYSIS FOR PVFS IN WIRELESS SENSOR NETWORKS

International Journal of Research -GRANTHAALAYAH ◽

10.29121/granthaalayah.v4.i8.2016.2555 ◽

2016 ◽

Vol 4 (8) ◽

pp. 1-10

Author(s):

Tae Ho Cho ◽

Su Man Nam

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Sensor Network ◽

Discrete Event ◽

Wireless Sensor ◽

Proper Function ◽

Message Authentication ◽

System Specification ◽

Authentication Codes ◽

Energy Usage

Wireless sensor networks (WSNs) suffer serious damage from false positive and negative attacks due to their hardware restrictions. The sensor network causes both unnecessary energy consumption and information loss through false reports and normal reports, which include false message authentication codes (MACs). A probabilistic voting-based filtering scheme (PVFS) effectively detects the two types of attacks through a pre-defined threshold, which is the number of detected false MACs in a report. Since the threshold significantly influences the ability to detect attacks, the sensor network should be simulated to ensure proper function. In this paper, we describe the development and simulation of a PVFS-based WSN using a discrete event system specification. The experimental results showed that PVFS with a threshold of 2 reduced energy usage by about 16% and improved the detected false reports as compared with a PVFS with a threshold of 3.

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A Review on Conservation of Energy in Wireless Sensor Networks

International Journal of Smart Sensor Technologies and Applications ◽

10.4018/ijssta.2020040101 ◽

2020 ◽

Vol 1 (2) ◽

pp. 1-16

Author(s):

Oluwadara J. Odeyinka ◽

Opeyemi A. Ajibola ◽

Michael C. Ndinechi ◽

Onyebuchi C. Nosiri ◽

Nnaemeka Chiemezie Onuekwusi

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Energy Harvesting ◽

Data Communication ◽

Sensor Nodes ◽

Wireless Sensor ◽

Energy Usage ◽

Wireless Sensor Nodes ◽

Conservation Of Energy ◽

Battery Energy

This paper is a review on energy conservation in wireless sensor networks (WSNs). Due to the nature of wireless sensor nodes in terms of deployment and their common usage in terrains with limited access, recharging or replacing sensor nodes batteries may be difficult. This paper examined various sources of energy in WSNs Battery, energy harvesting and energy transference. Also, various energy usage operations and energy wastage activities in WSNs were examined, and comparisons of different routing protocols based on network structure, energy dissipation, data communication cost, and entire energy usage in WSNs were itemized. The prospects of the machine learning (ML) approach in addressing energy constraint issues in WSNs were reviewed. This paper recommends a compound approach in routing decisions to maximize energy usage operation and minimize energy wastage activities, consideration for energy harvesting and transference mechanisms, and exploring the potentials in ML algorithms to resolve energy problem in wireless sensor networks.

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Coverage Maximization and Energy Conservation for Mobile Wireless Sensor Networks

International Journal of Natural Computing Research ◽

10.4018/jncr.2012040103 ◽

2012 ◽

Vol 3 (2) ◽

pp. 43-63 ◽

Cited By ~ 9

Author(s):

Nor Azlina Ab. Aziz ◽

Ammar W. Mohemmed ◽

Mohamad Yusoff Alias ◽

Kamarulzaman Ab. Aziz ◽

Syabeela Syahali

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Energy Conservation ◽

Wireless Sensor ◽

Energy Usage ◽

Mobile Wireless ◽

Mobile Wireless Sensor Networks ◽

Coverage Maximization ◽

Mobile Wireless Sensor

WSN is a group of low-cost, low-power, multifunctional and small size wireless sensor nodes that work together to sense the environment, perform simple data processing and communicate wirelessly over a short distance. Mobile wireless sensor networks (WSN) coverage can be enhanced by moving the sensors so that a better arrangement is achieved. However, movement is a high energy consumption task. To maximize coverage the sensors need to be placed not too close to each other so that the sensing capability of the network is fully utilised; however they must not be located too far from each other to avoid coverage holes. It is desired to achieve optimal coverage and at the same time not to relax the mobility energy consumption issue due to the fact that sensors have a limited energy supply. This research is interested in solving the coverage and energy conservation issues of mobile wireless sensors using PSO. In this paper the WSN coverage maximization problem is considered by taking into account the energy spent for sensor repositioning. Thus there are two objectives to be optimized, namely maximizing the coverage and conserving the energy. The two objectives are tackled one by one, starting with the coverage maximization followed by energy conservation. Hence a two-phase PSO approach is proposed. The results show that the proposed algorithm successfully achieves its objectives to reduce the energy usage while at the same time improve the coverage. The energy usage is reduced by cutting down the maximum distance moved.

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