Lifetime improvement of visual sensor networks for target coverage through uniform energy consumption

Hosseini, Mojtaba; Dehghan, Mehdi; Pedram, Hossein

doi:10.1504/ijahuc.2013.058506

Cited by 3 publications

(2 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With a finite amount of energy, only a low amount of information can be transmitted . Therefore, it is important to minimize the energy consumption and lengthen network lifetime in designing an MWSN . There is a trade‐off between the accuracy of measurement and energy consumption in the localization protocol.…”

Section: Energy Consumption For Mobile Virtual Mimo Systemmentioning

confidence: 99%

Energy‐efficient cooperative localization in mobile WSN

Taheri

Motamedi

2016

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

Design and implementation of an energy-efficient protocol is one of the main challenges in wireless sensor networks (WSNs). In terms of localization, both energy efficiency and accuracy must be addressed to achieve the final goals of localization. In mobile sensor nodes, where battery power is the most hardware resource limitation, accurate localization needs to be extremely energy efficient. In this work, a virtual multiple-input multiple-output (VMIMO) technique is deployed to tackle the problems of getting more energy efficiency and higher accuracy simultaneously.In this case, the optimum selection of the number of transceiver nodes can be obtained with the lowest possible total energy consumption, localization error, and speed of nodes. In addition, VMIMO decreases the power of transmitters, and therefore will lead to the reduction of destructive effects of electromagnetic sensitivity (EMS) on the body.

show abstract

Section: Energy Consumption For Mobile Virtual Mimo Systemmentioning

confidence: 99%

Energy‐efficient cooperative localization in mobile WSN

Taheri

Motamedi

2016

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

show abstract

“…23 Therefore, it is important to minimize the energy consumptions and lengthen network lifetime in designing an MWSN. 24,25 There is a trade-o® between the measurement accuracy and energy consumptions in localization protocol. VMIMO is one of the usual schemes for MWSNs to reduce energy consumptions of transmission.…”

Section: Energy Consumptions For Mobile Vmimo Systemmentioning

confidence: 99%

Transceiver Optimization for ToA-Based Localization of Mobile WSN

Taheri

Motamedi

2016

J CIRCUIT SYST COMP

View full text Add to dashboard Cite

One of the main parameters in wireless sensor networks (WSNs) is the design of energy-e±cient protocols. And accuracy is another central goal of localization. Since sensor nodes run on battery power, any WSN application and accurate localization needs to be energy-e±cient. In this paper, the accuracy of localization is increased by accurate measurement of the distance between the mobile sensors. Limit error in multiple-input multiple-output (MIMO) has been calculated by CRB method. Virtual MIMO (VMIMO) technique can obtain better localization precision and the localization is energy-e±cient. Optimum selection of the number of the transceiver nodes is obtained by the lowest possible energy consumption, the existent localization error, and speed of nodes. Mathematical relation between energy consumption and localization of mobile nodes is presented and then veri¯ed by simulation. VMIMO decreases power of transmitters and this in turn will result in decreasing destructive e®ects of electromagnetic sensitivity (EMS) on body. Furthermore, optimized localization parameters will increase the e±ciency of the system and network lifetime. and nonneighbor nodes can lead to the selection of the best route for exchange of messages. In addition, it accelerates exchange of messages and decreases energy consumption of nodes. 1 Localization is a prerequisite for nodes to achieve many of their network tasks.It is essential to measure the distance between a transmitting node and a receiving node or their angular positions in order to estimate the location of the nodes. To achieve this purpose, range-based techniques make use of distance measurements like time of arrival (ToA), angle of arrival (AoA), received signal strength indicator (RSSI), and direction of arrival (DoA) to measure the distances between the nodes to¯nd geographical location of a node. 2 IEEE 802.15.4 Standard has been widely used in WSNs. Ultra-wideband (UWB) is one of the frequency bands de¯ned for the IEEE 802.15.4 Standard. 3 UWB is a major technology implemented for localization and communication because of its desirable feature in accurate ranging and reliable communication. Two design goals, lower cost and lower power consumption, are achieved by the use of UWB in physical layer. This is because it results in using simpler demodulation schemes, lower bit rates, and by that low energy consumption. This technique is a promising method for high-resolution ToA estimation. [4][5][6] The Cramer-Rao bound (CRB) provides a standard benchmark for evaluating any estimator, independent of the particular estimator's form. 7 In this paper, CRB is used to investigate the distance between a transmitter and a receiver, which is an important parameter in localization.The application of multiple-input multiple-output (MIMO) techniques is an ordinary approach in high-speed wireless networks. The quality of communications between wireless devices can be improved by the use of multiple antennas and multiple processing units. Using di®erent antennas by means of multiplexing tech...

show abstract

Energy-efficient mobile node localization using CVA technology and SAI algorithm

Zhang,

Shen,

Yao

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

In the evolving landscape of the Internet of Things (IoT), Mobile Wireless Sensor Networks (MWSN) play a pivotal role, particularly in dynamic environments requiring mobile sensing capabilities. A primary challenge in MWSNs is achieving accurate node positioning with minimal energy consumption, as these networks often consist of battery-powered, mobile sensors where energy replenishment is difficult. This paper addresses the critical problem of energy-efficient node localization in MWSNs. We propose a novel positioning approach leveraging Cooperative Virtual Array (CVA) technology, which strategically utilizes the mobility of nodes to enhance positioning accuracy while conservatively using energy resources. The methodology revolves around optimizing the number of transceiver nodes, considering factors such as node moving speed, total energy consumption, and positioning errors. Central to our approach is the Signal Arrival and Interaction (SAI) algorithm, an innovative technique devised for efficient and precise mobile node localization, replacing traditional Time of Arrival (ToA) methods. Our simulations, conducted under various scenarios, demonstrate the significant advantages of the CVA-based positioning algorithm. Results show a marked reduction in energy consumption and robust performance in mobile node scenarios. Key findings include substantial improvements in localization accuracy and energy efficiency, highlighting the potential of our approach in enhancing the operational sustainability of MWSNs. The implications of this research are far-reaching for IoT applications, particularly those involving mobile sensors, such as in smart cities, industrial monitoring, and disaster management. By introducing a novel, energy-efficient positioning method, our work contributes to the advancement of MWSN technology, offering a sustainable solution to the challenge of mobile node localization.

show abstract

Lifetime improvement of visual sensor networks for target coverage through uniform energy consumption

Cited by 3 publications

References 36 publications

Energy‐efficient cooperative localization in mobile WSN

Energy‐efficient cooperative localization in mobile WSN

Transceiver Optimization for ToA-Based Localization of Mobile WSN

Energy-efficient mobile node localization using CVA technology and SAI algorithm

Contact Info

Product

Resources

About