ECO CS: Energy consumption optimized compressive sensing in group sensor networks

Yang, Hao; Wang, Xiwei

doi:10.1016/j.comnet.2018.07.003

Cited by 7 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The cluster head established a minimum spanning tree based on the above factors, and used ant colony algorithm to optimizing routing effectively extends the lifetime of the network and reduce the energy consumption of nodes. Paper [37] proposed an extended ant colony-based cognitive wireless network routing algorithm, which combined delay time with idle frequency bands and used non-uniform clustering to cluster nodes, and gave the best candidate cluster head probability solution. And then it uses the ACO algorithm to complete the path search and complete the data transmission and the delay can be reduced.…”

Section: A Coverage Problemmentioning

confidence: 99%

CoC-SCS: Cooperative-Optimization Coverage Algorithm Based on Sensor Cloud Systems in Intelligent Computing

Sun

2020

IEEE Access

View full text Add to dashboard Cite

the coverage of traditional Wireless Sensor Networks (WSNs) is limited by node energy and data redundancy, which forces WSNs to be interrupted abnormally. Therefore, Cooperative-optimization Coverage Algorithm based on Sensor Cloud Systems in Intelligent Computing (CoC-SCS) is proposed. First, the algorithm determines the location information of the Focus Target Nodes (FTNs), and uses the Genetic Algorithm (GA) to give the node path planning. Second, the mutation parameters and the controllable threshold parameters are used in order to control the event domain nodes. Optimizing clustering makes the clustering of the nodes to be more uniform, so that it can improve the search ability of the global target nodes and even reduce the nodes energy consumption. Third, the adaptation function covers the continuity of the covered target positions and the monitoring range of the nodes. Optimization is also performed to achieve the goals of increasing network coverage and extending the network lifetime. Finally, simulation results show that the proposed CoC-SCS algorithm compared with other three algorithms in this paper has improved 11.27% and 16.35% on average in terms of network coverage, network lifetime, etc., and 13.95% in terms of network energy overhead, thereby we can further verify that CoC-SCS algorithm has strong stability and effectiveness.

show abstract

Section: A Coverage Problemmentioning

confidence: 99%

CoC-SCS: Cooperative-Optimization Coverage Algorithm Based on Sensor Cloud Systems in Intelligent Computing

Sun

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In the work of Yang and Wang, 16 an energy conserving compressive sensing technique was proposed for group sensor networks. This work presents the group measurement matrix and the size of CS measurements is predicted.…”

Section: Review Of Literaturementioning

confidence: 99%

Energy conserving texture‐based adaptable compressive sensing scheme for WVSN

Lakshmi¹,

Gnanadurai²,

Muthulakshmi

2019

Concurrency and Computation

View full text Add to dashboard Cite

Summary Wireless Sensor Networks (WSN) have gained considerable research interest due to its wider applicability and efficiency. Due to the technological advancement, the WSN is multifaceted and one of the facets is the Wireless Visual Sensor Network (WVSN). The core functionality of WVSN is to handle multimedia data that involves data processing and transference, which, in turn, consumes more energy. Data transference requires more energy and the energy consumption is reduced by the concept of compressive sensing. Understanding the benefits of compressive sensing, this article proposes an adaptable compressive scheme that relies on the texture property of the video frames. The texture property is extracted by means of Local Directional Pattern (LDP). The performance of the proposed approach is evaluated in terms of image quality, time, and energy consumption. The proposed approach outperforms the comparative approaches with reasonable performance.

show abstract

“…Other than these applications they are employed for measuring the positions of the body, tracking location of a person, entire observation of sick patients in hospitals and at home. The body area networks are used to gather information about a patient's health condition, strength and energy outlays [7,8].…”

Section: Introductionmentioning

confidence: 99%

Certain Investigation on Healthcare Monitoring for Enhancing Data Transmission in WSN

Durai

Duraisamy²,

Thirukrishna

2021

Int J Wireless Inf Networks

View full text Add to dashboard Cite

Wireless Sensor Networks are often to perform autonomous sensing and controlling the real world objects through the sensor nodes across the globe. Since these sensor nodes are operated by the energy of the battery that has been performed a vital role in deploying a sensor network. Hence, the battery power needs to be minimized to prolong network lifetime for healthcare applications. The monitored data transmission is very important to process in building wireless sensor networks. In order to provide efficient data transmission wireless technology standards are followed as IEEE 802.15.4 standards that provide desirable communication between end to end with optimal routes using the proposed Energy Optimization Algorithm. The proposed algorithm has been improved the data packet transmission efficiency up to 25% and also helps to prolong the life time of Wireless Sensor Networks in order to achieve the efficient data transmission for health care monitoring.

show abstract

ECO CS: Energy consumption optimized compressive sensing in group sensor networks

Cited by 7 publications

References 15 publications

CoC-SCS: Cooperative-Optimization Coverage Algorithm Based on Sensor Cloud Systems in Intelligent Computing

CoC-SCS: Cooperative-Optimization Coverage Algorithm Based on Sensor Cloud Systems in Intelligent Computing

Energy conserving texture‐based adaptable compressive sensing scheme for WVSN

Certain Investigation on Healthcare Monitoring for Enhancing Data Transmission in WSN

Contact Info

Product

Resources

About