Bibliographic Details
| Title: |
An Event-Driven Mechanism Coverage Algorithm Based on Sensing-Cloud-Computing in Sensor Networks |
| Authors: |
Zeyu Sun, Lili Wei, Chen Xu, Zhiguo Lv |
| Source: |
IEEE Access, Vol 7, Pp 84668-84679 (2019) |
| Publisher Information: |
IEEE, 2019. |
| Publication Year: |
2019 |
| Collection: |
LCC:Electrical engineering. Electronics. Nuclear engineering |
| Subject Terms: |
Sensing-cloud-computing, sensor network, coverage rate, network lifetime, Electrical engineering. Electronics. Nuclear engineering, TK1-9971 |
| More Details: |
The structure of network topology in heterogeneous sensor networks changes fast. As a result, the coverage and control ability of sensor nodes will be undermined. In order that we can address this problem, we propose an event-driven mechanism coverage algorithm based on Sensing-cloud-computing in heterogeneous sensor networks (EMC-SC). First, the network coverage model is utilized to compute the boundary relationship between the dual square and the sensor nodes coverage area. Then, the Poisson distribution model is employed to analyze the coverage performance of the randomly deployed sensor nodes and further compute the probability of the coverage which is effective over the monitoring area. Next, the node state mechanism scheduling algorithm is determined according to the amount of exchanged information between the neighbor nodes and the sensor nodes as well as the remaining sensor nodes energy. Finally, the results of the simulation show that, if it is compared with other algorithms which exist, the EMC-SC algorithm which is proposed could improve the network lifetime and the network coverage rate by 12.73% and 16.22%, respectively. Therefore, the effectiveness of the proposed algorithm and the validity of the proposed algorithm are verified. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2169-3536 |
| Relation: |
https://ieeexplore.ieee.org/document/8746129/; https://doaj.org/toc/2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2925119 |
| Access URL: |
https://doaj.org/article/bc0db5ae97be40a89d8b77acae467854 |
| Accession Number: |
edsdoj.bc0db5ae97be40a89d8b77acae467854 |
| Database: |
Directory of Open Access Journals |
