Heuristic mobile data gathering for wireless sensor networks via trajectory control
This article focuses on the problem of scheduling the optimal paths of multiple mobile elements (e.g. robots, vehicles, etc.) to minimize the travel distance and balance the energy consumption and the data gathering latency in wireless sensor networks for smart cities. To partition the network for t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-05-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147720907052 |
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| _version_ | 1832556846298169344 |
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| author | Jianxin Ma Shuo Shi Xuemai Gu Fanggang Wang |
| author_facet | Jianxin Ma Shuo Shi Xuemai Gu Fanggang Wang |
| author_sort | Jianxin Ma |
| collection | DOAJ |
| description | This article focuses on the problem of scheduling the optimal paths of multiple mobile elements (e.g. robots, vehicles, etc.) to minimize the travel distance and balance the energy consumption and the data gathering latency in wireless sensor networks for smart cities. To partition the network for the multiple mobile elements and compute the trajectories of the multiple mobile elements, we utilize the sensor’s communication range and construct a multiple mobile elements scheduling problem. A heuristic mobile data gathering approach is proposed to solve this problem, which includes the following three steps. The sensor nodes are preliminarily partitioned into four levels, and then the clusterheads are further partitioned, and the traveling tour is scheduled for each cluster. After the first two steps, all the sensor nodes are partitioned reasonably for the multiple mobile elements. In the last step, the traveling tour is scheduled for each cluster, and the meeting point of each clusterhead is determined. We compare the proposed heuristic mobile data gathering with the existing approaches. The results indicate that the travel distance and the data gathering latency are reduced significantly, which further validates that the communication range is beneficial to minimize the travel distance. |
| format | Article |
| id | doaj-art-bb4866bce8a3473eac802b97add1246e |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2020-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-bb4866bce8a3473eac802b97add1246e2025-02-03T05:44:20ZengWileyInternational Journal of Distributed Sensor Networks1550-14772020-05-011610.1177/1550147720907052Heuristic mobile data gathering for wireless sensor networks via trajectory controlJianxin Ma0Shuo Shi1Xuemai Gu2Fanggang Wang3Department of Electrical and information Engineering, Harbin Institute of Technology, Harbin, ChinaDepartment of Electrical and information Engineering, Harbin Institute of Technology, Harbin, ChinaDepartment of Electrical and information Engineering, Harbin Institute of Technology, Harbin, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, ChinaThis article focuses on the problem of scheduling the optimal paths of multiple mobile elements (e.g. robots, vehicles, etc.) to minimize the travel distance and balance the energy consumption and the data gathering latency in wireless sensor networks for smart cities. To partition the network for the multiple mobile elements and compute the trajectories of the multiple mobile elements, we utilize the sensor’s communication range and construct a multiple mobile elements scheduling problem. A heuristic mobile data gathering approach is proposed to solve this problem, which includes the following three steps. The sensor nodes are preliminarily partitioned into four levels, and then the clusterheads are further partitioned, and the traveling tour is scheduled for each cluster. After the first two steps, all the sensor nodes are partitioned reasonably for the multiple mobile elements. In the last step, the traveling tour is scheduled for each cluster, and the meeting point of each clusterhead is determined. We compare the proposed heuristic mobile data gathering with the existing approaches. The results indicate that the travel distance and the data gathering latency are reduced significantly, which further validates that the communication range is beneficial to minimize the travel distance.https://doi.org/10.1177/1550147720907052 |
| spellingShingle | Jianxin Ma Shuo Shi Xuemai Gu Fanggang Wang Heuristic mobile data gathering for wireless sensor networks via trajectory control International Journal of Distributed Sensor Networks |
| title | Heuristic mobile data gathering for wireless sensor networks via trajectory control |
| title_full | Heuristic mobile data gathering for wireless sensor networks via trajectory control |
| title_fullStr | Heuristic mobile data gathering for wireless sensor networks via trajectory control |
| title_full_unstemmed | Heuristic mobile data gathering for wireless sensor networks via trajectory control |
| title_short | Heuristic mobile data gathering for wireless sensor networks via trajectory control |
| title_sort | heuristic mobile data gathering for wireless sensor networks via trajectory control |
| url | https://doi.org/10.1177/1550147720907052 |
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