Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network
In a wireless visual sensor network consisting of wireless, battery-powered, and field-of-view (FoV) overlapping and stationary visual sensors, trade-offs exist between extending network lifetime and enhancing its sensing accuracy. Moreover, aggregating individual inferences from each sensor is esse...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2014-06-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/839710 |
| _version_ | 1797706326476849152 |
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| author | Yeong-Jae Choi Go-Wun Jeong Yong-Ho Seo Hyun S. Yang |
| author_facet | Yeong-Jae Choi Go-Wun Jeong Yong-Ho Seo Hyun S. Yang |
| author_sort | Yeong-Jae Choi |
| collection | DOAJ |
| description | In a wireless visual sensor network consisting of wireless, battery-powered, and field-of-view (FoV) overlapping and stationary visual sensors, trade-offs exist between extending network lifetime and enhancing its sensing accuracy. Moreover, aggregating individual inferences from each sensor is essential to generate a globally consistent inference, because these individual inferences can be biased by noise or other unexpected conditions. Those challenges can be addressed by reducing the amount of data transmission among the sensors and by activating, in a timely manner, only a desirable camera subset for given targets. In this paper, we initialize an optimal data transmission path among visual sensors using the inference tree method, which is vital for collecting individual inferences and building a global inference. Based on the optimal data transmission path, we model the camera selection problem in a cooperative bargaining game. In this game, based on the serial dictatorial rule, camera sensors cooperatively attempt to raise the overall sensing accuracy by sequentially deciding their own mode between “sleep” and “active” in descending order of their bargaining power. Simulated results demonstrate that our proposed approach outperforms other alternatives, resulting in reduced resource overhead and improved network lifetime and sensing accuracy. |
| first_indexed | 2024-03-12T05:49:34Z |
| format | Article |
| id | doaj.art-71d19fa8c587460cab1090fe2720befa |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T05:49:34Z |
| publishDate | 2014-06-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-71d19fa8c587460cab1090fe2720befa2023-09-03T05:18:01ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-06-011010.1155/2014/839710839710Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor NetworkYeong-Jae Choi0Go-Wun Jeong1Yong-Ho Seo2Hyun S. Yang3 Department of Computer Science, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea Department of Computer Science, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea Department of Intelligent Robot Engineering, Mokwon University, 88 Doanbuk-ro, Seo-gu, Daejeon 302-729, Republic of Korea Department of Computer Science, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of KoreaIn a wireless visual sensor network consisting of wireless, battery-powered, and field-of-view (FoV) overlapping and stationary visual sensors, trade-offs exist between extending network lifetime and enhancing its sensing accuracy. Moreover, aggregating individual inferences from each sensor is essential to generate a globally consistent inference, because these individual inferences can be biased by noise or other unexpected conditions. Those challenges can be addressed by reducing the amount of data transmission among the sensors and by activating, in a timely manner, only a desirable camera subset for given targets. In this paper, we initialize an optimal data transmission path among visual sensors using the inference tree method, which is vital for collecting individual inferences and building a global inference. Based on the optimal data transmission path, we model the camera selection problem in a cooperative bargaining game. In this game, based on the serial dictatorial rule, camera sensors cooperatively attempt to raise the overall sensing accuracy by sequentially deciding their own mode between “sleep” and “active” in descending order of their bargaining power. Simulated results demonstrate that our proposed approach outperforms other alternatives, resulting in reduced resource overhead and improved network lifetime and sensing accuracy.https://doi.org/10.1155/2014/839710 |
| spellingShingle | Yeong-Jae Choi Go-Wun Jeong Yong-Ho Seo Hyun S. Yang Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network International Journal of Distributed Sensor Networks |
| title | Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network |
| title_full | Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network |
| title_fullStr | Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network |
| title_full_unstemmed | Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network |
| title_short | Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network |
| title_sort | game theoretic camera selection using inference tree method for a wireless visual sensor network |
| url | https://doi.org/10.1155/2014/839710 |
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