Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks
Biological sensors are a very promising technology that will take healthcare to the next level. However, there are obstacles that must be overcome before the full potential of this technology can be realized. One such obstacle is that the heat generated by biological sensors implanted into a human b...
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| Format: | Article |
| Language: | English |
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Wiley
2013-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2013/794920 |
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| author | Yahya Osais F. Richard Yu Marc St-Hilaire |
| author_facet | Yahya Osais F. Richard Yu Marc St-Hilaire |
| author_sort | Yahya Osais |
| collection | DOAJ |
| description | Biological sensors are a very promising technology that will take healthcare to the next level. However, there are obstacles that must be overcome before the full potential of this technology can be realized. One such obstacle is that the heat generated by biological sensors implanted into a human body might damage the tissues around them. Dynamic sensor scheduling is one way to manage and evenly distribute the generated heat. In this paper, the dynamic sensor scheduling problem is formulated as a Markov decision process (MDP). Unlike previous works, the temperature increase in the tissues caused by the generated heat is incorporated into the model. The solution of the model gives an optimal policy that when executed will result in the maximum possible network lifetime under a constraint on the maximum temperature level tolerable by the patient's body. In order to obtain the optimal policy in a lesser amount of time, two specific types of states are aggregated to produce a considerably smaller MDP model equivalent to the original one. Numerical and simulation results are presented to show the validity of the model and superiority of the optimal policy produced by it when compared with two policies one of which is specifically designed for biological wireless sensor networks. |
| format | Article |
| id | doaj-art-7b87412502cd4feb831cccda79d0f7b5 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2013-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-7b87412502cd4feb831cccda79d0f7b52025-02-03T01:30:50ZengWileyInternational Journal of Distributed Sensor Networks1550-14772013-04-01910.1155/2013/794920Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor NetworksYahya Osais0F. Richard Yu1Marc St-Hilaire2 Department of Computer Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada K1S 5B6 Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada K1S 5B6Biological sensors are a very promising technology that will take healthcare to the next level. However, there are obstacles that must be overcome before the full potential of this technology can be realized. One such obstacle is that the heat generated by biological sensors implanted into a human body might damage the tissues around them. Dynamic sensor scheduling is one way to manage and evenly distribute the generated heat. In this paper, the dynamic sensor scheduling problem is formulated as a Markov decision process (MDP). Unlike previous works, the temperature increase in the tissues caused by the generated heat is incorporated into the model. The solution of the model gives an optimal policy that when executed will result in the maximum possible network lifetime under a constraint on the maximum temperature level tolerable by the patient's body. In order to obtain the optimal policy in a lesser amount of time, two specific types of states are aggregated to produce a considerably smaller MDP model equivalent to the original one. Numerical and simulation results are presented to show the validity of the model and superiority of the optimal policy produced by it when compared with two policies one of which is specifically designed for biological wireless sensor networks.https://doi.org/10.1155/2013/794920 |
| spellingShingle | Yahya Osais F. Richard Yu Marc St-Hilaire Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks |
| title_full | Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks |
| title_fullStr | Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks |
| title_full_unstemmed | Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks |
| title_short | Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks |
| title_sort | dynamic sensor scheduling for thermal management in biological wireless sensor networks |
| url | https://doi.org/10.1155/2013/794920 |
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