Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach
We model a wireless sensors’ connectivity scenario mathematically and analyze it using capacity provision mechanisms, with the objective of maximizing the profits of a network operator. The scenario has several sensors’ clusters with each one having one sink node, which uploads the sensing data gath...
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| Format: | Article |
| Language: | English |
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Wiley
2018-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718772544 |
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| author | Angel Sanchis-Cano Luis Guijarro Massimo Condoluci |
| author_facet | Angel Sanchis-Cano Luis Guijarro Massimo Condoluci |
| author_sort | Angel Sanchis-Cano |
| collection | DOAJ |
| description | We model a wireless sensors’ connectivity scenario mathematically and analyze it using capacity provision mechanisms, with the objective of maximizing the profits of a network operator. The scenario has several sensors’ clusters with each one having one sink node, which uploads the sensing data gathered in the cluster through the wireless connectivity of a network operator. The scenario is analyzed both as a static game and as a dynamic game, each one with two stages, using game theory. The sinks’ behavior is characterized with a utility function related to the mean service time and the price paid to the operator for the service. The objective of the operator is to maximize its profits by optimizing the network capacity. In the static game, the sinks’ subscription decision is modeled using a population game. In the dynamic game, the sinks’ behavior is modeled using an evolutionary game and the replicator dynamic, while the operator optimal capacity is obtained solving an optimal control problem. The scenario is shown feasible from an economic point of view. In addition, the dynamic capacity provision optimization is shown as a valid mechanism for maximizing the operator profits, as well as a useful tool to analyze evolving scenarios. Finally, the dynamic analysis opens the possibility to study more complex scenarios using the differential game extension. |
| format | Article |
| id | doaj-art-8656d16e283e41e7924c8c4267d9e31f |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2018-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-8656d16e283e41e7924c8c4267d9e31f2025-08-20T03:37:54ZengWileyInternational Journal of Distributed Sensor Networks1550-14772018-04-011410.1177/1550147718772544Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approachAngel Sanchis-Cano0Luis Guijarro1Massimo Condoluci2Department of Informatics, King’s College London, London, UKITACA, Universitat Politècnica de València, Valencia, SpainDepartment of Informatics, King’s College London, London, UKWe model a wireless sensors’ connectivity scenario mathematically and analyze it using capacity provision mechanisms, with the objective of maximizing the profits of a network operator. The scenario has several sensors’ clusters with each one having one sink node, which uploads the sensing data gathered in the cluster through the wireless connectivity of a network operator. The scenario is analyzed both as a static game and as a dynamic game, each one with two stages, using game theory. The sinks’ behavior is characterized with a utility function related to the mean service time and the price paid to the operator for the service. The objective of the operator is to maximize its profits by optimizing the network capacity. In the static game, the sinks’ subscription decision is modeled using a population game. In the dynamic game, the sinks’ behavior is modeled using an evolutionary game and the replicator dynamic, while the operator optimal capacity is obtained solving an optimal control problem. The scenario is shown feasible from an economic point of view. In addition, the dynamic capacity provision optimization is shown as a valid mechanism for maximizing the operator profits, as well as a useful tool to analyze evolving scenarios. Finally, the dynamic analysis opens the possibility to study more complex scenarios using the differential game extension.https://doi.org/10.1177/1550147718772544 |
| spellingShingle | Angel Sanchis-Cano Luis Guijarro Massimo Condoluci Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach International Journal of Distributed Sensor Networks |
| title | Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach |
| title_full | Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach |
| title_fullStr | Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach |
| title_full_unstemmed | Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach |
| title_short | Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach |
| title_sort | dynamic capacity provision for wireless sensors connectivity a profit optimization approach |
| url | https://doi.org/10.1177/1550147718772544 |
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