Stability of Game-Theoretic Energy-Aware MAC Scheme for Wireless Sensor Networks

Park, Jin Kyung; Ha, Jun; Seo, Heewon; Kim, Joonmo; Choi, Cheon Won

doi:10.1109/sutc.2010.23

Cited by 4 publications

(9 citation statements)

References 18 publications

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“…We can infer from the presented proposals and Table 3, that game theory has been applied to address the energy efficiency in different MAC schemes, scheduling based [50,51], contention based [49], and mixed (scheduling and contention based) [48]. Although the number of proposals in this domain is limited, we believe that they are sufficient to break the ice in this domain.…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

“…Correlated equilibrium requires joint computation of strategies. In general, it is easier to computer those joint [21], [24], [25], [26], [28], [76],[100], [115], [139] Repeated game [21], [48], [50], [68], [96], [97], [98],[100],[105], [125], [157] Incomplete information [21], [23], [69], [105], [113], [114], [136], [153], [154], [156] Bayesian NE [23], [68], [113], [117] Dynamic game [66], [69], [76], [113] Static game [113] Mixed strategy NE [49], [55], [57], [69], [136], [138], [139], [157] Pure strategy NE [22], [76], [79], [125] Potential game [28],…”

Section: Cooperation Enforcement Gamesmentioning

confidence: 99%

“…In [49], a MAC scheme based on p-persistent slotted ALOHA and constructed a simple non-cooperative 760 game is proposed in order to determine the value of the channel attempt probability p. Firstly, general- history-based estimation, infinitely repeated adjusting the transmission probability and the sleeping time of a node according to the number of its opponents [49] 2010 Non-cooperative contention based mixed strategy NE optimizing the channel attempt probability taking energy consumption into account [50] 2013 Non-cooperative scheduling based NE, repeated game optimizing the sleep interval between consecutive wake-ups (duty cycle control) [51] 2007 Cooperative scheduling based NE, Pareto optimality, bargaining game determining the optimal sleep and wakeup probabilities ized payoffs were designed to reflect the costs of energy consumption and throughput deterioration. Next, NE is found in a closed form.…”

Section: Non-cooperative Gamesmentioning

confidence: 99%

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Game theory for energy efficiency in Wireless Sensor Networks: Latest trends

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Section: Discussion and Future Directionsmentioning

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Section: Cooperation Enforcement Gamesmentioning

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Game theory for energy efficiency in Wireless Sensor Networks: Latest trends

AlSkaif

Zapata

Bellalta

2015

Journal of Network and Computer Applications

125

View full text Add to dashboard Cite

“…In practice, the Game-theoretical Total Link (GTL) algorithm which sets each node's energy range is usually better than Critical Transmitting Range (CTR) in energy saving according to the topological changing, as shown by Zhang et al [ 122 ]. Kyung et al [ 123 ] considered a MAC scheme based on p -persistence slotted ALOHA. To determine the value of the attempt probability p , the authors constructed the p -persistence slotted ALOHA as a simple non-cooperative game which involves generalized payoffs reflecting energy saving and throughput.…”

Section: Applications Of Game Theory In Wsnmentioning

confidence: 99%

Game Theory for Wireless Sensor Networks: A Survey

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Wang

Kwok

et al. 2012

Sensors

211

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Game theory (GT) is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs). This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field.

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“…It is employed in economics, biology, and computer science [19,20,21,22,23,24]. Game theory helps to achieve an optimized decision and, therefore, it is used in various applications involving decision-making in the field of computer science [19,21,23,25,26,27]. Accordingly, game theoretical methods can be used in IoT environments to determine the optimal decision for different requirements.…”

Section: Introductionmentioning

confidence: 99%

Self-Adaptive Framework Based on MAPE Loop for Internet of Things

Lee

Seo

Kim

2019

Sensors

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The Internet of Things (IoT) connects a wide range of objects and the types of environments in which IoT can be deployed dynamically change. Therefore, these environments can be modified dynamically at runtime considering the emergence of other requirements. Self-adaptive software alters its behavior to satisfy the requirements in a dynamic environment. In this context, the concept of self-adaptive software is suitable for some dynamic IoT environments (e.g., smart greenhouses, smart homes, and reality applications). In this study, we propose a self-adaptive framework for decision-making in an IoT environment at runtime. The framework comprises a finite-state machine model design and a game theoretic decision-making method for extracting efficient strategies. The framework was implemented as a prototype and experiments were conducted to evaluate its runtime performance. The results demonstrate that the proposed framework can be applied to IoT environments at runtime. In addition, a smart greenhouse-based use case is included to illustrate the usability of the proposed framework.

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Stability of Game-Theoretic Energy-Aware MAC Scheme for Wireless Sensor Networks

Cited by 4 publications

References 18 publications

Game theory for energy efficiency in Wireless Sensor Networks: Latest trends

Game theory for energy efficiency in Wireless Sensor Networks: Latest trends

Game Theory for Wireless Sensor Networks: A Survey

Self-Adaptive Framework Based on MAPE Loop for Internet of Things

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