IoT-D2D task allocation: an award-driven game theory approach - Archive ouverte HAL
Communication Dans Un Congrès Année : 2016

IoT-D2D task allocation: an award-driven game theory approach

Résumé

An IoT-D2D cooperation framework for task allocation among objects in the IoT (Internet of Things) is presented. Proximity Services based on Device to Device (D2D) communication are used to enable direct interaction between IoT objects. The process is triggered by a node that decides to set up a cluster of nodes and then to coordinate the allocation strategy, where objects capable of performing the same tasks compete to get relevant remunerations. We then propose a game-theory based approach to find a solution maximizing objects utility functions. We prove that a Nash Equilibrium Point (NEP) can be found. Experimental results provide insights on the strategy performance

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Dates et versions

hal-01370189 , version 1 (22-09-2016)

Identifiants

Citer

Emad Mohamed Abd Elrahman Abousabea, Hossam Afifi, Luigi Aztori, Makhlouf Hadji, Virginia Pilloni. IoT-D2D task allocation: an award-driven game theory approach. ICT 2016 : 23rd International Conference on Telecommunications, May 2016, Thessaloniki, Greece. pp.1 - 6, ⟨10.1109/ICT.2016.7500355⟩. ⟨hal-01370189⟩
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