This work focuses on the problem of task allocation among mobile objects that aim to collaborate in the execution of IoT (Internet of Things) applications. We consider 3GPP Proximity Services (ProSe) that enable Device to Device (D2D) communications for direct interaction among IoT objects. We first define the framework where devices willing to cooperate: (i) discover and join a cluster of objects to take part to the IoT_ProSe service; (ii) compete with the other objects in the cluster when a request for a service is sent to the cluster from the IoT application server. We then focus on two important problems. The first problem is the decision about which node should win the competition, for which we propose a game-theory based approach to find a solution maximizing objects’ utility functions. The second problem is the computation of the optimal size of devices’ clusters within a cell by maximizing the signal quality across the cell. Experimental results provide insights on the strategy performance. By appropriately setting working parameters, it is possible to improve system reliability up to 21%, and system lifetime up to 68%.

IoT_ProSe: Exploiting 3GPP services for task allocation in the Internet of Things

PILLONI, VIRGINIA;ATZORI, LUIGI;
2017-01-01

Abstract

This work focuses on the problem of task allocation among mobile objects that aim to collaborate in the execution of IoT (Internet of Things) applications. We consider 3GPP Proximity Services (ProSe) that enable Device to Device (D2D) communications for direct interaction among IoT objects. We first define the framework where devices willing to cooperate: (i) discover and join a cluster of objects to take part to the IoT_ProSe service; (ii) compete with the other objects in the cluster when a request for a service is sent to the cluster from the IoT application server. We then focus on two important problems. The first problem is the decision about which node should win the competition, for which we propose a game-theory based approach to find a solution maximizing objects’ utility functions. The second problem is the computation of the optimal size of devices’ clusters within a cell by maximizing the signal quality across the cell. Experimental results provide insights on the strategy performance. By appropriately setting working parameters, it is possible to improve system reliability up to 21%, and system lifetime up to 68%.
2017
D2D; Game theory; Internet of Things; Software; Hardware and Architecture; Computer Networks and Communications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/228244
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