Reward Maximization Strategy in Virtualized Wireless Sensor Networks

Ailing Zhong, Zhidu Li, Dapeng Wu, Ruyan Wang, Alexander A. Fedotov, Vladimir Lvovich Badenko · 2020

Virtualized wireless sensor network (WSN) will play an important role in Internet of Everything for the future 6G networks. This paper studies the task allocation strategy to maximize the reward for the operator. Firstly, a novel virtualized supplier-operator-buyer WSN framework is constructed, based on which the application service delay and reward model are studied. Then a dynamic reward optimization problem is formulated for the network operator. Furthermore, we optimize the task allocation from both short-term and long-term perspectives. In particular, an activation factor is introduced in the long-term optimal strategy to control the energy efficiency of the sensors beyond a reasonable level. Simulation results validate that a suitable activation factor can improve the accumulated reward for the operator significantly. The analysis in this paper sheds new insight of task allocation in a virtualized WSN.

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