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Abstract
How to guarantee the data rate and latency requirement for an application with limited energy is an open issue in wireless virtualized sensor networks. In this paper, we integrate the wireless energy transfer technology into the wireless virtualized sensor network and focus on the stochastic performance guarantee. Firstly, a joint task and resource allocation optimization problem are formulated. In order to characterize the stochastic latency of data transmission, effective capacity theory is resorted to study the relationship between network latency violation probability and the transmission capability of each node. The performance under the FDMA mode and that under the TDMA mode are first proved to be identical. We then propose a bisection search approach to ascertain the optimal task allocation with the objective to minimize the application latency violation probability. Furthermore, a one-dimensional searching scheme is proposed to find out the optimal energy harvesting time in each time block. The effectiveness of the proposed scheme is finally validated by extensive numerical simulations. Particularly, the proposed scheme is able to lower the latency violation probability by 11.6 times and 4600 times while comparing with the proportional task allocation scheme and the equal task allocation scheme, respectively.
Highlights
The rapid evolution of communication and intelligent technologies is inviting all human beings to the era of the Internet of everything, where unprecedented changes will have a profound impact on every single aspect of our daily interactions [1,2,3,4]
An exponentially increasing amount of data is needed to be sensed from different areas, which brings a large burden to the wireless sensor networks (WSNs)
Based on the proposed architecture, we prove that the FDMA mode can guarantee identical latency performance to the TDMA mode, when each node is allocated equal frequency resource or time resource
Summary
The rapid evolution of communication and intelligent technologies is inviting all human beings to the era of the Internet of everything, where unprecedented changes will have a profound impact on every single aspect of our daily interactions [1,2,3,4]. An exponentially increasing amount of data is needed to be sensed from different areas, which brings a large burden to the wireless sensor networks (WSNs). In this sense, virtualized WSN is proposed to manage the WSNs from different operators centrally with the objective of resource utilization improvement [5]. Similar to the traditional WSNs, energy is one of the key factors bring performance bottlenecks to the virtualized WSNs. In addition to tag identification [6], radio frequency (RF) energy has been considered to be a stable energy source for wireless sensors. Wireless powered communication has attracted attention from both academia and industria [7,8]
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