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Optimizing Average AoI with Directional Charging for Wireless-Powered Network Edge | IEEE Conference Publication | IEEE Xplore

Optimizing Average AoI with Directional Charging for Wireless-Powered Network Edge


Abstract:

Age of Information, which emerged as a new performance metric to quantify the data freshness, has drawn increasing interests recently. At wireless-powered network edge, t...Show More

Abstract:

Age of Information, which emerged as a new performance metric to quantify the data freshness, has drawn increasing interests recently. At wireless-powered network edge, the source nodes can only transmit their updates after being charged ready, which means the system AoI is not only determined by the update transmission strategies, but also the charging strategies. However, the existing works either only focused on the point of scheduling of update transmissions or have a rigid assumption that only one source node can be charged per time. Aiming at making the work more practical and general, we investigate the average A oI optimization problem at wireless-powered network edge without such limitations in this paper. Firstly, the lower bound of the weighted sum of average A oI of the whole network with a directional charger is analyzed, which is proved to be related to nodes' maximum transmitting interval and the charging strategy. An optimal charging time allocation algorithm is proposed to obtain the maximum transmitting interval of each source node by considering the overlapped areas of different charging orientations. After then, an AoI-aware periodical charging scheduling algorithm is proposed, which can obtain a periodical charging schedule including a charging period T and the charging orientation assigned to each time slot within T, while the average AoI is bounded. The proposed algorithm is proved to have an approximation ratio of up to 1.5625. Finally, the extensive simulations demonstrate the high performance of the proposed algorithm in terms of AoI.
Date of Conference: 19-21 June 2023
Date Added to IEEE Xplore: 27 July 2023
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Conference Location: Orlando, FL, USA

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