Optimum Multicast Scheduling in Delay-Constrained Content-Centric Wireless Networks | IEEE Conference Publication | IEEE Xplore

Optimum Multicast Scheduling in Delay-Constrained Content-Centric Wireless Networks


Abstract:

In this paper, we study the optimum multicast scheduling of cache-enabled content-centric wireless networks, where multiple users requesting multiple contents with differ...Show More

Abstract:

In this paper, we study the optimum multicast scheduling of cache-enabled content-centric wireless networks, where multiple users requesting multiple contents with different quality of service (QoS) constraints. The QoS of a content is measured by using the worst-case delay between a request and transmission. Each content is assigned a unique delay threshold based on its delay tolerance. To ensure the timely delivery of the contents, a large delay penalty is imposed if the worst case delay for a content exceeds its delay threshold. In case two or more contents reach their respective delay thresholds simultaneously, the content with a higher priory is assigned a larger penalty in the cost function to prioritize its transmission. Delaying the transmission of a content can potentially increase the number of requests served by a single transmission, given that more requests for the same content might arrive during the waiting period, thus reducing the average power consumption per request. The objective of this paper is to identify the optimum multicast scheduling policy that can jointly minimize the weighted combination of average power, delay penalty, and the fetching cost associated with fetching uncached contents from a remote server. The problem is formulated as an infinite horizon average cost Markov decision process (MDP), and it is optimally solved by applying the relative value iteration algorithm. Simulation results demonstrate that the proposed multicast scheduling outperforms existing scheduling algorithms, and it can achieve flexible tradeoff between power and delay in a multicast system by adjusting the weight coefficient in the cost function.
Date of Conference: 20-24 May 2019
Date Added to IEEE Xplore: 15 July 2019
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Conference Location: Shanghai, China

References

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