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Backhaul-Aware Storage Allocation and Pricing Mechanism for RSU-Based Caching Networks

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Remarkable prevalence of in-car entertainment systems empowers vehicular users to download multimedia-enabled contents in transit and creates a new business opportunity for content providers (CPs). However, the timely delivery of… Click to show full abstract

Remarkable prevalence of in-car entertainment systems empowers vehicular users to download multimedia-enabled contents in transit and creates a new business opportunity for content providers (CPs). However, the timely delivery of requested content is a major concern for CPs to improve the quality of service (QoS) of their subscribe users. Roadside unit (RSU)-based caching appears as a promising solution for CPs wherein CPs proactively store their content at the RSU to reduce the content delivery time. Since the RSUs are enabled with limited storage capacity, the competition among multiple CPs for storage space is unavoidable. Further, the CPs are connected with RSUs using capacity limited backhaul links. Hence the allocation of RSUs’ storage among CPs becomes a fundamental issue in RSU-based caching networks. In this paper, we design a market scenario in which the set of CPs competes for the storage space of RSUs. In the unavailability of utility and cost functions of the CPs and the RSUs, we introduce a market maker to manage the marketplace. Further, we employ iteration-based double-sided auction mechanism to compute the optimal storage allocation and corresponding payment transfer for CPs which maximizes the social welfare of the networks. The simulation results demonstrate the proposed auction mechanism improves the social welfare of the network by at least 29.3% compared to the benchmark schemes. Further, with the help of both analytical and numerical analysis, we show that the proposed auction mechanism also holds vital economical properties.

Keywords: based caching; storage; rsu based; mechanism; cps

Journal Title: IEEE Transactions on Wireless Communications
Year Published: 2022

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