Cache-Assisted Content Delivery in Wireless Networks: A New Game Theoretic Model

Liu, Changtong; Wang, Zhuwei; Sun, Yang; Ni, Wei; Guo, Song

doi:10.1109/jsyst.2020.3001229

Cited by 11 publications

(2 citation statements)

References 48 publications

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“…( 21), which operate under the limited 3C resources capacities by using optimal and least recently used (LRU) caching policies while considering request aggregation. "OPT without Cache and Aggregation" indicates that the existing cloud-edge cooperation scheme does not consider the deployment of caching resource and request aggregation policies, while request aggregation is adopted in "OPT without Cache" [3,33]. The advantages of in-network caching and aggregation have been discussed in Section II-A.…”

Section: Simulation and Resultsmentioning

confidence: 99%

Energy-Efficient Hierarchical Collaborative Scheme for Content Delivery in Mobile Edge Computing

Huang

Huang²,

et al. 2022

Wireless Communications and Mobile Computing

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With the rapid growth of Internet traffic and smart mobile terminals, ultradense networks are adopted as the key technology of the fifth generation to enhance resource utilization and content distribution while causing serious energy efficiency problem. Mobile edge computing has recently drawn great attention for its advantages in reducing transmission delay and network energy consumption by implementing caching and computing abilities at the edge of mobile networks. To improve network energy efficiency and content transmission, in this paper, we propose a novel energy-efficient hierarchical collaborative scheme by considering the in-network caching, request aggregation, and joint allocation of caching, computing, and communication resources in a layered heterogeneous network including mobile users, small base stations, macro base stations, and the cloud. We formulate the energy consumption problem as a queuing theory-based centralized model, where the same content requests can be aggregated in the queue of each base station. Then, the optimal solution is analyzed based on the distribution characteristic of content popularity at the base stations. Simulation results show that the performance of our proposed model is much better than the existing cloud-edge cooperation solutions without considering the deployment of caching resource and request aggregation policies.

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Section: Simulation and Resultsmentioning

confidence: 99%

Energy-Efficient Hierarchical Collaborative Scheme for Content Delivery in Mobile Edge Computing

Huang

Huang²,

et al. 2022

Wireless Communications and Mobile Computing

Self Cite

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“…Accordingly, F = 10 input files are considered, with the input size l f m (in bits) ranging from l min = 1 × 10 6 , l max = 20 × 10 6 . Specifically, the input size of r m with input file f takes the value of l f m = l min + ( f − 1) l max −l min F following uniform distribution, Zipf distribution [41,42] (skewness factor α = 1) prioritizing small loads and Zipf distribution prioritizing large loads. The computation load (L m ) of each task ranges from L min = 0.5 × 10 8 , L max = 4 × 10 8 (in CPU cycles) and computation load of r m with input file f takes a value of…”

Section: Simulation Settingmentioning

confidence: 99%

Water Pumping and Refilling (WPR): A Resource Allocation Algorithm for Maximizing Acceptance Ratio in Asymmetrical Edge Computing Networks

Liu

2023

Symmetry

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Computation offloading has received a significant amount of attention in recent years, with many researchers proposing joint offloading decision and resource allocation schemes. However, although existing delay minimization schemes achieve minimum delay costs, they do so at the cost of losing possible further maximization of the number of serviced requests. Furthermore, the asymmetry between uplink and downlink poses challenges to resource allocation in edge computing. This paper addresses this issue by formulating the joint computation offloading and edge resource allocation problem as a mixed-integer nonlinear programming (MINLP) problem in an edge-enabled asymmetrical network. Leveraging the margin between a delay-minimum scheme and a near-deadline scheme, a water pumping and refilling (WPR) algorithm is proposed to maximize the number of accepted requests. The WPR algorithm can function both as a supplementary algorithm to a given offloading scheme and as a standalone algorithm to obtain a resource allocation scheme following a customizable refilling policy. The simulation results demonstrated that the proposed algorithm outperforms delay-minimum schemes in achieving a high acceptance ratio.

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A remote sensing data transmission strategy based on the combination of satellite-ground link and GEO relay under dynamic topology

Chen

et al. 2023

Future Generation Computer Systems

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Cache-Assisted Content Delivery in Wireless Networks: A New Game Theoretic Model

Cited by 11 publications

References 48 publications

Energy-Efficient Hierarchical Collaborative Scheme for Content Delivery in Mobile Edge Computing

Energy-Efficient Hierarchical Collaborative Scheme for Content Delivery in Mobile Edge Computing

Water Pumping and Refilling (WPR): A Resource Allocation Algorithm for Maximizing Acceptance Ratio in Asymmetrical Edge Computing Networks

A remote sensing data transmission strategy based on the combination of satellite-ground link and GEO relay under dynamic topology

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