5G Network Communication, Caching, and Computing Algorithms Based on the Two-Tier Game Model

Kim, Sung-Wook

doi:10.4218/etrij.2017-0023

Cited by 20 publications

(18 citation statements)

References 22 publications

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“…[20] extends the results in [19] to a big data MEC network. [21] proposes hybrid control algorithms in smart base stations along with devised communication, caching, and computing techniques based on game theory. However, the joint caching and computing designs developed in [19]- [21] do not exploit specific nature of VR delivery and look deeper into the VR delivery framework, and thus the performances are limited.…”

Section: Related Workmentioning

confidence: 99%

Communications, Caching, and Computing for Mobile Virtual Reality: Modeling and Tradeoff

Sun

Chen

Tao

et al. 2019

IEEE Trans. Commun.

181

109

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Virtual reality (VR) over wireless is emerging as an important use case of 5G networks. Immersive VR experience requires the delivery of huge data at ultra-low latency, thus demanding ultra-high transmission rate. This challenge can be largely addressed by the recent network architecture known as mobile edge computing (MEC), which enables caching and computing capabilities at the edge of wireless networks. This paper presents a novel MEC-based mobile VR delivery framework that is able to cache parts of the field of views (FOVs) in advance and run certain post-processing procedures at the mobile VR device. To optimize resource allocation at the mobile VR device, we formulate a joint caching and computing decision problem to minimize the average required transmission rate while meeting a given latency constraint. When FOVs are homogeneous, we obtain a closed-form expression for the optimal joint policy which reveals interesting communicationscaching-computing tradeoffs. When FOVs are heterogeneous, we obtain a local optima of the problem by transforming it into a linearly constrained indefinite quadratic problem then applying concave convex procedure. Numerical results demonstrate great promises of the proposed mobile VR delivery framework in saving communication bandwidth while meeting low latency requirement.

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Section: Related Workmentioning

confidence: 99%

Communications, Caching, and Computing for Mobile Virtual Reality: Modeling and Tradeoff

Sun

Chen

Tao

et al. 2019

IEEE Trans. Commun.

181

109

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“…Due to the desirable features of cooperative game theory, we can get a fair-efficient SHG traffic control solution through our proposed approach. In our previous researches [14]- [15], we also adopt different bargaining solutions to develop novel dual-level game models. The main merit possessed by our two-level game approach is to shed light on the practical control problem while providing excellent adaptability and flexibility to satisfy the different application requirements.…”

Section: Related Workmentioning

confidence: 99%

Home Network Traffic Control Scheme Based on Two-Level Bargaining Game Model

Kim

2021

IEEE Access

Self Cite

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This article presents a new smart home network (SHN) traffic control scheme to adaptively handle different quality of service (QoS) traffic services. According to their special characteristics, we categorize the SHN traffic services into three classes -class I, II and III data services -to share the limited SHN bandwidth resource. To effectively share the limited resource, we adopt the bridging and iterated egalitarian bargaining solutions, and formulate a two-level cooperative bargaining game. At the over bargaining process, the idea of bridging bargaining solution is used to compromise the conflicting views of real-time and non real-time data services. At the under bargaining process, class I and class II data services share the assigned bandwidth based on the concept of iterated egalitarian bargaining solution. These both processes are implemented to take full advantages of collaborative SHN traffic services. This interactive coordinated paradigm explores the mutual benefits under dynamically changing SHN environments. The most important novelties of our two-level bargaining approach is to compromise diverse QoS requirements while leveraging a reciprocal consensus among different traffic services. In a coordinated manner, we can get a globally desirable solution to challenge the relatively fair-efficient gains. Finally, simulation testbed is constructed and the numerical analysis is conducted to demonstrate the performance improvement of our proposed method. INDEX TERMSSmart home network, Smart home gateway, Cooperative bargaining game theory, Bridging bargaining, Iterated egalitarian bargaining.

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“…Then, drop the constant 1/N in (28) and we obtain the partial augmented Lagrangian of Problem 8 via moving the consensus constraint (32) to the objective function of Problem 8 as follows:…”

Section: B Optimal Policy Design For α >mentioning

confidence: 99%

Bandwidth Gain From Mobile Edge Computing and Caching in Wireless Multicast Systems

Sun

Chen

Tao

et al. 2020

IEEE Trans. Wireless Commun.

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In this paper, we present a novel mobile edge computing (MEC) model where the MEC server has the input and output data of all computation tasks and communicates with multiple caching-and-computing-enabled mobile devices via a shared wireless link. Each task request can be served from local output caching, local computing with input caching, local computing or MEC computing, each of which incurs a unique bandwidth requirement of the multicast link. Aiming to minimize the transmission bandwidth, we design and optimize the local caching and computing policy at mobile devices subject to latency, caching, energy and multicast transmission constraints. The joint policy optimization problem is shown to be NP-hard. When the output data size is smaller than the input data size, we reformulate the problem as minimization of a monotone submodular function over matroid constraints and obtain the optimal solution via a strongly polynomial algorithm of Schrijver. On the other hand, when the output data size is larger than the input data size, by leveraging sample approximation and concave convex procedure together with the alternating direction method of multipliers, we propose a lowcomplexity high-performance algorithm and prove it converges to a stationary point. Furthermore, we theoretically reveal how much bandwidth gain can be achieved from computing and caching resources at mobile devices or the multicast transmission for symmetric case. Our results indicate that exploiting the computing and caching resources at mobile devices as well as multicast transmission can provide significant bandwidth savings.

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5G Network Communication, Caching, and Computing Algorithms Based on the Two-Tier Game Model

Cited by 20 publications

References 22 publications

Communications, Caching, and Computing for Mobile Virtual Reality: Modeling and Tradeoff

Communications, Caching, and Computing for Mobile Virtual Reality: Modeling and Tradeoff

Home Network Traffic Control Scheme Based on Two-Level Bargaining Game Model

Bandwidth Gain From Mobile Edge Computing and Caching in Wireless Multicast Systems

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