Joint design of device to device caching strategy and incentive scheme in mobile edge networks

Wang, Shuo; Zhang, Xing; Wang, Lin; Yang, Juwo; Wang, Wenbo

doi:10.1049/iet-com.2017.1044

Cited by 15 publications

(15 citation statements)

References 21 publications

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“…Taking UE heterogeneity into account, a joint design of a D2D caching strategy and incentive scheme in MEC networks is presented in [199] to maximize the BS utility and to improve the social welfare of the cellular network. The optimization problem includes two subproblems: caching and contract design.…”

Section: ) Content Deliverymentioning

confidence: 99%

“…To achieve the optimal caching strategy, a heuristic algorithm based on the gradient projection method is proposed. The type of UEs is considered to follow a uniform distribution in [199]; however, the UE type distribution may change based on network or device conditions in a real network environment. The simple scenario considering only one BS is also a shortcoming of this study.…”

Section: ) Content Deliverymentioning

confidence: 99%

“…In the caching context, the Zipf distribution is widely used to model the UE request pattern [209], [210], [220]. With the emergence of the ''Big Data'' concept, the actual content popularity matrix for a particular network could be obtained from wireless big data analyses at the MEC using ML algorithms [199]. Thus, the obtained actual content popularity matrix could potentially improve the caching performance of device-enhanced MEC.…”

Section: ) Learning Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

et al. 2019

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Multi-access edge computing (MEC) has recently been proposed to aid mobile end devices in providing compute-and data-intensive services with low latency. Growing service demands by the end devices may overwhelm MEC installations, while cost constraints limit the increases of the installed MEC computing and data storage capacities. At the same time, the ever increasing computation capabilities and storage capacities of mobile end devices are valuable resources that can be utilized to enhance the MEC. This article comprehensively surveys the topic area of device-enhanced MEC, i.e., mechanisms that jointly utilize the resources of the community of end devices and the installed MEC to provide services to end devices. We classify the device-enhanced MEC mechanisms into mechanisms for computation offloading and mechanisms for caching. We further subclassify the offloading and caching mechanisms according to the targeted performance goals, which include throughput maximization, latency minimization, energy conservation, utility maximization, and enhanced security. We identify the main limitations of the existing device-enhanced MEC mechanisms and outline future research directions. INDEX TERMS Caching, computation offloading, device-to-device (D2D) communication, mobile edge computing (MEC). I. INTRODUCTION A. MOTIVATION

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Section: ) Content Deliverymentioning

confidence: 99%

Section: ) Content Deliverymentioning

confidence: 99%

Section: ) Learning Algorithmsmentioning

confidence: 99%

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Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

et al. 2019

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“…However, the mobile subscribers hesitate to participate in D2D caching because of limited battery capacity and incurred energy consumption [170], [171]. Therefore, in recent studies [169]- [172], incentive designs for the participating mobile users have been introduced.…”

Section: Energy-aware Caching Resource Managementmentioning

confidence: 99%

A Review on Green Caching Strategies for Next Generation Communication Networks

et al. 2020

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In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching.

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“…To tackle these problems, mobile edge networks have been proposed to take advantage of the edge caching resources in networks and reduce the distance between contents and UEs [8,9]. Edge caching and content delivery *Correspondence: luweid@zjut.edu.cn 1 College of Information Engineering, Zhejiang University of Technology, Liuhe Road, Hangzhou 310023, China Full list of author information is available at the end of the article are key techniques for a content-centric network [10]. Traditionally, for a cellular network, a user's content request is served by servers located far away from the UE.…”

Section: Introductionmentioning

confidence: 99%

Edge caching strategy design and reward contract optimization for uAV-enabled mobile edge networks

Yin

Huang

et al. 2020

J Wireless Com Network

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Edge caching is a promising technology to alleviate the burden on backhaul and improve the quality of experience (QoE) of users in unmanned aerial vehicle (UAV)-enabled mobile edge networks, which has played an important role in wireless communication systems. However, owing to the selfish nature and limited battery life of the user equipments (UEs), only a limited part of the caching resources will be shared by the UEs. To drive the UEs to share more caching resources to improve the social welfare of the UAV-enabled mobile edge network, in this paper, we jointly design an edge caching strategy and reward contract optimization scheme. Aiming to maximize the utility of the UAV, a joint edge caching and contract optimization problem is formulated. Firstly, a novel edge caching strategy is proposed based on the content popularity. Then, an optimal reward contract is designed by reducing the restrictions. Finally, the system performance of the designed caching strategy and reward contract is evaluated compared with two benchmark caching schemes with no incentives. Simulation results show that the proposed scheme performs better than the other two schemes in terms of the utilities of the UAV and UEs, which proves the efficiency of our proposed scheme.

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Joint design of device to device caching strategy and incentive scheme in mobile edge networks

Cited by 15 publications

References 21 publications

Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

A Review on Green Caching Strategies for Next Generation Communication Networks

Edge caching strategy design and reward contract optimization for uAV-enabled mobile edge networks

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