Joint Offloading and Computing Design in Wireless Powered Mobile-Edge Computing Systems With Full-Duplex Relaying

Wen, Zhigang; Yang, Kaixi; Liu, Xiaoqing; Shan, Li; Zou, Junwei

doi:10.1109/access.2018.2879334

Cited by 29 publications

(32 citation statements)

References 14 publications

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“…where β * j and ν * j satisfy the KKT conditions (19) and (20), respectively. In the following, we examine 3 cases in order to obtain {p * j , β * j , ν * j }: 1) From (19) and (20)…”

Section: A Trade-off Optimization Based On Interference Suppressionmentioning

confidence: 99%

“…Ξ j implies that β * j > 0 from the constraints (21). Therefore, p * j = τ j Ξ j and ν * j = 0 according to (19) and (20). By substituting these in (21)…”

Section: A Trade-off Optimization Based On Interference Suppressionmentioning

confidence: 99%

“…In the area of multi-user FD systems, only limited works have been done on mobile-edge computing (MEC). [19] studied energy harvesting with MEC, where a FD relay assists a mobile user to connect to an access point (AP) integrated with a MEC server. The user uploads part of its computation bits to the AP for execution and then, uses power splitting to download the results and harvest energy within a time frame.…”

Section: Introductionmentioning

confidence: 99%

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A Scalable Energy vs. Latency Trade-Off in Full-Duplex Mobile Edge Computing Systems

Kabir

Masouros

2019

IEEE Trans. Commun.

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In this paper, we investigate the offloading energy and latency trade-off in a multiuser full-duplex (FD) system. We consider a multi-user FD system where a FD base station (BS), equipped with a mobile-edge computing (MEC) server, carries out data transmission in the downlink, while at the same time receiving computational tasks from mobile devices in the uplink. Our main aim is to study the trade-off between the offloading energy and latency, which are known to be very important and desirable system objectives for both the system operator and users. In practice, there always exist a trade-off between these two objectives. Towards this aim, we formulate two weighted multi-objective optimization problems (MOOPs), one, where the multi-user interference (MUI) is suppressed and the other, where MUI is rather exploited. As a result, our proposed MOOPs allow for a scalable tradeoff between the two objectives. To tackle the non-convexity of the formulations, we design an iterative algorithm through Lagrangian method. We also, address the scenario of imperfect channel state information (CSI) at the FD BS. For the imperfect CSI case, we apply convex relaxations and transformation using the S-procedure to tackle the non-convexity of the formulations. Simulation results show the effectiveness of the proposed FD schemes compared with the existing baseline half duplex schemes, and the superiority of MUI exploitation over suppression.

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“…where β * j and ν * j satisfy the KKT conditions (19) and (20), respectively. In the following, we examine 3 cases in order to obtain {p * j , β * j , ν * j }: 1) From (19) and (20)…”

Section: A Trade-off Optimization Based On Interference Suppressionmentioning

confidence: 99%

“…Ξ j implies that β * j > 0 from the constraints (21). Therefore, p * j = τ j Ξ j and ν * j = 0 according to (19) and (20). By substituting these in (21)…”

Section: A Trade-off Optimization Based On Interference Suppressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Scalable Energy vs. Latency Trade-Off in Full-Duplex Mobile Edge Computing Systems

Kabir

Masouros

2019

IEEE Trans. Commun.

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“…Cooperative relaying is a promising technique to improve the spectrum efficiency, strengthen the system security, and enhance the network connectivity [5][6][7][8]. To improve the performance of MEC networks, cooperative relaying has been proposed to improve the transmission rate, which therefore reduces the latency and the energy efficiency [9][10][11]. Specifically, Cao et al in [9] proposed to utilize relay nodes consisting of retransmission and cooperative computation to improve the performance of MEC network, and the authors designed an energyefficient algorithms for the proposed network.…”

Section: Introductionmentioning

confidence: 99%

“…In [10], Hu et al investigated the wireless powered cooperation network, where the access terminals are powered by the radio signal transmitted from the MEC base station, and the authors optimized the transmit power for the proposed system. Based on above works, Wen et al in [11] further considered the full-duplex relaying scenario and jointly optimized the task offloading and computing scheme.…”

Section: Introductionmentioning

confidence: 99%

Cache-aided mobile edge computing for B5G wireless communication networks

Xia

Lai

et al. 2020

J Wireless Com Network

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This paper investigates a cache-aided mobile edge computing (MEC) network, where the source offloads the computation task to multiple destinations with computation capacity, with the help of a cache-aided relay. For the proposed cache-aided MEC networks, two destination selection criteria have been proposed to maximize the computation capacity of the selected destination, the channel gain of relay link and the channel gain of direct link, respectively. Similarly, three destination selection criteria have been proposed for the cache-free MEC networks based on the computation capacities of destinations and the channel gains of transmission links, respectively. To evaluate the system performance regarding the latency constraint, we provide the outage probability for the proposed network which is defined based on the transmission-plus-computation time. Our analysis suggests that caching can significantly alleviate the impact of increasing the size of computation task, since only half of the transmission time of cache-free network is required. However, the cache-aided network can not fully exploit the signal from both direct and relay links, thus the improvement by caching is less significant in the high signal-to-noise ratio (SNR) region, compared with the cache-free network employing the destination with maximal channel gain of direct link. Numerical results are given to validate our analysis.

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A review on the computation offloading approaches in mobile edge computing: A game‐theoreticperspective

2020

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In recent years, novel mobile applications such as augmented reality, virtual reality, and three-dimensional gaming, running on handy mobile devices have been pervasively popular. With rapid developments of such mobile applications, decentralized mobile edge computing (MEC) as an emerging distributed computing paradigm is developed for serving them near the smart devices, usually in one hop, to meet their computation, and delay requirements. In the literature, offloading mechanisms are designed to execute such mobile applications in the MEC environments through transferring resource-intensive tasks to the MEC servers. On the other hand, due to the resource limitations, resource heterogeneity, dynamic nature, and unpredictable behavior of MEC environments, it is necessary to consider the computation offloading issues as the challenging problem in the MEC environment. However, to the best of our knowledge, despite its importance, there is not any systematic, comprehensive, and detailed survey in game theory (GT)-based computation offloading mechanisms in the MEC environment. In this article, we provide a systematic literature review on the GT-based computation offloading approaches in the MEC environment in the form of a classical taxonomy to recognize the state-of-the-art mechanisms on this important topic and to provide open issues as well. The proposed taxonomy is classified into four main fields: classical game mechanisms, auction theory, evolutionary game mechanisms, and hybrid-base game mechanisms. Next, these classes are compared with each other according to the important factors such as performance metrics, case studies, utilized techniques, and evaluation tools, and their advantages and disadvantages are discussed, as well. Finally, open issues and future uncovered or weakly covered research challenges are discussed and the survey is concluded. K E Y W O R D S game theory, mobile edge computing, offloading, systematic review 1 INTRODUCTION Thanks to the recent improvements in hardware and software capabilities and accordingly complex mobile applications of mobile devices, they are becoming more popular in recent years. In the presence of emerging technologies,

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Joint Offloading and Computing Design in Wireless Powered Mobile-Edge Computing Systems With Full-Duplex Relaying

Cited by 29 publications

References 14 publications

A Scalable Energy vs. Latency Trade-Off in Full-Duplex Mobile Edge Computing Systems

A Scalable Energy vs. Latency Trade-Off in Full-Duplex Mobile Edge Computing Systems

Cache-aided mobile edge computing for B5G wireless communication networks

A review on the computation offloading approaches in mobile edge computing: A game‐theoreticperspective

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