Proactive edge computing in latency-constrained fog networks

Elbamby, Mohammed S.; Bennis, Mehdi; Saad, Walid

doi:10.1109/eucnc.2017.7980678

Cited by 112 publications

(67 citation statements)

References 13 publications

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“…In addition, mmWave also enables wireless backhauling [15], [16] that facilitates edge servers' prefetching popular content with low latency. At the processing level, proactive computing provides significant latency reduction while maximizing resource efficiency by avoiding repetitive and redundant on-demand computing [17]- [19]. Next, coded computing is effective in reducing parallel computing latency, which eliminates the dependency of processing tasks, thereby minimizing the worst-case latency due to a straggling task.…”

Section: Low Latency Enablersmentioning

confidence: 99%

“…The ideas of prefetching tasks [48] and proactive computing [17], [18] aim to develop techniques that learns and predicts which tasks are to be requested in the future and pre-compute them. Indeed, the success of proactive computing lies on a well-aimed choice of which tasks to proactively compute and which are to leave for real-time processing.…”

Section: Low Latency Enabler 4 Proactive Computingmentioning

confidence: 99%

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Wireless Edge Computing With Latency and Reliability Guarantees

et al. 2019

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Edge computing is an emerging concept based on distributing computing, storage, and control services closer to end network nodes. Edge computing lies at the heart of the fifth generation (5G) wireless systems and beyond. While current state-of-the-art networks communicate, compute, and process data in a centralized manner (at the cloud), for latency and compute-centric applications, both radio access and computational resources must be brought closer to the edge, harnessing the availability of computing and storage-enabled small cell base stations in proximity to the end devices. Furthermore, the network infrastructure must enable a distributed edge decision-making service that learns to adapt to the network dynamics with minimal latency and optimize network deployment and operation accordingly. This article will provide a fresh look to the concept of edge computing by first discussing the applications that the network edge must provide, with a special emphasis on the ensuing challenges in enabling ultra-reliable and lowlatency edge computing services for mission-critical applications such as virtual reality (VR), vehicle-to-everything (V2X), edge artificial intelligence (AI), and so forth. Furthermore, several case studies where the edge is key are explored followed by insights and prospect for future work.

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Section: Low Latency Enablersmentioning

confidence: 99%

Section: Low Latency Enabler 4 Proactive Computingmentioning

confidence: 99%

Wireless Edge Computing With Latency and Reliability Guarantees

et al. 2019

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“…This is particularly helpful when the SBS performs caching since this process is based on the user's preference. The steps involved in our proposed clustering scheme are inherited from the work of ElBamby et al and summarized as follows. The SBSs calculate the distance between users as a weighted function of the spatial distances and social distances (SDs), where the SD is meant to characterize how the preference between users differ.…”

Section: Simulation Experimentsmentioning

confidence: 99%

Section: Clustering Schemementioning

confidence: 99%

A user‐centric cooperative edge caching scheme for minimizing delay in 5G content delivery networks

Tang

Alnoman

Anpalagan

et al. 2018

Trans Emerging Tel Tech

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This paper investigates the problem of user‐centric cooperative edge caching in content delivery networks to leverage service provisioning at the network edge and to improve the quality of experience by minimizing the end‐to‐end delay. By taking advantage of the major characteristics in fifth‐generation networks, users can access contents not only from the nearest small base station (SBS) but also from other SBSs in the vicinity that have the requested precached contents. In the proposed scheme, a user‐centric delivery approach is considered in such a way that the base station can respond to the user request as long as it has enough resources. To this end, a caching algorithm is introduced whereby a group of SBSs cooperatively share storage and decide on the caching policy together aiming to cache as much contents as possible under the capacity constraint. Moreover, a modified matching theory is used for content delivery taking the bandwidth requirements into account. Simulation results show that the proposed scheme can achieve 99.5% local serve ratio when the SBS has a caching capacity of 40% the overall file size, and 20 available communication channels for content distribution.

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“…In [24], a coded prefetching and the corresponding delivery strategy was proposed, which relies on a combination of rank metric codes and maximum distance separable (MDS) codes in a non-binary finite field. In [25], a novel centralized coded caching scheme was proposed that approaches the ratememory region achieved by the scheme in [24] as the number of users in the system increases, which only requires a finite field of 2 2 . Moreover, instead of relying on the existence of some valid code, an explicit combinatorial construction of the caching scheme was provided.…”

mentioning

confidence: 99%

Decentralized Asynchronous Coded Caching Design and Performance Analysis in Fog Radio Access Networks

Jiang

Huang

Bennis

et al. 2020

IEEE Trans. on Mobile Comput.

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In this paper, we investigate the problem of asynchronous coded caching in fog radio access networks (F-RANs). To minimize the fronthaul load, the encoding set collapsing rule and encoding set partition method are proposed to establish the relationship between the coded-multicasting contents for asynchronous and synchronous coded caching. Furthermore, a decentralized asynchronous coded caching scheme is proposed, which provides asynchronous and synchronous transmission methods for different delay requirements. The closed-form expression of the fronthaul load is established for the special case where the number of requests during each time slot is fixed, and the upper and lower bounds of the fronthaul load are given for the general case where the number of requests during each time slot is random. The simulation results show that our proposed scheme can create considerable coded-multicasting opportunities in asynchronous request scenarios.

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Proactive edge computing in latency-constrained fog networks

Cited by 112 publications

References 13 publications

Wireless Edge Computing With Latency and Reliability Guarantees

Wireless Edge Computing With Latency and Reliability Guarantees

A user‐centric cooperative edge caching scheme for minimizing delay in 5G content delivery networks

Decentralized Asynchronous Coded Caching Design and Performance Analysis in Fog Radio Access Networks

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