Fog computing in internet of things: Practical applications and future directions

Naeem, Rida Zojaj; Bashir, Shariq; Amjad, Muhammad Faisal; Abbas, Haider; Afzal, Hammad

doi:10.1007/s12083-019-00728-0

Cited by 31 publications

(16 citation statements)

References 87 publications

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“…Explanation 2: When F f =1 n f 0 = 3, the split scheme [3,3,4, 0] obviously does not fully utilize the cache space, while [3,3,3, 0] does. Incomplete utilization of cache space indicated that contents with lower probability of requests are split into more portions.…”

Section: A Problem Analysis and Heuristic Strategymentioning

confidence: 99%

“…Most people already consider mobile voice service a necessity, and mobile voice, data, and video services are fast becoming an integral part of consumers and business users' lives [1]. With the growth of mobile data traffic, the Cloud RAN (C-RAN) and F-RAN have been regarded as promising network architectures for next generation wireless communication [2], [3]. However, not only the signaling overload but also the payload data need to be shared among all the edge nodes (ENs), resulting tremendous burden on fronthaul links [4].…”

Section: Introductionmentioning

confidence: 99%

“…However, not only the signaling overload but also the payload data need to be shared among all the edge nodes (ENs), resulting tremendous burden on fronthaul links [4]. Compared with C-RAN, the multiple ENs in F-RAN are equipped with local cache to store some popular files during the off-peak time and hence can greatly reduce the fronthaul burden and improve the user-perceived experience [3], [5], [6]. In addition to caching, multicast…”

Section: Introductionmentioning

confidence: 99%

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Content-Centric Transmission Design in Fog Radio Access Network With Partition-Based Caching

Li¹,

Xiang²,

Ren³

et al. 2019

IEEE Access

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This paper presents a joint optimization of caching and multicast beamforming for a content-centric transmission in a fog radio access network (F-RAN). Users requesting the same file are grouped together and served using multicast transmission. Each edge node (EN) has a local cache and can pre-store contents via partition-based caching. To improve cache performance and reduce fronthaul cost, the maximum distance separable (MDS) code is applied to the file coding. We consider the mixed timescale joint optimization. In short-term optimization, our goal is to optimize the beamforming vector to minimize the total network consumption under the quality-of-service (QoS) constraint. Meanwhile, semi-definite relaxation (SDR) and convex-concave procedure (CCP) algorithms are introduced to solve short-term problem. In long-term optimization, based on the channel state information (CSI) and user requests, we formulate an integer programming problem of minimizing the expectation of the total network consumption under the constraint of cache capacity and the parameter of MDS code. Furthermore, the considered long-term problem is decomposed and a heuristic method is proposed by replacing the objective function with the expectation of the file splitting number. After transforming the integer variables, the subproblem is transformed into the difference of convex (DC) programs and effectively solved using the CCP algorithm. Numerical results show that the proposed content-centric transmission can strike a better balance between power consumption and fronthaul consumption than existing schemes.

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Section: A Problem Analysis and Heuristic Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Content-Centric Transmission Design in Fog Radio Access Network With Partition-Based Caching

Li¹,

Xiang²,

Ren³

et al. 2019

IEEE Access

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“…Today, many IoT applications that leverage pervasive connectivity and cloud computing are permitting the initiatives of the smart city all over the world [1][2][3][4][5][6][7][8][9][10]. These applications based on cloud computing propose new capabilities including monitoring system ability, control and manage devices remotely, and to make new actionable information and insights to keep massive access streams of real-time data [11].…”

Section: Introductionmentioning

confidence: 99%

Fog computing scheduling algorithm for smart city

Al-smadi

Aloglah

Abu-darwish

et al. 2021

IJECE

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With the advent of the number of smart devices across the globe, increasing the number of users using the Internet. The main aim of the fog computing (FC) paradigm is to connect huge number of smart objects (billions of object) that can make a bright future for smart cities. Due to the large deployments of smart devices, devices are expected to generate huge amounts of data and forward the data through the Internet. FC also refers to an edge computing framework that mitigates the issue by applying the process of knowledge discovery using a data analysis approach to the edges. Thus, the FC approaches can work together with the internet of things (IoT) world, which can build a sustainable infrastructure for smart cities. In this paper, we propose a scheduling algorithm namely the weighted round-robin (WRR) scheduling algorithm to execute the task from one fog node (FN) to another fog node to the cloud. Firstly, a fog simulator is used with the emergent concept of FC to design IoT infrastructure for smart cities. Then, spanning-tree routing (STP) protocol is used for data collection and routing. Further, 5G networks are proposed to establish fast transmission and communication between users. Finally, the performance of our proposed system is evaluated in terms of response time, latency, and amount of data used.

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“…With the development of micro‐processing technology, smart sensing devices (SSDs) have connected to Internet of Things, and the number has reached 2 billion [1–3]. These massive SSDs have huge storage and computing power, which results in the current network computing from the network centre (cloud) [2–5] to the edge of the network, and leads edge computing (EC) [4–7].…”

Section: Introductionmentioning

confidence: 99%

Towards minimum code dissemination delay through UAV joint vehicles for smart city

et al. 2020

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Fog computing in internet of things: Practical applications and future directions

Cited by 31 publications

References 87 publications

Content-Centric Transmission Design in Fog Radio Access Network With Partition-Based Caching

Content-Centric Transmission Design in Fog Radio Access Network With Partition-Based Caching

Fog computing scheduling algorithm for smart city

Towards minimum code dissemination delay through UAV joint vehicles for smart city

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