Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System

Wang, Xiaojie; Ning, Zhaolong; Wang, Lei

doi:10.1109/tii.2018.2816590

Cited by 354 publications

(185 citation statements)

References 26 publications

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“…Another major advantage of using cloudlets is that they are energy saving. The cloudlets are fixed, and the clients are mobile in the literature, Scavenger, and CirrusCloud…”

Section: Related Workmentioning

confidence: 99%

“…The slow data transmission speeds from mobile devices to cellular tower introduce communication delays in the task completion time. Researchers [23][24][25][26][27][28][29][30][31][32][33][34] proposed the concept of cloudlets to reduce these delays. A cloudlet is a computer or a system of computers placed together at a local site.…”

Section: Mobile Cloud and Its Offloading Architecturesmentioning

confidence: 99%

“…Another major advantage of using cloudlets is that they are energy saving. The cloudlets are fixed, and the clients are mobile in the literature, [24][25][26][27][28][29][30][31][32] Scavenger, 33 and CirrusCloud. 34 Some cloud frameworks have been proposed as open source for private cloud formation, for example, OpenNebula, 35 Nimbus, 36 Openstack, 37 Eucalyptus, 38 and Snooze.…”

Section: Mobile Cloud and Its Offloading Architecturesmentioning

confidence: 99%

“…We have discussed various MCC frameworks: (1) commercial clouds with complete task offloading for mobile devices, [2][3][4][5] (2) commercial clouds with partial task offloading for mobile devices, [9][10][11][12] (3) volunteer global cloud with stationary devices, [13][14][15] (4) volunteer global cloud with mobile devices, [18][19][20][21][22] (5) commercial or volunteer global cloud with mobile devices using cloudlets, [23][24][25][26][27][28][29][30][31][32][33][34] and (6) volunteer local cloud with mobile devices. [35][36][37][38][39][40] The major limitation of all the above-mentioned techniques 2,3,7-40 is that a fixed infrastructure is required which acts as a central controller to manage resource sharing.…”

Section: Mobile Cloud and Its Offloading Architecturesmentioning

confidence: 99%

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EMCloud: A hierarchical volunteer cloud with explicit mobile devices

Malhotra

Dhurandher

Gupta³

et al. 2018

Int J Communication

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Summary Today, the world is witnessing an exponential growth in the computational capabilities and storage capabilities of mobile devices. This has inspired application developers to create new and interesting applications for mobile devices. The applications have varied resource requirements and mobile devices are heterogeneous in their configurations. The idea of this research is to design a model for resource sharing among mobile devices so that any type of application can be run on a mobile device with the help of other such devices in close geographical proximity. A novel architecture for managing a group of volunteer nodes with unused or underused resources is designed and algorithms that are required for its operation are developed. The purpose of this research is to shift the focus towards futuristic computing paradigm where seamless resource sharing in the network would be feasible with explicitly all mobile nodes and without any dependency on fixed infrastructures. An extensive evaluation of the proposed Explicit Mobile Cloud (EMCloud) has been undertaken for mobile nodes in the network. It includes experience with a prototype that demonstrates EMCloud's performance. Simulation results demonstrate that the proposed scheme outperforms the state‐of‐the‐art Serendipity, OpenNebula, and Eucalyptus prototypes in terms of success rate and average delay for different network density, mobility, network load, and extent of hierarchy.

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“…Another major advantage of using cloudlets is that they are energy saving. The cloudlets are fixed, and the clients are mobile in the literature, Scavenger, and CirrusCloud…”

Section: Related Workmentioning

confidence: 99%

Section: Mobile Cloud and Its Offloading Architecturesmentioning

confidence: 99%

Section: Mobile Cloud and Its Offloading Architecturesmentioning

confidence: 99%

Section: Mobile Cloud and Its Offloading Architecturesmentioning

confidence: 99%

See 2 more Smart Citations

EMCloud: A hierarchical volunteer cloud with explicit mobile devices

Malhotra

Dhurandher

Gupta³

et al. 2018

Int J Communication

View full text Add to dashboard Cite

show abstract

“…To accomplish real‐time and location‐aware network responses, a combination of vehicular systems and fog computing termed as vehicular fog computing Vehicular Fog Computing (VFC) was introduced in a previous study The VFC‐empowered offloading plan was figured in previous studies; for continuous administration and real‐world taxi trajectory–based performance, analysis were conducted for performance validation similarly as in the other existing study …”

Section: Introductionmentioning

confidence: 99%

LTE‐DSRC hybrid vehicular communication system using DFT‐spread OFDM in uplink

Chyne

Kandar

2019

Int J Communication

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Summary Technologies are advancing at a rapid rate in the current era. People are advancing with the advancement of technologies, be it in education industry, health industry, and providing luxury. With the advent of autonomous luxury‐in‐motion car that provides in‐car‐entertainment (ICE), vehicular communication is the prerequisite towards achieving this goal. Dedicated short range communication (DSRC) is a matured vehicular communication standard, and Long‐Term Evolution (LTE) is the most competing technologies in the cellular communication. In this paper, we focus on the uplink performance of the LTE‐DSRC hybrid infrastructure. The basic transmission scheme for uplink direction is based on single carrier transmission in the form of discrete Fourier transform (DFT)‐spread Orthogonal Frequency Division Multiplexing (OFDM) with a minimum mean square error (MMSE) receiver at the LTE Evolved Node B (eNodeB) and a DSRC OFDM transmitter. A comprehensive bit error rate (BER) performance simulative study has been made on a color image transmission in uplink hybrid LTE‐DSRC system, and the results obtained are encouraging that the proposed convergence is possible, as it provides a substantial decrease in the BER with a gradual increase in the signal ‐to‐ noise ratio Signal to Noise Ratio (SNR).

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Towards general Internet of Vehicles networking: Routing protocols survey

Ksouri

Jemili

Mosbah

et al. 2020

Concurrency and Computation

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The specific characteristics of vehicular ad hoc networks, such as high speed of nodes and frequent topology changes, impose challenges for the routing process. In addition, the advent of the Internet of Vehicles (IoV) concept along with the autonomous and connected cars contribute to the proliferation of new innovative applications with different quality of service requirements, rising new challenging issues for data transfer.In this article, we review the different taxonomies of vehicular routing protocols, while giving an insight into the design of geographical protocols. Then, we outline several optimization techniques and paradigms used to enhance the routing process. Moreover, in order to promote the deployment of robust IoV routing protocols at large scale, we provide some directions for future research work.

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Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System

Cited by 354 publications

References 26 publications

EMCloud: A hierarchical volunteer cloud with explicit mobile devices

EMCloud: A hierarchical volunteer cloud with explicit mobile devices

LTE‐DSRC hybrid vehicular communication system using DFT‐spread OFDM in uplink

Towards general Internet of Vehicles networking: Routing protocols survey

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