Efficient placement of edge computing devices for vehicular applications in smart cities

Premsankar, Gopika; Ghaddar, Bissan; Francesco, Mario Di; Verago, Rudi

doi:10.1109/noms.2018.8406256

Cited by 57 publications

(39 citation statements)

References 91 publications

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“…The study [62] considered a smart city scenario where vehicles ran applications that take data from the environment and send them to edge computing servers through roadside units (RSUs) to enable further processing and analysis. The edge computing servers are co-located with the RSUs, which are further connected to the cloud through the Internet.…”

Section: Cost Optimized Edge Enabled Transportationmentioning

confidence: 99%

See 1 more Smart Citation

Edge-Computing-Enabled Smart Cities: A Comprehensive Survey

Khan

Yaqoob

Tran

et al. 2020

IEEE Internet Things J.

288

131

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Recent years have disclosed a remarkable proliferation of compute-intensive applications in smart cities. Such applications continuously generate enormous amounts of data which demand strict latency-aware computational processing capabilities. Although edge computing is an appealing technology to compensate for stringent latency related issues, its deployment engenders new challenges. In this survey, we highlight the role of edge computing in realizing the vision of smart cities. First, we analyze the evolution of edge computing paradigms. Subsequently, we critically review the state-of-the-art literature focusing on edge computing applications in smart cities. Later, we categorize and classify the literature by devising a comprehensive and meticulous taxonomy. Furthermore, we identify and discuss key requirements, and enumerate recently reported synergies of edge computing enabled smart cities. Finally, several indispensable open challenges along with their causes and guidelines are discussed, serving as future research directions.

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Section: Cost Optimized Edge Enabled Transportationmentioning

confidence: 99%

“…Premsankar et al [62] • Proposed deployment of RSUs to jointly reduce deployment and transmission power cost.…”

Section: Smart Tourismmentioning

confidence: 99%

Edge-Computing-Enabled Smart Cities: A Comprehensive Survey

Khan

Yaqoob

Tran

et al. 2020

IEEE Internet Things J.

288

131

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“…This can be attributed to edge computing characteristics of functional and geographical scalability in the urban environments and efficient utilization of compute, network and storage resources. However, a lot of research is taking place to deal with computation capacity, security, and placement of edge devices for specific smart city applications such as vehicular network …”

Section: Related Workmentioning

confidence: 99%

“…In the context of smart cities there is a lot of ongoing research on Internet‐of‐Things (IoT) and edge‐computing to distribute computing model at edge of the IT infrastructure in order to gain functional and geographical scalability . However, most existing solutions focus on IoT and/or sensors data processing through edge computing enabled deployment models.…”

Section: Introductionmentioning

confidence: 99%

Blockchain and edge computing–based architecture for participatory smart city applications

Khan

Abbasi

Pervez

2019

Concurrency and Computation

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Smart cities aim to provide smart governance with the emphasis on gaining high transparency and trust in public services and enabling citizen participation in decision making processes.This means on the one hand data generated from urban transactions need to be open and trustworthy. On the other hand, security and privacy of public data needs to be handled at different administrative and geographical levels. In this paper, we investigate the pivotal role of blockchain in providing privacy, self-verification, authentication, and authorization of participatory transactions in open governance. We also investigate up to what extent edge computing can contribute toward management of permissioned sharing at specific administrative levels and enhance privacy and provide an economic approach for resource utilization in a distributed environment. We introduce a novel architecture that is based on distributed hybrid ledger and edge computing model. The architecture provides refined and secure management of data generated and processed in different geographical and administrative units of a city.We implemented a proof of concept of the architecture and applied it on a carefully designed use case, ie, citizen participation in administrative decisions through consensus. This use case highlights the need to keep and process citizen participation data at local level by deploying district chaincodes and only share consensus results through permissioned chaincodes. The results reveal that proposed architecture is scalable and provide secure and privacy protected environment for citizen participatory applications. Our performance test results are promising and show that under control conditions, the average registration time for a citizen transaction is about 42 ms, whilst the validation and result compilation of 100 concurrent citizens' transactions took about 2.4 seconds. INTRODUCTIONSmart cities are becoming prevalent in urban areas to deal with different societal challenges such as sustainable transport, energy, greenhouse gas emissions and monitoring, public health and quality of life, economic and job growth, etc. 1,2 The ubiquitous nature of smart IT-based solutions provides new services to citizens. As a result, it has become a source of new information for city administrations for smart open governance, based on which city development plans are proposed and strategic decisions are made. Such a smart open governance approach aims to engage with citizens through innovative approaches and deliver highly transparent and trustable public services. 3 The involvement of citizen in city planning through consultation meetings, opinions, polls, and call-for-comments on online proposals is referred as citizen engagement or participation, eg, smarticipate project. 4 This enables city administrators to get to know actual needs of the local community, co-create and transform the city infrastructure and services around citizens' needs and requirements. Berntzen and Johannessen 5 highlighted importance of citizen's role in the participat...

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“…In fact, high mobility of vehicles in V2V communication impacts a lot the network performance (i.e., QoS) and user satisfaction/perception while exchanging critical and sensitive information. In the last few years, edge computing has entirely revolutionized the landscape of automotive industry, especially multimedia streaming in V2V communication while optimizing the QoS in terms of greenness, sustainability, reliability, and availability (i.e., high coverage) [1]. Furthermore, IoT-based battery-driven devices have significantly revolutionized the entire ITS platform; thus, it is necessary to optimize their power drain and battery lifetime during communication among users such as those in smart healthcare environments where physicians, medical and paramedical staff, nurses and patients are used to easily exchange the daily reports and relevant contents (i.e., dosage, food, exercise and precaution tips etc) [2].…”

Section: Introductionmentioning

confidence: 99%

Quality of Service Optimization in an IoT-Driven Intelligent Transportation System

Sodhro

Obaidat

Abbasi

et al. 2019

IEEE Wireless Commun.

132

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High mobility in intelligent transportation systems (ITS), especially vehicle to vehicle (V2V) communication, allows increasing coverage and quick assistance to the users and neighboring networks, but also degrades the performance of the entire system due to fluctuation in the wireless channel. How to obtain better quality of service (QoS) in terms of performance metrics during multimedia transmission in V2V over future generation networks (i.e., edge computing platforms) is very challenging due to the high mobility of vehicles and heterogeneity of future internet of things (IoT)-based edge computing networks. In this context, the paper contributes in three distinct ways: (i) to develop a QoS-aware, green, sustainable, reliable and available (QGSRA) algorithm to support multimedia transmission in V2V over future IoT driven edge computing networks; (ii) to implement a novel QoS optimization strategy in V2V during multimedia transmission over IoT-based edge computing platforms; (iii) to propose QoS metrics such as greenness (i.e., energy efficiency), sustainability (i.e., less battery charge consumption), reliability (i.e., less packet loss ratio), and availability (i.e., more coverage) to analyze the performance of V2V networks. Finally, the proposed QGSRA algorithm has been validated through extensive real-time data sets of vehicles to demonstrate how it outperforms conventional techniques making it a potential candidate for multimedia transmission in V2V over self-adaptive edge computing platforms.

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Efficient placement of edge computing devices for vehicular applications in smart cities

Cited by 57 publications

References 91 publications

Edge-Computing-Enabled Smart Cities: A Comprehensive Survey

Edge-Computing-Enabled Smart Cities: A Comprehensive Survey

Blockchain and edge computing–based architecture for participatory smart city applications

Quality of Service Optimization in an IoT-Driven Intelligent Transportation System

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