An edge-based platform for dynamic Smart City applications

Cicirelli, Franco; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea

doi:10.1016/j.future.2017.05.034

Cited by 113 publications

(36 citation statements)

References 21 publications

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“…Edge computing is a technology which conducts calculation at the network edge through a small data center closer to the terminals. The edge is the immediate first hop from the IoT device but not the IoT node itself, such as IoT gateways and base stations [16][17][18][19]. As an important part of the IoT, the base stations play a bridge role.…”

Section: Positioning System Architecturementioning

confidence: 99%

BeiDou Satellite Positioning Method Based on IoT and Edge Computing

Wang

Qiu

2020

Sensors

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The BeiDou navigation satellite system (BDS) developed by China can provide users with high precision, as well as all-weather and real-time positioning and navigation. It can be widely used in many applications. However, new challenges emerge with the development of 5G communication system and Internet of Things (IoT) technologies. The BDS needs to be suitable for the large-scaled terminal scenario and provides higher positioning precision. In this paper, a BeiDou differential positioning method based on IoT and edge computing is proposed. The computational pressure on the data center is offloaded to the edge nodes when the massive positioning requests of IoT terminals need to be processed. To ensure the load balancing of the edge nodes, the resource allocation of the terminal positioning requests is performed with the improved genetic algorithm, thereby reducing the service delay of the entire edge network. Moreover, the optimized unscented Kalman filter based on the edge node (EUKF) algorithm is used to improve the positioning precision of IoT terminals. The results demonstrate that the proposed positioning method has better positioning performance which can provide the real-time positioning service for the large-scale IoT terminals.

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Section: Positioning System Architecturementioning

confidence: 99%

BeiDou Satellite Positioning Method Based on IoT and Edge Computing

Wang

Qiu

2020

Sensors

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“…In the work of Cicirelli et al, the authors introduced iSapeins, and IoT‐based platform, which utilizes software agents and virtual objects (VO), deployed on distributed compute nodes (Raspberry Pi 2 model B board), for implementing application and services for the smart city. All software agents and VO are managed by an iSapeins server in an external data center.…”

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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“…As a result, we use the concept of edge computing in the maintenance architecture of a communication network [Qiao, Ren, Dustdar et al (2018) ;Schneider, Rambach, Stricker et al (2018)]. Edge computing migrates applications, data resources, and computing services originally provided by the central node to edge nodes, providing nearest-end services at nearby locations [Ai, Peng, Zhang et al (2017); Cicirelli, Guerrieri, Spezzano et al (2017); Aazam and Huh (2016); Dolui and Datta (2017)]. This method of providing nearby computing services meets technical and application-related requirements in terms of rapid connection and response, and real-time analysis [Al-Shuwaili and Simeone (2017)].…”

Section: Related Workmentioning

confidence: 99%

Context-Based Intelligent Scheduling and Knowledge Push Algorithms for AR-Assist Communication Network Maintenance

Rui¹,

Qin²,

Li³

et al. 2019

Computer Modeling in Engineering &Amp; Sciences

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Maintenance is an important aspect in the lifecycle of communication network devices. Prevalent problems in the maintenance of communication networks include inconvenient data carrying and sub-optimal scheduling of work orders, which significantly restrict the efficiency of maintenance work. Moreover, most maintenance systems are still based on cloud architectures that slow down data transfer. With a focus on the completion time, quality, and load balancing of maintenance work, we propose in this paper a learning-based virus evolutionary genetic algorithm with multiple quality-ofservice (QoS) constraints to implement intelligent scheduling in an edge network. The algorithm maintains the diversity of the population and improves the speed of convergence using a fitness function and a learning-based population generation mechanism. The test results demonstrate that the algorithm delivers good performance in terms of load balancing and QoS guarantee. We also propose a knowledge push algorithm based on a context model for intelligently pushing relevant knowledge according to the given conditions. The simulation results demonstrate that our scheme can improve the efficiency of on-site maintenance.

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An edge-based platform for dynamic Smart City applications

Cited by 113 publications

References 21 publications

BeiDou Satellite Positioning Method Based on IoT and Edge Computing

BeiDou Satellite Positioning Method Based on IoT and Edge Computing

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

Context-Based Intelligent Scheduling and Knowledge Push Algorithms for AR-Assist Communication Network Maintenance

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