Invited Paper: Edge and Fog Computing: Vision and Research Challenges

Dustdar, Schahram; Avasalcai, Cosmin; Murturi, Ilir

doi:10.1109/sose.2019.00023

Cited by 35 publications

(16 citation statements)

References 28 publications

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“…Next, edge computing is expected to be a key component of 5G networks [24,89,99] to enable low-latency applications described in Chapter 4. However, the deployment and management of edge resources is still an open challenge [31,100]. Our research is an important step in establishing the optimal locations of edge devices.…”

Section: Future Workmentioning

confidence: 99%

“…Our research is an important step in establishing the optimal locations of edge devices. Novel algorithms are required to decide where to deploy applications and when to migrate them in the edge infrastructure to support mobility of end-devices [24,100]. To this end, the optimization model proposed in Publication V can be extended by incorporating latency constraints with a realistic model of computing delay based on queueing theory, similar to [99].…”

Section: Future Workmentioning

confidence: 99%

“…To this end, the optimization model proposed in Publication V can be extended by incorporating latency constraints with a realistic model of computing delay based on queueing theory, similar to [99]. Moreover, the resources at the distributed edge can be pooled to further increase computing capacity when the demand is higher [99,100]. So far, we have considered two representative applications (namely, gaming and automotive) that greatly benefit from edge computing.…”

Section: Future Workmentioning

confidence: 99%

See 2 more Smart Citations

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

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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The author of this dissertation contributed to the development of the heuristic algorithms, the implementation of the simulator, the evaluation through simulation, the analysis of results, and writing the article.Publication IV empirically evaluates the impact of edge computing on emerging interactive applications and services. At the time of writing, there was no clear consensus on what specifically constitutes the edge of the network in edge computing. Thus, we first survey the state of the art in edge computing architectures and determine different deployment options for edge devices. Next, we experimentally evaluate edge computing when available at different physical locations and with different virtualization technologies. Specifically, we characterize the end-to-end latency (including

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Section: Future Workmentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%

See 1 more Smart Citation

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

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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show abstract

“…We observe that many previous works presented in-depth surveys on the advances of existing cloud and emerging fog/edge computing paradigms in developing a complete architecture of IoT infrastructure [30,33,[45][46][47]. Only a few recent works as mentioned above discussed the existing integration of cloud-fog or cloud-edge in IoT applications, specifically for e-Healthcare.…”

Section: Background On Internet Of Thingsmentioning

confidence: 99%

A Hierarchical Modeling and Analysis Framework for Availability and Security Quantification of IoT Infrastructures

2020

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Modeling a complete Internet of Things (IoT) infrastructure is crucial to assess its availability and security characteristics. However, modern IoT infrastructures often consist of a complex and heterogeneous architecture and thus taking into account both architecture and operative details of the IoT infrastructure in a monolithic model is a challenge for system practitioners and developers. In that regard, we propose a hierarchical modeling framework for the availability and security quantification of IoT infrastructures in this paper. The modeling methodology is based on a hierarchical model of three levels including (i) reliability block diagram (RBD) at the top level to capture the overall architecture of the IoT infrastructure, (ii) fault tree (FT) at the middle level to elaborate system architectures of the member systems in the IoT infrastructure, and (iii) continuous time Markov chain (CTMC) at the bottom level to capture detailed operative states and transitions of the bottom subsystems in the IoT infrastructure. We consider a specific case-study of IoT smart factory infrastructure to demonstrate the feasibility of the modeling framework. The IoT smart factory infrastructure is composed of integrated cloud, fog, and edge computing paradigms. A complete hierarchical model of RBD, FT, and CTMC is developed. A variety of availability and security measures are computed and analyzed. The investigation of the case-study’s analysis results shows that more frequent failures in cloud cause more severe decreases of overall availability, while faster recovery of edge enhances the availability of the IoT smart factory infrastructure. On the other hand, the analysis results of the case-study also reveal that cloud servers’ virtual machine monitor (VMM) and virtual machine (VM), and fog server’s operating system (OS) are the most vulnerable components to cyber-security attack intensity. The proposed modeling and analysis framework coupled with further investigation on the analysis results in this study help develop and operate the IoT infrastructure in order to gain the highest values of availability and security measures and to provide development guidelines in decision-making processes in practice.

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“…Other surveys have studied basic characteristics, research challenges, and opportunities of different edge computing paradigms [19][20][21][22]. Caprolu et al [2] discussed security issues about supporting technologies for the edge computing, and Dustdar et al [23] presented detailed individual characteristics and use cases along with certain future challenges of edge and fog computing paradigms. Alrowaily et al [24] reviewed the concepts, characteristics, security, and edge computing IoT-driven applications besides the security features of a data-driven world.…”

Section: B Related Workmentioning

confidence: 99%

Edge Computing and Its Convergence With Blockchain in 5G and Beyond: Security, Challenges, and Opportunities

2020

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Invited Paper: Edge and Fog Computing: Vision and Research Challenges

Cited by 35 publications

References 28 publications

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

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

A Hierarchical Modeling and Analysis Framework for Availability and Security Quantification of IoT Infrastructures

Edge Computing and Its Convergence With Blockchain in 5G and Beyond: Security, Challenges, and Opportunities

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