Edge Computing Optimization Using Artificial Intelligence Methods
A special issue of IoT (ISSN 2624-831X).
Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 9837
Special Issue Editors
2. INESC-ID, Rua Alves Redol 9, 1000-029 Lisboa, Portugal
3. INOV, Rua Alves Redol 9, 1000-029 Lisboa, Portugal
Interests: Computer Networks; Wireless Communications; Internet of Things; Artificial Intelligence
2. INESC-ID, Rua Alves Redol 9, 1000-029 Lisboa, Portugal
Interests: Computer Networks; Delay Tolerant Networks; Vehicular Networks; Internet of Vehicles
Interests: computer networks; network security; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The growing importance of the Internet of Things (IoT) and the ubiquitous high capacity provided by 5G technologies have brought the specter of massive quantities of data being generated and/or consumed by sensors, actuators, and smart devices. Such massive amounts of data require considerable processing power, which is available in the cloud. However, cloud-based computation and data delivery models do not allow the stringent quality of service (QoS) guarantees to be efficiently harnessed. The latter is due to the number of hops of wired networks between the data endpoints and the cloud, which leads to a significant increase in latency, which may dramatically affect real-time control and other critical systems. Moreover, forwarding all the data generated by such devices directly to the cloud may devour the network bandwidth, leading to congestion. Therefore, it is necessary that critical processing to be hosted closer to the endpoint devices, i.e., closer to the sources and sinks of the data so that data can be processed and filtered out by the time it reaches the cloud. This can be achieved through Edge Computing (EC).
Efficient, scalable, and QoS-aware placement of IoT data processing jobs in EC resources is a complex optimization problem and, currently, an active research topic. As new jobs are created, they have to be assigned computational resources dynamically, matching job requirements with the cost, reliability, location (and mobility), besides the current availability of the resources. Less critical or demanding communication jobs may be offloaded to the cloud. The use of Artificial Intelligence (AI) methods to jointly tackle the problem of job placement optimization, including jobs belonging to AI-based data analytics software, constitute currently active research topics addressed by this Special Issue.
For this Special Issue, original scientific articles are welcome on the following as well as closely related topics:
- AI-based algorithms to optimize job placement in EC
- AI software architectures favoring distributed computing job placement in EC resources (e.g., Distributed Deep Neural Network architectures)
- AI-based mechanisms supporting open EC markets leveraging the participation of third-party computing resources opportunistically (e.g., parked autonomous vehicles)
- AI-based methods to optimize mobile EC resources’ placement (e.g., EC capable drones)
Prof. Dr. António M.R.C. Grilo
Prof. Dr. Paulo Rogerio Pereira
Prof. Dr. Naércio Magaia
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. IoT is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Edge Computing
- Job Placement Optimization
- Artificial Intelligence
- Distributed Data Flow
- Mobile and Opportunistic Edge Computing Resources
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