- From: <angalletta@ieee.org>
- Date: Wed, 15 Jul 2020 07:07:36 -0700
- To: semantic-web@w3.org
- Message-ID: <CAN9y1QKv=EzuYd2ZzmcKskkqL=EwpGJ4mXNeETgAy=MTd+qc_A@mail.gmail.com>
Dear users of Semantic-Web mailing list, FYI [Apologies if you receive multiple copies of this CFP] ************************************************************************************************** Journal of Grid Computing - From Grids to Cloud Federations [IF 3.288 (2018)] Special Issue on Orchestration of computing resources in the Cloud-to-Things continuum ************************************************************************************************** https://www.springer.com/journal/10723/updates/18017998 Aim and Scope: The objective of the SI is to collect the latest research findings on major and emerging topics related to the orchestration of resources in a wide ecosystem where IoT, Edge/Fog and Cloud converge to form a computing continuum also known as Cloud-to-Things continuum. Cloud computing can provide flexible and scalable resources to meet any computing needs. Big Data has revolutionized the approach to data computation. With the increase of the volume of data produced by IoT devices, there is a growing demand of applications capable of elaborating such data flows close to their sources, not just on the Cloud, or anywhere else along the IoT-to- Cloud path (Edge/Fog). Where computation should occur depends on the specific needs of each application. Strict real-time constraints require computation to run as close to the data origin as possible (e.g., IoT Gateway). Conversely, batch-wise tasks (e.g., Big Data analytics) are advised to run on the Cloud where computing resources are abundant. Edge/Fog may be a good compromise in case of a concomitant demand of both computing power and timeliness of elaboration. Application designers would greatly benefit from a support for a flexible and dynamic provisioning of computing resources along the Cloud-to-Things path, that is, a provisioning system capable of orchestrating (activating, deactivating, integrating, etc.) computing resources provided by heterogeneous computing infrastructures. Furthermore, that system shall also take into account and cope with the heterogeneity of providers owning the computing infrastructures in terms of service APIs, guaranteed service levels, data management policies, etc. Moreover, typical data-intensive workloads that consist of data-analytics tasks such as Machine Learning (ML)/AI and descriptive analysis are perfect candidates for the Cloud-to-things continuum, since data is being generated typically on the edge (by IoT devices, etc) with the use for instance of a serverless pipeline, whereas the analysis (either for model training, or execution of descriptive tasks) traditionally happens on centralized locations on the cloud with the use of distributed processing frameworks. This SI encourages submissions that address resource orchestration issues in the Cloud-to-Things landscape and propose experimental solutions, case studies, deployed systems and best practices in that field. Topics of the SI include (but are not limited to): - Resource provisioning and monitoring in Cloud-to-Things environments; Cross cloud/edge service migration; Orchestration of microservices; Blockchain techniques for resource orchestration; Machine learning techniques for resource orchestration; - Data governance across multiple computing domains; Scheduling and provisioning data analytics on hybrid Edge/Fog and Cloud infrastructures; Stream data processing in Edge/Fog and Clouds; Serverless Execution of Machine Learning and SQL workloads on the Cloud; - Quality of Service and SLA in Cloud-to-Things environments; Fault management and recovery strategies; Identity and access management; Cross-Infrastructure security mechanisms; Data security and protection; - Multi-cloud deployment and orchestration; Multi-cloud resource elasticity; Optimisation of services and service chains for Cloud-to-Things systems; Optimisation of networking services; SDN/NFV based solutions; Networking; Network orchestration; - Orchestration of computing resources in the following applicative domains: Smart City; Smart Industry; Smart Grid; Smart Agriculture; Smart Health. Submission guidelines: All submitted papers will undergo a rigorous revision process adopted by Journal of Grid Computing. Please submit a full-length paper through the Journal of Grid Computing online submission system ( https://www.editorialmanager.com/grid/default.aspx) and indicate that it is for this special issue. Papers should be formatted by following Journal of Grid Computing manuscript formatting guidelines and must not exceed 18 pages. Please refer to the Journal’s website for detailed instructions on paper submission. For further inquiries, please contact the corresponding Guest Editor Giuseppe Di Modica (see contact details below). Papers submission is according to the following timetable (Tentative Schedule): - Submission deadline: 15th October 2020 - Author notification: 15th January 2021 - Revised papers: 1st March 2021 - Final notification: 15th April 2021 - Publication: as per the policy of the journal Guest Editors Giuseppe Di Modica (Corresponding Guest Editor), University of Bologna, Italy Antonino Galletta, University of Messina, Italy Shadi Ibrahim, Inria, France Ioannis Konstantinou, University of Thessaly, Greece Javid Taheri, Karlstad University, Sweden For more details: https://www.springer.com/journal/10723/updates/18017998
Received on Wednesday, 15 July 2020 14:07:55 UTC