FGCS-DaSPFog 2017 : FGCS Special Issue on New Landscapes of the Data Stream Processing in the era of Fog Computing
Call For Papers
Nowadays, an increasingly connected ecosystem of heterogeneous devices is continuously producing unbounded streams of data that have to be processed “on the fly” in order to detect operational exceptions, deliver real-time alerts, and trigger automated actions. This paradigm extends to a wide spectrum of applications with high socio-economic impact, like systems for healthcare, emergency management, surveillance, intelligent transportation and many others.
High-volume data streams can be efficiently analysed in real-time through the adoption of novel high-performance solutions targeting today’s commodity parallel hardware. This comprises multicore-based platforms including mobile devices, heterogeneous systems equipped with GPU and FPGA co-processors, and large-scale distributed-memory systems like multi-Cloud and Fog computing environments. However, despite the large computing power offered by the affordable hardware available nowadays, high-performance data streaming solutions need to be equipped with smart logics in order to adapt the framework/application configuration to rapidly changing execution conditions and workloads. Moreover, the burst in the amount of data streams generated at the network edge by sensors and devices and the emergence of applications with predictable and low latency requirements require a shift from the traditional data stream processing performed in a central data center to a geo-distributed processing environment as represented by Fog computing and multi-Clouds. Such a new and challenging scenario demands for mechanisms and strategies for adapting the data stream computation to changes in the operating environment and workload and for dealing with uncertainty, fostering novel interdisciplinary approaches.
The special issue aims at collecting high-quality scientific contributions from the research community working in the fields of data stream processing, data analytics algorithms, big data frameworks and autonomic resource management. The main focus is on parallel and autonomic models and practical implementations on parallel heterogeneous hardware and distributed systems.
We solicit papers covering various topics of interests that include, but are not limited to the following:
* Autonomic resource management for data streaming processing in geo-distributed infrastructures, including resource deployment and provisioning and admission control
* Adaptive load balancing policies for streaming computations
* Queries and data streaming operator placements on Fog resources
* Real-time analytics architecture for IoT
* Elastic techniques and runtime reconfiguration strategies for bursty workloads and varying resource demands
* Programming models and toolkits for supporting Fog Computing for data streaming
* Smart sensors and in-network processing in the context of Fog Computing
* Parallel algorithms and runtime solutions for data streaming
* Decentralized data stream mining algorithms and systems
* Case studies of Fog-based real-time analytics in various domains (Healthcare, IoT, Smart Cities, Social Networks)
* QoS for real-time analytics for Fog Computing and IoT services
All submitted papers will be peer-reviewed by at least three reviewers and selected on the basis of both their quality and their relevance to the theme of this special issue.
Submitted papers must be written in English and must describe original research that has not been published, and is not currently under review by other journals or conferences. A submission based on one or more papers that appeared elsewhere has to comprise major value-added extensions over what appeared previously (at least 40% new material). Authors are requested to attach to the submitted paper their relevant, previously published articles and a summary document explaining the enhancements made in the journal version. The author instructions for preparation of manuscripts can be found at the journal web page. The manuscript format must conform to the submission guidelines provided in the Elsevier FGCS official page. All manuscripts and any supplementary material should be submitted through the online submission system of Future Generation Computer Systems at https://www.evise.com/evise/jrnl/FGCS. Authors should select “SI: DSP in the Fog” when they reach the “Article Type” step in the submission process.
Paper submission due: November 3rd, 2017
Pre-screening notification: November 17th, 2017
First-round notification: January 12th, 2018
Revision submission due: February 23rd, 2018
Final notification: March 30th, 2018
Final Manuscript due: April 27th, 2018
Expected publication: Summer 2018
Valeria Cardellini -- University of Rome Tor Vergata, Italy
Gabriele Mencagli -- University of Pisa, Italy
Domenico Talia -- University of Calabria, Italy
Massimo Torquati (Managing Guest Editor) -- University of Pisa, Italy
(If you make an enquiry, please state “FGCS SI: DSP in the Fog” in your email’s subject