[hpc-announce] CFP: Special Issue on Elastic Computing from Edge to the Cloud

[Rajkumar Buyya]

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            Software: Practice and Experience (Wiley Press)
          Special Issue on Elastic Computing from Edge to the Cloud

https://onlinelibrary.wiley.com/page/journal/1097024x/homepage/special_issues.htm

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Call for Papers
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Today, a huge amount of data is being generated by the Internet of 
Things (IoT), such as  smartphones,  sensors,  cameras,  cars,  and 
robots.  These  data  have  been traditionally processed in the Cloud 
with various Big Data platforms (e.g. Hadoop, Spark), with Artificial 
Intelligence methods, and similar. Elasticity represents the ability to 
quickly expand or decrease computer processing, memory, and storage 
resources to meet changing demands without worrying about capacity 
planning and engineering for peak usage. Such mechanisms already exist 
for the Cloud. With the increasing production of Big Data and due to 
latency, privacy, and other concerns, an Edge computing paradigm has 
emerged in order to facilitate Big Data processing closer to the source 
of the data.

Edge computing seamlessly integrates hardware and software resources 
across multiple computing tiers, from the Edge to the Cloud. The Edge 
consists of heterogeneous and potentially moving devices that are under 
the control of various entities. Elasticity mechanisms for such a very 
complex and heterogeneous environment, under different administrative 
controls, has not been yet fully developed. Since computing resources at 
the Edge may be power and capacity constrained, it is necessary to 
invent new lightweight platforms and techniques that seamlessly 
interact, sense, execute and produce results with very low latency, 
while at the same time address other high-level requirements of 
applications with elasticity such as security, and privacy. Regarding 
these problems, there are many challenges that must be addressed with 
the invention of new architectures, methods, algorithms, and solutions.


The  aim of the Special Issue is to report the state-of-the-art research 
on Elastic Computing from Edge to the Cloud. This is an open call for 
contributions. Our intention is  to  discuss  various  problems, 
challenges,  new  approaches,  and  technologies addressing this hot new 
area of research. The idea is to shortlist the most challenging 
problems,  to  shape  future  directions  for  research,  foster  the 
exchange  of  ideas, standards, and common requirements. We look for 
high-quality work that addresses various aspects of the investigated 
problem.


Topics of interest include but are not limited to:
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▪Elasticity solutions for the Edge
▪Integrate and process data from underlying IoT platforms and services
▪Smartly select data streams for processing

▪Address elasticity requirements related to the 4 “V” of the Big Data 
problem: volume, variety, velocity and veracity
▪Improve the energy-efficient management of resources and tasks processing
▪Address the QoS and time-critical aspects of smart applications
▪Facilitate intelligent integration of information arising from various 
sources
▪Address the requirements of very dynamic Big Data pipelines (e.g. 
moving smartphones, sensors, cars, robots with dynamically changing 
requirements for processing)
▪Provide orchestration methods and scheduling policies that address 
dependability, reliability, availability and other high-level 
application requirements
▪Adequately address the inherent variability of resources from the Edge 
to the Data Centers
▪Provide new architectures which use the powerful computing resources of 
Data Centers, while at the same time providing optimal QoS to applications
▪Address elasticity requirements through the use of Blockchain-based 
Smart Contracts and Oracles
▪Implement distributed Artificial Intelligence methods from the Edge to 
the Data Center/Cloud

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Important Dates
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July 30, 2020 - Paper submission due

Sept 30, 2020 - First round evaluation notification

Oct 30, 2020 - Revision submission due

November 15, 2020 - Paper acceptance/rejection notification

Dec 15, 2020 - Special Issue

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Special Issue Paper Submission
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This special issue seeks the submission of papers that present novel and 
innovative ideas.All submissions go under the regular peer-review 
process.

The guest editorial board members cover broad expertise from the areas 
of Edge and Fog   computing,   High-Performance   Computing,   Cloud 
computing, decentralized/distributed  Artificial  Intelligence, 
orchestration  and  scheduling, Blockchain, and others.

We seek submission of papers that present new, original, and innovative 
ideas for the "first" time in SPE. Submission of "extended versions" of 
already published works (e.g., conference papers) is not encouraged 
unless they contain a significant number of "new and original" 
ideas/contributions along with more than 50% brand "new" material. If 
you are submitting an extended version, you must submit a cover 
letter/document detailing (1) the "Summary of Differences" between the 
SPE paper and the earlier paper,  (2) a  clear list of "new and 
original" ideas/contributions in the SPE paper (identifying  sections 
where  they  are  proposed/presented),  and  (3)  confirming  the 
percentage of new material. Otherwise, the submission will be "desk" 
rejected without being reviewed.

While submitting the paper to this issue, please select 
“SPE-SI-BigDataPipelines” in the submission system 
(https://mc.manuscriptcentral.com/spe).

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Regular Issue Submission
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"If you have a paper on that does not match the requirements of the 
Special Issue, we encourage you to submit it as a regular paper to 
Software: Practice and Experience. The journal has expanded its coverage 
to specifically include cloud computing."

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Guest Editors
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Vlado Stankovski

Distributed and Cloud Computing
University of Ljubljana, Slovenia

Rajkumar Buyya

Cloud Computing and Distributed Systems (CLOUDS) Laboratory,
University of Melbourne, Australia

Shrideep Pallickara

Department of Computer Science
Colorado State University, USA

Shashikant Ilager

Cloud Computing and Distributed Systems (CLOUDS) Laboratory,
University of Melbourne, Australia
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