Calls for Papers (special): International Journal of Grid and High Performance Computing (IJGHPC)


Special Issue On: Machine Learning for Internet of Things and Big Data

Submission Due Date
12/20/2017

Guest Editors
Chintan Bhatt
Dmitry Korzun
Soumya Banerjee

Introduction
By 2025, the overall size of digital knowledge generated by social networks, sensors, medical imaging and simulation devices, can reach up to Zettabytes. We are now in era of “big data”. This kind of “big” knowledge, along with the advances in information and communication technologies like Web of Things (IoT), connected sensible objects, wearable technology, pervasive computing, is remodeling each facet of contemporary life and conveyance nice challenges and spectacular opportunities to meet our dream of a property sensible society.

Objective
This issue aims to supply a platform and forum to debate and report current progressive, new solutions, future directions to handle challenges, problems and success stories on a way to harness potential advances within the digital space to boost people’s life (e.g. big data, IoT, mobile/ present computing), and the way to maximize the employment of huge processing and knowledge analytics to understand the sensible society.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:
  • Machine Learning Techniques and algorithms for Big Data and IoT
  • Data mining, statistical modeling and machine learning for data management
  • Analytics and machine learning applications to security and privacy
  • Machine Learning as-a-service
  • Machine learning and prediction of context awareness with Big Data and IoT
  • Big Data applications such as analytics for the Internet-of-Things (IoT), online web analytics, smart grid analytics etc.
  • Deep Learning in Big Data and IoT
  • Edge/Fog Analytics
  • Advanced collaboration techniques and scaling issues
  • Emerging standards for organizations and international projects


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Machine Learning for Internet of Things and Big Data on or before November 1, 2017. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/journals/guidelines-for-submission.aspx. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Chintan Bhatt
Dmitry Korzun
Soumya Banerjee
Guest Editor
International Journal of Grid and High Performance Computing (IJGHPC)
E-mail: chintanbhatt.ce@charusat.ac.in; dkorzun@cs.karelia.ru; dr.soumya@ieee.org

PLEASE NOTE: All submissions should be created using the link below ↴

Special Issue On: Big Data Analytics and Internet of Everything-Fusion for Various Administrations

Submission Due Date
12/31/2017

Guest Editors
Dr. Hemraj Saini, Jaypee University of Information Technology, India
Dr. Alexander Horst Norta, Tallinn University of Technology, Estonia
Dr. Mayank Singh, University of Kwazulu-Natal, Durban, South Africa

Introduction
IoE is the intelligent connection of people, process, data and things. The Internet of Everything (IoE) describes a world where billions of objects have sensors to detect measure and assess their status; all connected over public or private networks using standard and proprietary protocols. The Internet of Everything (IoE) with four pillars- people, process, data, and things builds on top of The Internet of Things (IoT) with one pillar- things. In addition, IoE further advances the power of the Internet to improve business and industry outcomes, and ultimately make people’s lives better by adding to the progress of IoT. The Internet of Everything will create tens of millions of new objects and sensors, all generating real-time data. “Data is money,” said Nick Jones, research vice president and distinguished analyst at Gartner. “Businesses will need big data and storage technologies to collect, analyze and store the sheer volume of information. Furthermore, to turn data into money business and IT leaders will need decisions. As they won’t have the time or the capacity to make all the decisions themselves they will need processing power.”

Objective
The aim of this special issue is to collect quality of research contributions and innovative work in the area of Big Data Analytics associated with IoE and their related applications for the benefit of research communities and society.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:
  • Fusion of Big Data and IoE for health informatics and medical services
  • Fusion of Big Data and IoE for business intelligence and finance
  • Fusion of Big Data and IoE for modern education
  • Fusion of Big Data and IoE for energy applications and services
  • Fusion of Big Data and IoE for natural science, weather forecasting and earth science
  • Fusion of Big Data and IoE for smart cities
  • Fusion of Big Data and IoE for security, privacy and trust
  • Fusion of Big Data and IoE for 5G networks and communications
  • Fusion of Big Data and IoE for mobile services and computing
  • Fusion of Big Data and IoE for the next generation architecture
  • Fusion of Big Data and IoE for any forms of predictive modeling and analytics
  • Fusion of Big Data and IoE for real world examples and case studies


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Big Data Analytics and Internet of Everything-Fusion for Various Administrations on or before December 31, 2017. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/journals/guidelines-for-submission.aspx. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Dr. Hemraj Saini
Guest Editor
International Journal of Grid and High Performance Computing (IJGHPC)
E-mail: hemraj1977@yahoo.co.in

PLEASE NOTE: All submissions should be created using the link below ↴

Special Issue On: Frontiers of Parallel and Distributed Algorithms for Edge-of-Things in Cluster Computing

Submission Due Date
4/15/2018

Guest Editors
Prof. Gunasekaran Manogaran
Prof. Thanjai Vadivel. M
Prof. Naveen Chilamkurti

Introduction
Cluster computing is a fusion of the fields of distributed, parallel, high-availability and high-performance computing. The objective of cluster computing is to solve various issues in cloud services and big data processing. Hence, cluster computing is widely used by algorithm developers, standardizing forums, network developers and system designers. Moreover, cluster computing is found to be an efficient platform for a range of parallel and distributed applications in both commercial and scientific environments. For example, cluster computing is widely used in following scientific environments, prediction of earthquakes, protein dynamic, climate change modeling, natural resource processing, e-commerce, data management services and web services.

The cloud-based Internet of Things (IoT) is used to connect a wide range of things such as vehicles, mobile devices, sensors, industrial equipments and manufacturing machines to develop a various smart systems it includes smart city and smart home, smart grid, smart industry, smart vehicle, smart health and smart environmental monitoring. These smart systems generate a large volume of data often called big data that cannot be processed by traditional data processing algorithms and applications. This would create more complexities to ensure scalability, mobility, reliability, low latency, network bandwidth consumption and energy efficiency of IoT devices while moving the IoT sensor data to the cloud. To overcome this issue, the fusion of IoT and rich cloud services are combined to create a novel technology called Edge-of-Things (EoT). In EoT, data processing occurs in part at the network edge or between the cloud-to-end that can best meet customer necessities, rather than entirely processing in a comparatively less number of massive clouds.

Objective
The main challenge in EoT is how to manage with emerging IoT environments, where a large number of connected devices participate in restricted wireless resources and where heterogeneity is ever-increasing. To overcome this issue, there is an urgent need for novel parallel and distributed algorithms for making effective decisions and interoperable solutions in emerging EoT. The aim of this special issue is to explore how the fusion of cluster computing environments such as parallel and distributed algorithms enhances an emerging EoT technology and hence present a completing panorama of the state-of-the-art scalable algorithms and architectures on applying cluster computing environments to EoT. This special issue aims to gather recent research works in emerging intelligent algorithms, parallel and distributed algorithms for EoT in cluster computing.

Recommended Topics
Topics include, but are not limited to, the following:
  • Parallel and distributed algorithms for EoT in cluster computing
  • Novel edge computing architecture for EoT in cluster computing
  • Semantic computing for EoT in cluster computing
  • Big data analytics for EoT in cluster computing
  • Programming models, APIs and toolkits for EoT in cluster computing
  • Cognitive edge computing for EoT in cluster computing
  • Autonomic resource management for EoT in cluster computing
  • Context-awareness for EoT in cluster computing
  • Intelligent algorithms for EoT in cluster computing
  • Agent based algorithms for EoT in cluster computing
  • Swarm Intelligence, Nature Inspired algorithms for EoT in cluster computing
  • Artificial intelligence and Genetic algorithms for EoT in cluster computing
  • Machine learning and deep learning for EoT in cluster computing


Submission Procedure
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).

All papers are refereed through a peer review process. All papers must be submitted online. To submit a paper, please read the Submission Procedure section. If you have any queries concerning this special issue, please email the Guest Editors using the information in the Submission Procedure section.

Submission deadline: April 15, 2018
Author notification: June 15, 2018
Final notification: Aug 15, 2018

All submissions and inquiries should be directed to the attention of:
Prof. Gunasekaran Manogaran, VIT University, Vellore, India, gunavit@gmail.com
Prof. Thanjai Vadivel. M, VelTech University, Chennai, India, thanjaivadivel@veltechuniv.edu.in
Prof. Naveen Chilamkurti, LaTrobe University, Melbourne, Australia, n.chilamkurti@latrobe.edu.au

PLEASE NOTE: All submissions should be created using the link below ↴