IEEE TNSM – SI on Data Analytics and Machine Learning for Network and Service Management 2020

When:
2 April 2020 all-day
2020-04-02T00:00:00-04:00
2020-04-03T00:00:00-04:00

Call for Papers

Network and Service analytics can harness the immense stream of operational data from clouds, to services, to social and communication networks. In the era of big data and connected devices of all varieties, analytics and machine learning have found ways to improve reliability, configuration, performance, fault and security management. In particular, we see a growing trend towards using machine learning, artificial intelligence and data analytics to improve operations and management of information technology services, systems and networks.

Research is therefore needed to understand and improve the potential and suitability of data analytics and machine learning in the context of services, systems and network management. This will provide deeper understanding and better decision making based on largely collected and available operational and service data. It will also present opportunities for improving machine learning and data analytics algorithms and methods on aspects such as reliability, dependability and scalability, as well as demonstrate the benefits of these methods in management and control systems. Moreover, there is an opportunity to define novel platforms that can harness the vast operational data and advanced data analysis algorithms to drive management decisions in networks, data centers, and clouds.

IEEE Transactions on Network and Service Management (IEEE TNSM) is a premier journal for timely publication of archival research on the management of networks, systems, services and applications. Following the success of three recent TNSM special issues on Big Data Analytics for Management in 2016, 2018, and 2019, this special issue will also focus on recent, emerging approaches and technical models that exploit data analytics and machine learning in network and service management solutions. We welcome submissions addressing the underlying challenges and opportunities, presenting novel techniques, experimental results, or theoretical approaches motivated by management problems. Survey papers that offer a perspective on related work and identify key challenges and opportunities for future research are also in the scope of the special issue. We look forward to your submissions!

Topics of Interest

Topics of interest for this special issue include, but are not limited, to the following:

  • Data Analytics, Machine Learning and Artificial Intelligence
    • Analysis, modelling and visualization
    • Operational analytics and intelligence
    • Event and log analytics, text mining
    • Outlier / Anomaly detection and prediction
    • Monitoring and measurements for management
    • Predictive analytics and real-time analytics
    • Artificial intelligence, neural networks, and deep learning for management
    • Data mining, statistical modeling, and machine learning for management
  • Application Domains and Management Paradigms
    • Cloud and network analytics
    • Social and communication networks analysis
    • Data centric management of virtualized infrastructure, clouds and data centers
    • Data centric management of software defined networks
    • Data centric management of storage resources
    • Data centric management of Internet of Things and cyber-physical systems
    • Data centric management of zero touch and driverless networks
    • Platforms for analyzing and storing logs and operational data for management tasks
    • Applications of data analytics to traffic classification, root-cause analysis, service quality assurance, IT service and resource management
    • Novel approaches to cyber-security, intrusion detection, threat analysis, and failure detection based on data analytics and machine learning

Submission Guidelines

All papers should be submitted through the IEEE Transactions on Network and Service Management manuscript submission site. Authors must indicate in the submission cover letter that their manuscript is intended for the “Data Analytics and Machine Learning for Network and Service Management” special issue. View detailed author guidelines.

Important Dates

  • Paper Submission: 2 April 2020
  • Review Results Returned: 15 June 2020
  • Revision Submission: 15 July 2020
  • Final Acceptance Notification: 15 September 2020
  • Final Paper Submission: 7 October 2020
  • Publication Date (Tentative): December 2020

Guest Editors

Nur Zincir-Heywood
Dalhousie University, Canada

Giuliano Casale
Imperial College London, UK

David Carrera
Barcelona Supercomputing Center, Spain

Amogh Dhamdhere
Amazon Web Services, USA

Takeru Inoue
NTT Laboratories, Japan

Hanan Lutfiyya
The University of Western Ontario, Canada

Taghrid Samak
Google, USA

For more information, please contact the guest editors at TNSM.SI.DAML20@gmail.com.