Big Data Mining and Analytics

Cloud computing has firmly established itself as an indispensable utility for the digital age. Cloud services and consumers expect and rely on sufficient computing power, the availability of data and media, and that these will be accessible across a range of devices. The emergence of edge and fog computing paradigm leveraging the power of Internet-of-Things and cloud datacenters has led to an increased utilisation of distributed computing applications in our daily life. Cloud services providers are capable of maintaining streamed services that are always available. However, the ever-increasing applications relying on cloud datacenters and other distributed computing paradigm is known to create new problems such as increased energy consumption, network congestion, performance overheads, whereby affecting Quality of Service and ultimately affecting the end user experience. Therefore, it is essential to leverage sound scientific principles to optimise workload execution in this distributed paradigm involving Internet of Things, edge nodes and cloud datacenters. The heterogeneity and large volume of the data generated in this distributed environment can provide with rich set of information that can help to optimise the overall processing of workloads. Intelligent approaches driven by efficient data analytics of relevant data sources can help with efficient processing of workloads such as task allocation, scheduling, migration, offloading and consolidation of workloads for optimisation. The topics of this special issue include, but are not limited to the following:

• Architectural models and patterns to achieve Utility in Clouds
• Cloud Computing middleware, stacks, tools, delivery networks and services at all layers (XaaS)
• Cloud large-scale foundations for Big Data, IoT, and real-time analytics
• Cloud-native application design, engineering and serverless/microservice implementation
• Cloud, Fog and edge/mobile devices management, hierarchy models, and business models
• High Performance Computing and the Cloud
• Integration of Cloud systems with Fog/edge and IoT devices, continuum computing
• Leading edge topics such as hybrid quantum clouds, coded computing
• Mobile and energy-efficient use of Clouds
• Networking for clouds and datacentres
• Performance analysis and modelling of cloud systems and applications
• Principles and theoretical foundations of Utility Computing
• Resource management and scalability: brokering, scheduling, migration, capacity planning, and elasticity
• Utility-driven models and mechanisms for interclouds / federations
• Virtualization, containerization, composition, orchestration and other enablers

The authors are requested to submit their full research papers complying with the general scope of the journal. The submitted papers will undergo peer review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.

SUBMISSION GUIDELINES

Papers submitted to this journal for possible publication must be original and must not be under consideration for publication in any other journals. Prospective authors should submit an electronic copy of their completed manuscript to https://mc03.manuscriptcentral.com/bdma with manuscript type as “Special Issue on Big Data Computing for Internet of Things and Utility and Cloud Computing”. Further information on the journal is available at: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8254253

IMPORTANT DATES

Deadline for submissions: December 15, 2022           

1^st round of acceptance notification: January 31, 2023

Submission of revised papers: February 28, 2023             

2^nd round of acceptance notification: March 31, 2023

Publication online (tentative): May 31, 2023

GUEST EDITORS

Prof. Lu Liu, University of Leicester, UK. Email: l.liu@leicester.ac.uk

Dr. Ovidiu Bagdasar, University of Derby, UK, Email: o.bagdasar@derby.ac.uk

Dr. John Panneerselvam, University of Leicester, UK. E-mail: j.panneerselvam@leicester.ac.uk