COMPUTING

Scope & Guideline

Advancing the Frontiers of Computational Research

Introduction

Welcome to the COMPUTING information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of COMPUTING, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN0010-485x
PublisherSPRINGER WIEN
Support Open AccessNo
CountryAustria
TypeJournal
Convergefrom 1966 to 2024
AbbreviationCOMPUTING / Computing
Frequency12 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressPrinz-Eugen-Strasse 8-10, A-1040 Vienna, AUSTRIA

Aims and Scopes

The journal 'COMPUTING' focuses on advancing the field of computer science through innovative research across various domains. Its primary aim is to publish high-quality papers that address theoretical, experimental, and practical aspects of computing, with an emphasis on interdisciplinary approaches and applications.
  1. Cloud Computing and Virtualization:
    Research in this area explores the optimization of cloud resources, virtual machine migration, and multi-tenancy challenges, focusing on enhancing efficiency and performance through various algorithms and frameworks.
  2. Machine Learning and Artificial Intelligence:
    The journal emphasizes the application of machine learning techniques in diverse fields such as healthcare, IoT, and cybersecurity, aiming to improve predictive capabilities and decision-making processes.
  3. Internet of Things (IoT) and Edge Computing:
    Papers often discuss the integration of IoT with edge computing paradigms, focusing on resource management, data processing, and the development of smart environments.
  4. Blockchain Technology and Security:
    The journal publishes research on blockchain applications, including smart contracts and security mechanisms, addressing challenges in transparency, privacy, and efficiency.
  5. Optimization Algorithms and Techniques:
    A significant portion of the research involves developing and refining optimization algorithms for various computing environments, including task scheduling, resource allocation, and energy management.
  6. Network Function Virtualization (NFV) and Software-Defined Networking (SDN):
    This area covers the design and implementation of flexible network architectures and protocols, focusing on improving performance and scalability in dynamic environments.
  7. Data Management and Analysis:
    Research in this scope includes methodologies for managing and analyzing large datasets, with a focus on machine learning, data mining, and knowledge discovery.
  8. Smart Cities and Urban Computing:
    The journal addresses the challenges of urban environments through computing technologies, focusing on traffic management, energy efficiency, and citizen engagement.
Recent publications in the journal have highlighted several emerging themes that are gaining traction among researchers. These trends reflect the changing landscape of computing and the increasing importance of interdisciplinary approaches.
  1. Federated Learning and Privacy-Preserving Techniques:
    There is a noticeable increase in research focusing on federated learning, emphasizing privacy preservation in data sharing and analysis, particularly in sensitive domains like healthcare.
  2. AI and Sustainability:
    Emerging studies explore the intersection of artificial intelligence and sustainability, addressing how computing technologies can contribute to environmental conservation and resource efficiency.
  3. Smart Healthcare Solutions:
    Research related to smart healthcare, particularly leveraging IoT and machine learning for disease prediction and management, is on the rise, reflecting the demand for innovative healthcare solutions.
  4. Enhanced Data Analytics for Decision Support:
    The trend towards advanced data analytics techniques that support decision-making processes in various sectors, including finance, logistics, and urban planning, is becoming more prominent.
  5. Dynamic Resource Management in Cloud and Edge Computing:
    Papers increasingly focus on dynamic resource management strategies that adapt to real-time demands in cloud and edge environments, highlighting the need for flexible and responsive computing solutions.
  6. Cybersecurity Innovations:
    With the growing prevalence of cyber threats, there is a strong emphasis on innovative cybersecurity measures, including machine learning-based detection systems and blockchain applications.

Declining or Waning

As the field of computing evolves, certain research areas within the journal have shown signs of declining prominence. This may reflect shifts in technological focus or the saturation of prior research themes.
  1. Traditional Software Engineering Practices:
    Topics related to traditional software engineering methodologies have seen a decrease in publication frequency, possibly due to the rise of agile and DevOps practices that prioritize flexibility and rapid iteration.
  2. Static Security Models:
    Research focused on static security models for software applications has diminished, as there is a growing recognition of the need for adaptive and dynamic security measures in response to evolving threats.
  3. Legacy Systems Integration:
    The integration of legacy systems into modern computing environments is less frequently addressed, suggesting a shift toward developing new solutions rather than adapting older technologies.
  4. Generalized Theoretical Computer Science:
    Theoretical explorations without direct application or relevance to current technological challenges are less prevalent, indicating a trend towards more applied research that addresses real-world problems.

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