International Journal of Networked and Distributed Computing

Scope & Guideline

Elevating Knowledge in Distributed Computing

Introduction

Welcome to the International Journal of Networked and Distributed 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 International Journal of Networked and Distributed 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
ISSN2211-7938
PublisherSPRINGERNATURE
Support Open AccessYes
CountryNetherlands
TypeJournal
Convergefrom 2013 to 2024
AbbreviationINT J NETW DISTRIB C / Int. J. Netw. Distrib. Comput.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressCAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND

Aims and Scopes

The International Journal of Networked and Distributed Computing aims to advance the understanding and application of distributed computing systems within various domains. It focuses on innovative methodologies and technologies that enhance networked computing environments, ensuring that research remains relevant to current technological challenges.
  1. Distributed Computing Architectures:
    Research exploring various architectures for distributed computing, including cloud, edge, and fog computing, aimed at improving efficiency and performance.
  2. Network Security and Privacy:
    Studies addressing security challenges in networked and distributed systems, with a focus on privacy-preserving techniques, encryption, and secure data transmission.
  3. Internet of Things (IoT) Integration:
    Investigations into the integration and management of IoT devices within distributed networks, emphasizing smart solutions and security frameworks.
  4. Algorithm Development and Optimization:
    Development of novel algorithms for tasks such as resource management, data processing, and machine learning applications tailored for distributed environments.
  5. Blockchain Technologies:
    Research on blockchain applications across various industries, including security, data integrity, and decentralized application frameworks.
  6. Performance Evaluation and Benchmarking:
    Methodological studies that assess the performance of distributed computing systems and propose benchmarks for evaluating efficiency and effectiveness.
Recent publications indicate a dynamic shift towards several emerging themes within the scope of networked and distributed computing. These trends reflect the evolving landscape of technology and its applications.
  1. Privacy-Preserving Technologies:
    Increasing emphasis on privacy-preserving computing methods, particularly in the context of encrypted data and secure data management over distributed networks.
  2. Real-Time Data Processing and Edge Computing:
    A growing focus on leveraging edge computing for real-time data processing, particularly in IoT applications, showcasing the need for low-latency solutions.
  3. Advanced Malware Analysis and Cybersecurity:
    Research has intensified around advanced techniques for malware detection and cybersecurity analytics, reflecting the rising importance of securing distributed systems.
  4. Integration of AI with Distributed Systems:
    Emerging studies are exploring the intersection of artificial intelligence and distributed computing, particularly in optimizing system performance and enhancing decision-making.
  5. Blockchain Applications Beyond Cryptocurrency:
    An increasing number of studies are investigating blockchain's potential in diverse fields, such as sports, healthcare, and decentralized organizational structures.

Declining or Waning

While the journal has consistently covered a broad range of topics, certain areas have shown a decline in focus over recent years. This may indicate a shift in research priorities or the saturation of certain themes.
  1. Traditional Network Protocols:
    Research on older network protocols has decreased, possibly due to the emergence of more advanced and efficient alternatives suited for modern computing environments.
  2. Basic Machine Learning Techniques:
    There has been a notable reduction in studies focusing on basic machine learning methods, as the field has shifted toward more complex and specialized algorithms.
  3. General Surveys on IoT Security:
    While IoT security remains a relevant topic, generic surveys are becoming less frequent, replaced by targeted studies addressing specific challenges and solutions.

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