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International Journal of Network Management

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Factor de Impacto:
2.6
Editor:
Wiley
ISSN:
1055-7148
Vistas:
16972
Seguidores:
2
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Solicitud de Artículos

International Journal of Network Management is an academic journal published by Wiley. (ISSN 1055-7148, impact factor 2.6).

Aims and Scope Modern computer networks and communication systems are increasing in size, scope, and heterogeneity. The promise of a single end-to-end technology has not been realized and likely never will occur. The decreasing cost of bandwidth is increasing the possible applications of computer networks and communication systems to entirely new domains. Problems in integrating heterogeneous wired and wireless technologies, ensuring security and quality of service, and reliably operating large-scale systems including the inclusion of cloud computing have all emerged as important topics. The one constant is the need for network management. Challenges in network management have never been greater than they are today. The International Journal of Network Management is the forum for researchers, developers, and practitioners in network management to present their work to an international audience. The journal is dedicated to the dissemination of information, which will enable improved management, operation, and maintenance of computer networks and communication systems. The journal is peer reviewed and publishes original papers (both theoretical and experimental) by leading researchers, practitioners, and consultants from universities, research laboratories, and companies around the world. Issues with thematic or guest-edited special topics typically occur several times per year. Topic areas for the journal are largely defined by the taxonomy for network and service management developed by IFIP WG6.6, together with IEEE-CNOM, the IRTF-NMRG and the Emanics Network of Excellence. The taxonomy is available here Readership The readership of this journal is broad. Readers include network and telecommunications managers, researchers, developers, designers, consultants, vendors, and students with an interest in existing and future directions in network management. Keywords IP networks Wireless networks and cellular networks Optical networks Overlay networks Virtual networks Home networks Access networks Enterprise networks and campus networks Data center networks SCADA networks and distributed control systems Wireless sensor networks Internet of Things networks Information-centric networks Software-defined networks Multimedia services Content delivery services Cloud computing services Internet connectivity and Internet access services Internet of Things services Security services Context-aware services Information technology services Economic aspects Multi-stakeholder aspects Service level agreements Lifecycle aspects Process and workflow aspects Legal perspective Regulatory perspective Privacy aspects Fault management Configuration management Accounting management Performance management Security management Centralized management Hierarchical management Distributed management Federated management Autonomic and cognitive management Policy-based management Pro-active management Energy-aware management Quality of experience-centric management Communication protocols Middleware Overlay networks Cloud computing and cloud storage Data models, information models semantic models Information visualization Software-defined networking Network function virtualization Orchestration Operations support systems and business support systems Mathematical logic and automated reasoning Mathematical optimization Control theory Probability theory, stochastic processes, and queuing theory Machine learning Evolutionary algorithms Economic theory and game theory Network monitoring and measurements Data mining and (big) data analysis Computer simulation experiments Prototype implementation and testbed experimentation Field trials
Última actualización por Dou Sun el

Números especiales

Número especial sobre AI-driven Management and MLOps for Networks and Services Día de Entrega: 2026-10-31 The increasing scale, programmability, and heterogeneity of modern networks and digital services are driving a fundamental shift in management paradigms. Communication infrastructures now operate across cloud, edge, mobile, IoT, and domain-specific environments, where service agility and operational resilience depend on timely, intelligent, and automated management decisions. In parallel, AI is becoming an essential component of operational systems, supporting prediction, optimization, control, and decision assistance across the management stack. This evolution creates a twofold research opportunity. First, AI-driven techniques are redefining how networks and services are monitored, analyzed, optimized, and controlled. Second, the growing operational use of AI models introduces the need for robust lifecycle management practices, including data engineering, model validation, deployment, monitoring, governance, and continuous adaptation. Together, these perspectives motivate a unified view of network and service management that integrates both intelligent automation and the operational management of AI itself. This Special Issue invites original contributions on methods, architectures, systems, platforms, and operational experiences related to AI-driven management and MLOps for networks and services. We welcome work that advances theoretical foundations, reports experimental or real-world results, and addresses the practical challenges of deploying trustworthy AI in operational environments. Topics for this call for papers include but are not restricted to: AI-driven monitoring, analysis, and control for networks and services Machine learning for service assurance, fault management, and root-cause analysis Large language models and foundation models for network and service operations Reinforcement learning for adaptive orchestration and autonomous control AI-driven management for cloud-native, edge, 5G/6G, and IoT environments Data pipelines, model training, validation, deployment, and continuous delivery for network AI Monitoring, observability, and drift management for AI models in production Governance, accountability, and policy compliance for operational AI Security and privacy in AI lifecycle management and inference pipelines Robustness against adversarial manipulation, poisoning, and model misuse Resource-efficient AI for network and service management Explainability, transparency, and trust in AI-driven operational decisions Benchmarks, datasets, testbeds, and evaluation methodologies Operational case studies, deployment experiences, and lessons learned Guest Editors: Dr. Marc-Oliver Pahl IMT Atlantique France Dr. Hanan Lutfiyya University of Western Ontario Canada Dr. Stuart Slayman University College London United Kingdom Keywords: application lifecycle management; cloud computing; computer science https://onlinelibrary.wiley.com/page/journal/10991190/homepage/call-for-papers/si-2026-000414
Última actualización por Dou Sun el
Número especial sobre Best Papers of IEEE/IFIP NOMS 2024: "Towards Intelligent, Reliable, and Sustainable Network and Service Management" Día de Entrega: 2027-05-31 IEEE/IFIP NOMS 2024 was held from 6–10 May 2024 in Seoul, Republic of Korea. The NOMS 2024 theme was "Towards Intelligent, Reliable, and Sustainable Network and Service Management." Papers were submitted as full and short technical session papers, experience session papers, and dissertation papers. The topics for NOMS 2024 were: Technologies: Communication Protocols; Middleware; Overlay Networks; Peer-to-Peer Networks; Cloud Computing and Cloud Storage; Data, Information, and Semantic Models; Information Visualization; Software-Defined Networking; Network Function Virtualization; Orchestration; Operations and Business Support Systems; Control and Data Plane Programmability; Distributed Ledger Technology. Service Management: Multimedia Services; Content Delivery Services; Cloud Computing Services; Internet Connectivity and Internet Access Services; Internet of Things Services; Security Services; Context-Aware Services; Information Technology Services; Service Assurance. Functional Areas: Configuration Management; Accounting Management; Performance Management; Security Management. Management Paradigms: Centralized Management; Hierarchical Management; Distributed Management; Federated Management; Autonomic and Cognitive Management; Policy- and Intent-Based Management; Model-Driven Management; Pro-active Management; Energy-aware Management; QoE-Centric Management. Methods: Mathematical Logic and Automated Reasoning; Optimization Theories; Control Theory; Probability Theory, Stochastic Processes, and Queuing Theory; Artificial Intelligence and Machine Learning; Evolutionary Algorithms; Economic Theory and Game Theory; Monitoring and Measurements; Data Mining and (Big) Data Analysis; Computer Simulation Experiments; Testbed Experimentation and Field Trials; Software Engineering Methodologies. Guest Editors: Prof. Baek-Young Choi University of Missouri, MO, United States Prof. Myungsup Kim Korea University, Republic of Korea Prof. Roberto Riggio Marche Polytechnic University, Italy https://onlinelibrary.wiley.com/page/journal/10991190/homepage/call-for-papers/si-2024-000511
Última actualización por Dou Sun el

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