International Journal of Network Management最新文献

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148122875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148091698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Securing Multicloud Environments With SAFIRE: A Federated and Adaptive Intelligence Approach","authors":"E. Fenil,&nbsp;S. Nachiyappan,&nbsp;A. Subash Chandar,&nbsp;P. Mohan Kumar","doi":"10.1002/nem.70040","DOIUrl":"https://doi.org/10.1002/nem.70040","url":null,"abstract":"<div>\u0000 \u0000 <p>Multicloud environments provide multicloud environment provision of cyber-attacks demands to have flexible security mechanisms, which can dynamically respond to evolving patterns of attacks. In this paper, a novel framework of Self-Adaptive Federated Intelligence known as Self-Adaptive Federated Intelligence of Real-time security Enforcement (SAFIRE) is introduced, which implements a combination of real-time security intelligence extraction, cross-cloud threat correlation, and adaptive learning to provide a more efficient security solution. This model uses a security insight system that trains itself to analyze multicloud attack patterns dynamically in order to provide real-time detection of advanced threats. A dynamic learning mechanism that provides changes in the dynamic trends in security decision-making is an important aspect of the model. A hierarchical classification module also divides the different types of attacks and corrects mitigation measures based on this. By employing an attention-based system of cross-cloud adaptation, the suggested system will enable a number of cloud service providers to collaborate toward greater levels of security in a noncentralized fashion. The key strength of this work is its potential to trace the pattern of multicloud attacks, adjust security policy in real-time situations, and enhance its threat detection with limited reliance on the centralized view of data accumulation. As experimental findings show, the proposed methodology is more accurate (98.9%), less prone to false positives (1.9), lower response time (180 ms), and less resource-intensive (4%). The findings indicate that the model takes minimal time to adapt to emerging cyber-attacks with high detection and low overhead rates and is therefore interesting as a solution to secure cloud infrastructure of the future.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147684098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Securing Multicloud Environments With SAFIRE: A Federated and Adaptive Intelligence Approach","authors":"E. Fenil,&nbsp;S. Nachiyappan,&nbsp;A. Subash Chandar,&nbsp;P. Mohan Kumar","doi":"10.1002/nem.70040","DOIUrl":"https://doi.org/10.1002/nem.70040","url":null,"abstract":"<div>\u0000 \u0000 <p>Multicloud environments provide multicloud environment provision of cyber-attacks demands to have flexible security mechanisms, which can dynamically respond to evolving patterns of attacks. In this paper, a novel framework of Self-Adaptive Federated Intelligence known as Self-Adaptive Federated Intelligence of Real-time security Enforcement (SAFIRE) is introduced, which implements a combination of real-time security intelligence extraction, cross-cloud threat correlation, and adaptive learning to provide a more efficient security solution. This model uses a security insight system that trains itself to analyze multicloud attack patterns dynamically in order to provide real-time detection of advanced threats. A dynamic learning mechanism that provides changes in the dynamic trends in security decision-making is an important aspect of the model. A hierarchical classification module also divides the different types of attacks and corrects mitigation measures based on this. By employing an attention-based system of cross-cloud adaptation, the suggested system will enable a number of cloud service providers to collaborate toward greater levels of security in a noncentralized fashion. The key strength of this work is its potential to trace the pattern of multicloud attacks, adjust security policy in real-time situations, and enhance its threat detection with limited reliance on the centralized view of data accumulation. As experimental findings show, the proposed methodology is more accurate (98.9%), less prone to false positives (1.9), lower response time (180 ms), and less resource-intensive (4%). The findings indicate that the model takes minimal time to adapt to emerging cyber-attacks with high detection and low overhead rates and is therefore interesting as a solution to secure cloud infrastructure of the future.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147684132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latency- and Load-Aware MEC Host Selection in Simu5G: A Lightweight Orchestration Policy for Delay-Sensitive 5G Applications","authors":"Atakan Ozcan,&nbsp;Deniz Berke Ozsoy,&nbsp;Mohammed Al-Hubaishi","doi":"10.1002/nem.70038","DOIUrl":"https://doi.org/10.1002/nem.70038","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;p&gt;Multiaccess edge computing (MEC) reduces end-to-end (E2E) latency by offloading computation from user equipment (UE) to nearby edge hosts, but host-selection policies in simulators such as &lt;i&gt;Simu5G&lt;/i&gt; typically focus on service availability or CPU headroom. They do not explicitly account for dynamic UE–host latency and can therefore steer delay-sensitive flows to topologically distant or temporarily congested hosts, inflating tail delay and limiting effective throughput. We extend &lt;i&gt;Simu5G&lt;/i&gt;'s ETSI-compliant MEC orchestrator with &lt;span&gt;LatencyAwareSelectionBased&lt;/span&gt;, a lightweight host-selection policy that jointly accounts for (i) a dynamic UE–host delay estimate derived from measurable run-time delay statistics and smoothed via an exponential moving average and (ii) the host's normalized CPU load. These two signals are combined in a simple score, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;S&lt;/mi&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mi&gt;h&lt;/mi&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;mo&gt;=&lt;/mo&gt;\u0000 &lt;mover&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;L&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;˜&lt;/mo&gt;\u0000 &lt;/mover&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mi&gt;h&lt;/mi&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mfenced&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;mo&gt;+&lt;/mo&gt;\u0000 &lt;mi&gt;α&lt;/mi&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mover&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;˜&lt;/mo&gt;\u0000 &lt;/mover&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mi&gt;h&lt;/mi&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mfenced&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ S(h)=tilde{L}(h)kern0.3em left(1+alpha kern0.3em tilde{C}(h)right) $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, controlled by a single trade-off parameter &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;α&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ alpha $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;. The policy is implemented as a plug-in selection module activated through &lt;i&gt;Simu5G&lt;/i&gt;'s native &lt;span&gt;selectionPolicy&lt;/span&gt; hook, requiring only minimal changes to existing scenarios and preserving the standard orchestration pipeline. We evaluate the proposed policy in &lt;i&gt;Simu5G&lt;/i&gt;'s &lt;span&gt;MultiMecHost&lt;/span&gt; scenario under three operating points (Best, Moderate, and Worst) and an additional multitenant burst configuration with up to 20 UEs generating bursty arrivals. Using Simu5G scalar outputs, we take downlink MAC delay and per-UE throughput as primary metrics and also examine CPU-only","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147288479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latency-Aware Proactive Event Monitoring Scheme in SDN/P4-Based IoT Networks","authors":"Bong-Hwan Oh","doi":"10.1002/nem.70037","DOIUrl":"https://doi.org/10.1002/nem.70037","url":null,"abstract":"<div>\u0000 \u0000 <p>The combination of control plane flexibility and data plane programmability enables the emergence of groundbreaking features in network systems. One of the key advancements is the provision of new network monitoring capabilities. This innovation has the potential to meet diverse demands arising from unique characteristics and specific requirements of certain network infrastructures, such as the Internet of Things (IoT). However, existing monitoring approaches primarily focus on assessing the overall network condition and lack the capability to accurately analyze specific target events. This presents a significant challenge for network management, where identifying and tracking critical events is a fundamental requirement. To address this limitation, this paper proposes a latency-aware proactive event monitoring (LPEM) scheme, a novel monitoring mechanism tailored to IoT requirements. LPEM leverages the programmable features of software-defined networking (SDN) and Programming Protocol-Independent Packet Processors (P4) to identify specified events and proactively report relevant information to a controller. This enables the controller to track specific events while simultaneously monitoring the network latency they experience in the network. Measurement results demonstrate that LPEM effectively tracks target events and monitors their experienced link latency, regardless of variations in network traffic. Furthermore, LPEM enables real-time monitoring with millisecond-level response times and enhances monitoring reliability by addressing both the loss of monitoring data and unexpected events.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146176097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-Aware Controller Placement With Delay Guarantees for In-Band SDN","authors":"Tomofumi Kondo,&nbsp;Luis Guillen,&nbsp;Satoru Izumi,&nbsp;Toru Abe,&nbsp;Takuo Suganuma","doi":"10.1002/nem.70036","DOIUrl":"https://doi.org/10.1002/nem.70036","url":null,"abstract":"<p>Software-defined networking (SDN) enables flexible, programmable networks, but in large deployments, poor controller placement can raise latency and energy use. This paper presents a practical in-band SDN model and an optimization method that jointly accounts for control-plane delay and device power consumption to place controllers and configure switches. We formulate the problem as a binary integer programming (BIP) that decides controller locations, which switches remain active, and port bit-rates and routes. Experiments on a large WAN topology (Janos-US) show the approach can cut total network energy by up to 15% while keeping control-plane delays within required bounds, offering network operators a straightforward way to trade responsiveness for energy savings.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.70036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146002233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Load Balancing Based on Consistent Hashing in P4 Switches","authors":"Yu-An Shi,&nbsp;Kuan-Ting Liu,&nbsp;Li-Der Chou","doi":"10.1002/nem.70033","DOIUrl":"https://doi.org/10.1002/nem.70033","url":null,"abstract":"<div>\u0000 \u0000 <p>In recent years, the emergence of new network architectures has seen substantial growth. Among these advancements, distributed server architectures and server load balancing have gradually become key areas of focus. This paper introduces a mechanism called consistent hashing with congestion awareness (CHCA), designed to optimize load balancing. CHCA enhances traditional algorithms by minimizing data migration when servers are added or removed. Additionally, this mechanism incorporates the least connections method to prevent certain servers from becoming overloaded due to persistent traffic, thereby mitigating server hotspots. Aiming to support this mechanism, two custom headers, the forward header and the MRI header, are introduced using P4 switches. The forward header allows P4 switches to make dynamic packet forwarding decisions based on optimal paths at runtime, eliminating the need for a static routing table. Meanwhile, the MRI header records the load information from all traversed P4 switches, enabling the load balancing forwarding strategy to adapt in real time based on current network conditions.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145686436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Arbitrage Occurrences With Machine Learning and Improved Decision Threshold Level in Live-Trading Crypto Environments","authors":"Kristína Okasová,&nbsp;Michal Géci,&nbsp;Kristián Košťál","doi":"10.1002/nem.70030","DOIUrl":"https://doi.org/10.1002/nem.70030","url":null,"abstract":"<p>Cryptocurrencies represent a significantly utilized class of digital assets, encompassing a diverse array of tokens and coins available for trading purposes. In this study, the integration of machine learning algorithms with an arbitrage trading strategy across cryptocurrency exchanges is explored. The objective is to scrutinize prominent cryptocurrency pairs characterized by high volatility, vulnerability to speculation, regulatory gaps, liquidity constraints, and heavy-tail distribution, with the intention of training the model to predict the potential for arbitrage. To differentiate from competitors who await rare arbitrage opportunities, a novel approach is introduced to enhance arbitrage profitability. The primary innovation of this study lies in demonstrating the capability to predict profitable arbitrage opportunities in discrete intervals in advance, by incorporating sophisticated confidence level metrics to initiate arbitrage trades only when the model's predictions demonstrate substantial certainty. The findings indicate that the profitability of the entire strategy exceeds 100% within a 1-week timeframe.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.70030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145686508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Literature Survey on Resource Allocation for Network Function Virtualization With and Without Machine Learning in Cloud Computing","authors":"Khaled Gadouh,&nbsp;Hend Koubaa","doi":"10.1002/nem.70034","DOIUrl":"https://doi.org/10.1002/nem.70034","url":null,"abstract":"<div>\u0000 \u0000 <p>The convergence of cloud computing, machine learning (ML), and network function virtualization (NFV) offers significant opportunities for advancing network infrastructure management by providing efficient, flexible, and scalable resource utilization. This study aims to provide a comprehensive review of the primary challenges and explores state-of-the-art solutions in cloud computing for resource allocation (RA) specific to NFV environments. The paper highlights the importance of adopting multifaceted strategies to optimize RA and enhance the efficiency, and adaptability of cloud systems that handle RA without ML, and with ML in NFV settings. In addition, gap identification is also discussed, emphasizing many needs: (1) the need for extending the NFV RA in the case of wireless networks; (2) the need for enhanced security protocols to fully harness the potential of ML within resource function virtualization (RFV) environments, ensuring that network infrastructures are not only efficient but also resilient and secure; and (3) the need to develop more efficient ML-based RA for NFV, considering the trade-off between performance and accuracy.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"36 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145626206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}