IEEE Transactions on Network and Service Management最新文献

{"title":"Energy-Efficient UAV-Assisted Federated Learning: Trajectory Optimization, Device Scheduling, and Resource Management","authors":"Zhenyu Fu;Juan Liu;Yuyi Mao;Long Qu;Lingfu Xie;Xijun Wang","doi":"10.1109/TNSM.2025.3531237","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3531237","url":null,"abstract":"The emergence of intelligent mobile technologies and the widespread adoption of 5G wireless networks have made Federated Learning (FL) a promising method for protecting privacy during distributed model training. However, traditional FL frameworks rely on static aggregators such as base stations, encountering obstacles such as increased energy demands, frequent disconnections, and poor model performance. To address these issues, this paper investigates an innovative aUtonomous Aerial Vehicle (UAV)-assisted FL framework, aiming to utilize UAVs as mobile model aggregators to collaborate with devices in training models, while minimizing the total energy consumption of devices and ensuring that FL can achieve the target model accuracy. By adopting the Distributed Approximate NEwton (DANE) method for local optimization, we analyze the convergence of FL and derive device scheduling constraints that aid in convergence. Accordingly, we formulate a problem of minimizing the total energy consumption of devices, integrating a constraint on global model accuracy, and jointly optimizing the UAV trajectory, device scheduling, bandwidth allocation, time slot lengths, as well as the uplink transmission power, CPU frequency, and local convergence accuracy. Then, we decompose this non-convex optimization problem into three subproblems and propose an iterative algorithm based on Block Coordinate Descent (BCD) with convergence guarantee. Simulation results indicate that, compared with various benchmark methods, our proposed UAV-assisted FL framework significantly reduces the total energy consumption of devices and achieves an improved trade-off between energy and convergence accuracy.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 2","pages":"974-988"},"PeriodicalIF":4.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"DRL-Based Maximization of the Sum Cross-Layer Achievable Rate for Networks Under Jamming","authors":"Abdul Basit;Muddasir Rahim;Tri Nhu Do;Nadir Adam;Georges Kaddoum","doi":"10.1109/TNSM.2025.3534028","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3534028","url":null,"abstract":"In quasi-static wireless networks characterized by infrequent changes in the transmission schedules of user equipment (UE), malicious jammers can easily deteriorate network performance. Accordingly, a key challenge in these networks is managing channel access amidst jammers and under dynamic channel conditions. In this context, we propose a robust learning-based mechanism for channel access in multi-cell quasi-static networks under jamming. The network comprises multiple legitimate UEs, including predefined UEs (pUEs) with stochastic predefined schedules and an intelligent UE (iUE) with an undefined transmission schedule, all transmitting over a shared, time-varying uplink channel. Jammers transmit unwanted packets to disturb the pUEs’ and the iUE’s communication. The iUE’s learning process is based on the deep reinforcement learning (DRL) framework, utilizing a residual network (ResNet)-based deep Q-Network (DQN). To coexist in the network and maximize the network’s sum cross-layer achievable rate (SCLAR), the iUE must learn the unknown network dynamics while concurrently adapting to dynamic channel conditions. Our simulation results reveal that, with properly defined state space, action space, and rewards in DRL, the iUE can effectively coexist in the network, maximizing channel utilization and the network’s SCLAR by judiciously selecting transmission time slots and thus avoiding collisions and jamming.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 2","pages":"1295-1313"},"PeriodicalIF":4.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Self-Adaptive Dynamic In-Band Network Telemetry Orchestration for Balancing Accuracy and Stability","authors":"Tianhao Ouyang;Haipeng Yao;Wenji He;Tianle Mai;Fu Wang;F. Richard Yu","doi":"10.1109/TNSM.2025.3530432","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3530432","url":null,"abstract":"In-band network telemetry (INT) is an emerging network measurement technique that offers real-time and fine-grained visualization capabilities for networks. However, the utilization of INT for network measurement introduces additional overheads to the network. The process of data collection consumes extra bandwidth resources, and adjustments to the data collection scheme can impact network stability. Additionally, the INT orchestration scheme requires adaptation to dynamics in the network to improve measurement accuracy. Therefore, striking a balance between accuracy and stability becomes a critical problem. In this paper, our focus lies in the trade-off between measurement accuracy and network stability. We consider the long-term orchestration of multiple telemetry tasks, rationally deploying distinct telemetry tasks to different application flows. To address the challenge, we propose a self-adaptive Dynamic INT Orchestration scheme, D-INTO. Specifically, we formulate a stochastic optimization problem for dynamic INT orchestration. Then we employ Lyapunov optimization to decouple the stochastic optimization problem and use surrogate Lagrangian relaxation to construct a polynomial-time approximation algorithm. Theoretical analysis and experimental results demonstrate that our proposed D-INTO outperforms existing schemes in terms of adaptability to the network dynamics.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 2","pages":"1514-1530"},"PeriodicalIF":4.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143871110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Path Selection via Mutual Coherence Optimization in Network Monitoring","authors":"XiaoBo Fan","doi":"10.1109/TNSM.2025.3532343","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3532343","url":null,"abstract":"Periodically monitoring the state of internal links is important for network diagnosis. One of the major problems in tomography-based network monitoring is to select which paths to measure. In this paper, we propose a new path selection scheme by means of optimizing the mutual coherence of the routing matrix. The proposed scheme exploits the sparse characteristic of link status and follows the matrix design methods in sparse signal theory. By picking the paths with the minimum average mutual coherence, we can recover a sparse vector more accurately. The effectiveness of the proposed algorithms is analyzed theoretically. We conduct simulation experiments of delay estimation on both synthetic and real topologies. The results demonstrate that our scheme can select the most useful paths for network tomography with lowest cost in an acceptable time.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 2","pages":"1461-1472"},"PeriodicalIF":4.7,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Properties of Horizontal Pod Autoscaling Algorithms and Application for Scaling Cloud-Native Network Functions","authors":"Tien Van Do;Nam H. Do;Csaba Rotter;T. V. Lakshman;Csaba Biro;Tamas Bérczes","doi":"10.1109/TNSM.2025.3532121","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3532121","url":null,"abstract":"With the growing adoption of network function virtualization, telco core network elements and network functions will increasingly be designed and deployed as cloud-native application instances. To ensure the efficient use of virtualised resources and meet diverse requirements for quality of services a resource scaling algorithm is used to scale the number of application instances up or down depending on variations in offered traffic from customers. Most of the observed performance metrics for a service are a function of the current customer traffic and the current number of application instances providing the service. The ubiquitous use of Kubernetes, the popular open-source framework for deployment and management of cloud-native functions, has resulted in variants of the Kubernetes Horizontal Pod Autoscaling (HPA) algorithm being widely used to change the number of application instances providing network functions as traffic demands vary. This change is done by determining whether a selected performance metric of interest is outside a range set by two input parameters (the desired metric value and the tolerance parameter). In this paper, we investigate the characteristics of the HPA algorithms and prove that there are only a finite number of intervals for its tolerance parameter. Further any choice of the tolerance parameter from each interval leads to similar computational decisions on the recommended number of application instances. As a consequence, the number of parameter setting choices is finite due to the rule that the desired metric value can only be an integer in specific ranges. Additionally, we investigate the use of HPA for scaling application instances that provide session-based services and establish lower and the upper bounds for the performance of the HPA scaling algorithms in this scenario. Our contributions can help operators find appropriate parameter settings efficiently - administrators of Kubernetes clusters only need to select parameters from a limited and finite number of choices (instead of infinite) for scaling cloud-native applications.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 2","pages":"1889-1898"},"PeriodicalIF":4.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Programmable Real-Time Scheduling of Disaggregated Network Functions: A Theoretical Model","authors":"Tamás Lévai;Balázs Vass;Gábor Rétvári","doi":"10.1109/TNSM.2025.3531989","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3531989","url":null,"abstract":"Novel telecommunication systems build on a cloudified architecture running softwarized network services as disaggregated virtual network functions (VNFs) on commercial off-the-shelf (COTS) hardware to improve costs and flexibility. Given the stringent processing deadlines of modern applications, these systems are critically dependent on a closed-loop control algorithm to orchestrate the execution of the disaggregated components. At the moment, however, the formal model for implementing such real-time control loops is mostly missing. In this paper, we introduce a new real-time VNF execution environment that runs entirely on COTS hardware. First, we define a comprehensive formal model that enables us to reason about packet processing delays across disaggregated VNF processing chains analytically. Then we integrate the model into a gradient-optimization control algorithm to provide optimal scheduling for real-time infocommunication services in a programmable way. We present experimental evidence that our model gives a proper delay estimation on a real software switch. We evaluate our control algorithm on multiple representative use cases using a software switch simulator. Our results show the algorithm drives the system to a real-time capable state in just a few control periods even in case of complex services.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 1","pages":"485-498"},"PeriodicalIF":4.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Priority-Dominated Traffic Scheduling Enabled ATS in Time-Sensitive Networking","authors":"Lihui Zhang;Gang Sun;Rulin Liu;Wei Quan;Hongfang Yu;Dusit Niyato","doi":"10.1109/TNSM.2025.3532080","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3532080","url":null,"abstract":"Time-Sensitive Networking (TSN) employs shaping mechanisms such as Time-Aware Shaping (TAS) and Cyclic Queuing and Forwarding (CQF), which depend heavily on precise time synchronization and complex Gate Control Lists (GCL) configurations, limiting their effectiveness in large-scale mixed traffic networks like those in vehicular systems. In response, IEEE 802.1Qcr protocol introduces the Asynchronous Traffic Shaping (ATS) mechanism, based on Urgency-Based Schedulers (UBS), to asynchronously address diverse traffic needs and ensure low and predictable latency. Nonetheless, no traffic scheduling algorithm exists that can be directly applied to ATS shapers in generic large-scale traffic scenarios to solve for fixed end-to-end (E2E) delay constraints and the number of priority queues.In this paper, we propose an urgency-based fast flow scheduling algorithm (UBFS) to address the issue. UBFS leverages domain-specific optimizing strategies with a focus on traffic delay urgency inspired by greedy algorithm for priority allocation across hops and flows, complemented by preprocessing for scenario solvability and dynamic verification to ensure scheduling feasibility. We benchmark UBFS against the method with both scalability and solution quality in typical network topology and demonstrate that UBFS achieves more rapid scheduling within seconds across linear, ring, and star topologies. Notably, UBFS significantly outperforms the baseline algorithm in scheduling efficiency in mixed and large-scale traffic environments, scheduling a larger number of flows. UBFS also reduces time costs by 2-10 times in delay-sensitive environments and by more than 10 times in large-scale scenarios, effectively balancing time efficiency, performance and scalability, thereby enhancing its applicability in real-world industrial settings.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 1","pages":"470-484"},"PeriodicalIF":4.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Elastic Cross-Layer Orchestration of Network Policies in the Kubernetes Stack","authors":"Gerald Budigiri;Christoph Baumann;Eddy Truyen;Wouter Joosen","doi":"10.1109/TNSM.2025.3531040","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3531040","url":null,"abstract":"Packaging applications in Containers, dynamically managed using a cluster orchestrator, is the de-facto approach for deployment of cloud-native applications. When Containers run inside Virtual Machines (VMs) to protect infrastructural assets, Network Policies at the Container layer and Security Groups at the VM layer provide complementary firewall mechanisms that strengthen defenses against lateral movement of attackers. However, least-privilege network policies at the Container layer may not always be consistent with statically defined, over-permissive Security Groups at the VM layer. This is especially a problem with low-latency configuration of Container networking solutions that requires every opened Container protocol, port and traffic direction also to be opened at the VM layer. In any post-exploitation scenario where attackers escape from within an already compromised or infected Container, such over-permissive Security Groups do not prevent the attacker from spreading across VMs to find powerful tokens for accessing the cluster orchestrator. In this paper, we introduce GrassHopper, a fast and dynamic cross-layer enforcement approach for Network Policies, which automatically generates Security Group configurations from dynamically verified Network Policies and Container scheduling decisions. Given the low-latency context, the design of GrassHopper must ensure that dynamically generated Security Group rules come in a timely manner to effect before the newly scheduled Containers become ready to serve traffic. We evaluate the performance of GrassHopper on a Kubernetes cluster running on OpenStack at the network and application level. In comparison to a Security Group management approach that is not scheduling-aware, our findings show that for low-latency applications GrassHopper can reduce the network attack surface between VMs at a ratio of 78-to-99%, while causing no network performance overhead at the application level with respect to latency and throughput.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 2","pages":"2031-2058"},"PeriodicalIF":4.7,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Optimizing Traffic Management in Airborne Power Line Communication Networks: A Credit-Based Shaping Approach Using Network Calculus","authors":"Ruowen Yan;Qiao Li;Huagang Xiong","doi":"10.1109/TNSM.2025.3529871","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3529871","url":null,"abstract":"As the aviation industry progresses towards More Electric Aircraft (MEA), the demand for robust and efficient data communication systems intensifies. Traditional fieldbus systems are burdened by high installation costs and substantial weight due to extensive cabling requirements. The Power Line Communication (PLC) technology presents a promising alternative; however, its adaptation to the stringent real-time demands of airborne environments poses significant challenges. To address this, this paper introduces a novel Credit-Based Shaper with Channel Contention (CBSCC) mechanism designed to optimize traffic management in airborne PLC networks. This mechanism operates at the Medium Access Control (MAC) layer of the HomePlug AV 2 protocol, employing a dynamic configuration approach informed by Network Calculus (NC). This approach utilizes End-to-End Delay (E2ED) requirements of data flows and network configuration details to calculate the parameters for the CBSCC traffic shaper. Comprehensive simulations conducted with OMNeT++ demonstrate the efficacy of CBSCC, demonstrating marked improvements in E2ED satisfaction for all data frames, reduced average access delays, and enhanced fairness across different priority levels compared to the HomePlug AV2 protocol and previous traffic management strategies. The findings confirm that the CBSCC mechanism substantially alleviates the starvation of lower-priority traffic, boosts network efficiency, and ensures robust real-time guarantees essential for the safety and reliability of airborne communication systems. This research represents a substantial advancement over existing solutions, aligning with the evolving needs of MEA implementations.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 2","pages":"1437-1449"},"PeriodicalIF":4.7,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143871107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"MDTL: Maliciously Secure Distributed Transfer Learning Based on Replicated Secret Sharing","authors":"Zhengran Tian;Hao Wang;Zhi Li;Ziyu Niu;Xiaochao Wei;Ye Su","doi":"10.1109/TNSM.2025.3529471","DOIUrl":"https://doi.org/10.1109/TNSM.2025.3529471","url":null,"abstract":"As data continues to grow at an unprecedented rate and informationization accelerates, concerns over data privacy have become more prominent. In image classification tasks, the challenge of insufficient labeled data is common. Transfer learning, an effective and important machine learning method, can address this issue by leveraging knowledge from the source domain to enhance performance in the target domain. However, existing privacy-preserving transfer learning schemes continue to face challenges related to low security and multiple rounds of communication. In the following works, we design a three-party privacy-preserving transfer learning protocol based on the Joint Distributed Adaptation (JDA) algorithm, which ensures malicious security under an honest majority model. To realize this protocol, we designed a series of sub-protocols for constant-round communication, including distributed solving of eigenvalues and eigenvectors based on replicated secret sharing techniques. Compared to existing work, our protocol requires fewer rounds and satisfies malicious security. We provide formal security proofs for the designed protocol and assess its performance using real datasets. Our protocol for computing the eigenvalues of matrices in a given dimension is approximately 2.5 times faster than existing methods. The results of the experiments demonstrate both the security and effectiveness of the proposed approach.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"22 1","pages":"877-891"},"PeriodicalIF":4.7,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}