IEEE Transactions on Network and Service Management最新文献_第9页

Node-Oriented Slice Reconfiguration Based on Spatial and Temporal Traffic Prediction in Metro Optical Networks 基于城域光网络时空流量预测的节点导向切片重组

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-09-02 DOI: 10.1109/TNSM.2024.3453381

Bowen Bao;Hui Yang;Qiuyan Yao;Jie Zhang;Bijoy Chand Chatterjee;Eiji Oki

{"title":"Node-Oriented Slice Reconfiguration Based on Spatial and Temporal Traffic Prediction in Metro Optical Networks","authors":"Bowen Bao;Hui Yang;Qiuyan Yao;Jie Zhang;Bijoy Chand Chatterjee;Eiji Oki","doi":"10.1109/TNSM.2024.3453381","DOIUrl":"10.1109/TNSM.2024.3453381","url":null,"abstract":"Given the spring-up of diverse new applications with different requirements in metro optical networks, network slicing provides a virtual end-to-end resource connection with customized service provision. To improve the quality-of-service (QoS) of slices with long-term operation in networks, it is beneficial to reconfigure the slice adaptively, referring to the future traffic state. Considering the busy-hour Internet traffic with daily human mobility, the tidal pattern of traffic flow occurs in metro optical networks, expressing both temporal and spatial features. To achieve high QoS of slices, this paper proposes a node-oriented slice reconfiguration (NoSR) scheme to reduce the penalty of slices, where a gradient-based priority strategy is designed to reduce the penalties of slices overall penalties in reconfiguration. Besides, given that a precise traffic prediction model is essential for efficient slice reconfiguration with future traffic state, this paper presents the model combining the graph convolutional network (GCN) and gated recurrent unit (GRU) to extract the traffic features in space and time dimensions. Simulation results show that the presented GCN-GRU traffic prediction model achieves a high forecasting accuracy, and the proposed NoSR scheme efficiently reduces the penalty of slices to guarantee a high QoS in metro optical networks.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6731-6743"},"PeriodicalIF":4.7,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187120","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}

引用次数: 0

Energy-Efficient and Latency-Aware Data Routing in Small-World Internet of Drone Networks 小型世界无人机互联网络中的高能效和延迟感知数据路由选择

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-30 DOI: 10.1109/TNSM.2024.3452414

Sreenivasa Reddy Yeduri;Sindhusha Jeeru;Om Jee Pandey;Linga Reddy Cenkeramaddi

{"title":"Energy-Efficient and Latency-Aware Data Routing in Small-World Internet of Drone Networks","authors":"Sreenivasa Reddy Yeduri;Sindhusha Jeeru;Om Jee Pandey;Linga Reddy Cenkeramaddi","doi":"10.1109/TNSM.2024.3452414","DOIUrl":"10.1109/TNSM.2024.3452414","url":null,"abstract":"Recently, drones have attracted considerable attention for sensing hostile areas. Multiple drones are deployed to communicate and coordinate sensing and data transfer in the Internet of Drones (IoD) network. Traditionally, multi-hop routing is employed for communication over long distances to increase the network’s lifetime. However, multi-hop routing over large-scale networks leads to energy imbalance and higher data latency. Motivated by this, in this paper, a novel framework of energy-efficient and latency-aware data routing is proposed for Small-World (SW)-IoD networks. We started with an optimization problem formulation in terms of network delay, energy consumption, and reliability. Then, the formulated mixed integer problem is solved by introducing the Small-World Characters (SWC) into the conventional IoD network to form the SW-IoD network. Here, the proposed framework introduces SWC by removing a few existing edges with the least edge weight from the traditional network and introducing the same number of long-range edges with the highest edge weight. We present the simulation results corresponding to packet delivery ratio, network lifetime, and network delay for the performance comparison of the proposed framework with state-of-the-art approaches such as the conventional SWC method, LEACH, Modified LEACH, Canonical Particle Multi-Swarm (PMS) method, and conventional shortest path routing algorithm. We also analyze the effect of the location of the ground control station, the velocity of the drones, and the different heights of layers on the performance of the proposed framework. Through experiments, the superiority of the proposed method is proven to be better when compared to other methods. Finally, the performance evaluation of the proposed model is tested on a network simulator (NS3).","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6555-6565"},"PeriodicalIF":4.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187265","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}

引用次数: 0

Edge Computing and Few-Shot Learning Featured Intelligent Framework in Digital Twin Empowered Mobile Networks 数字孪生移动网络中的边缘计算和快速学习特色智能框架

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-30 DOI: 10.1109/TNSM.2024.3450993

Yirui Wu;Hao Cao;Yong Lai;Liang Zhao;Xiaoheng Deng;Shaohua Wan

{"title":"Edge Computing and Few-Shot Learning Featured Intelligent Framework in Digital Twin Empowered Mobile Networks","authors":"Yirui Wu;Hao Cao;Yong Lai;Liang Zhao;Xiaoheng Deng;Shaohua Wan","doi":"10.1109/TNSM.2024.3450993","DOIUrl":"10.1109/TNSM.2024.3450993","url":null,"abstract":"Digital twins (DT) and mobile networks have evolved forms of intelligence in Internet of Things (IoT). In this work, we consider a Digital Twin Mobile Network (DTMN) scenario with few multimedia samples. Facing challenges of knowledge extraction with few samples, stable interaction with dynamic changes of multimedia data, time and privacy saving in low-resource mobile network, we propose an edge computing and few-shot learning featured intelligent framework. Considering time-sensitive property of transmission and privacy risks of directly uploads in mobile network, we deploy edge computing to locally run networks for analysis, thus saving time to offload computing request and enhancing privacy by encrypting original data. Inspired by remarkable relationship representation of graphs, we build Graph Neural Network (GNN) in cloud to map physical mobile systems to virtual entities with DT, thus performing semantic inferences in cloud with few samples uploaded by edges. Occasionally, node features in GNN could converge to similar, non-discriminative embeddings, causing catastrophic unstable phenomena. An iterative reweight and drop structure (IRDS) is thus constructed in cloud, which nonetheless contributes stability with respect to edge uncertainty. As part of IRDS, a drop Edge&Node scheme is proposed to randomly remove certain nodes and edges, which not only enhances distinguished capability of graph neighbor patterns, but also offers data encryption with random strategy. We show one implementation case of image classification in social network, where experiments on public datasets show that our framework is effective with user-friendly advantages and significant intelligence.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6505-6514"},"PeriodicalIF":4.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187267","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}

引用次数: 0

OptCDU: Optimizing the Computing Data Unit Size for COIN OptCDU：优化 COIN 计算数据单元大小

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-30 DOI: 10.1109/TNSM.2024.3452485

Huanzhuo Wu;Jia He;Jiakang Weng;Giang T. Nguyen;Martin Reisslein;Frank H. P. Fitzek

{"title":"OptCDU: Optimizing the Computing Data Unit Size for COIN","authors":"Huanzhuo Wu;Jia He;Jiakang Weng;Giang T. Nguyen;Martin Reisslein;Frank H. P. Fitzek","doi":"10.1109/TNSM.2024.3452485","DOIUrl":"10.1109/TNSM.2024.3452485","url":null,"abstract":"Computing in the Network (COIN) has the potential to reduce the data traffic and thus the end-to-end latencies for data-rich services. Existing COIN studies have neglected the impact of the size of the data unit that the network nodes compute on. However, similar to the impact of the protocol data unit (packet) size in conventional store-and-forward packet-switching networks, the Computing Data Unit (CDU) size is an elementary parameter that strongly influences the COIN dynamics. We model the end-to-end service time consisting of the network transport delays (for data transmission and link propagation), the loading delays of the data into the computing units, and the computing delays in the network nodes. We derive the optimal CDU size that minimizes the end-to-end service time with gradient descent. We evaluate the impact of the CDU sizing on the amount of data transmitted over the network links and the end-to-end service time for computing the convolutional neural network (CNN) based Yoho and a Deep Neural Network (DNN) based Multi-Layer Perceptron (MLP). We distribute the Yoho and MLP neural modules over up to five network nodes. Our emulation evaluations indicate that COIN strongly reduces the amount of network traffic after the first few computing nodes. Also, the CDU size optimization has a strong impact on the end-to-end service time; whereby, CDU sizes that are too small or too large can double the service time. Our emulations validate that our gradient descent minimization correctly identifies the optimal CDU size.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6095-6111"},"PeriodicalIF":4.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187266","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}

引用次数: 0

GreenShield: Optimizing Firewall Configuration for Sustainable Networks 绿盾为可持续网络优化防火墙配置

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-30 DOI: 10.1109/TNSM.2024.3452150

Daniele Bringhenti;Fulvio Valenza

{"title":"GreenShield: Optimizing Firewall Configuration for Sustainable Networks","authors":"Daniele Bringhenti;Fulvio Valenza","doi":"10.1109/TNSM.2024.3452150","DOIUrl":"10.1109/TNSM.2024.3452150","url":null,"abstract":"Sustainability is an increasingly critical design feature for modern computer networks. However, green objectives related to energy savings are affected by the application of approximate cybersecurity management techniques. In particular, their impact is evident in distributed firewall configuration, where traditional manual approaches create redundant architectures, leading to avoidable power consumption. This issue has not been addressed by the approaches proposed in literature to automate firewall configuration so far, because their optimization is not focused on network sustainability. Therefore, this paper presents GreenShield as a possible solution that combines security and green-oriented optimization for firewall configuration. Specifically, GreenShield minimizes the power consumption related to firewalls activated in the network while ensuring that the security requested by the network administrator is guaranteed, and the one due to traffic processing by making firewalls to block undesired traffic as near as possible to the sources. The framework implementing GreenShield has undergone experimental tests to assess the provided optimization and its scalability performance.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6909-6923"},"PeriodicalIF":4.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10660559","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Multipartite Entanglement Distribution in the Quantum Internet: Knowing When to Stop! 量子互联网中的多方纠缠分发：知止！

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-30 DOI: 10.1109/TNSM.2024.3452326

Angela Sara Cacciapuoti;Jessica Illiano;Michele Viscardi;Marcello Caleffi

{"title":"Multipartite Entanglement Distribution in the Quantum Internet: Knowing When to Stop!","authors":"Angela Sara Cacciapuoti;Jessica Illiano;Michele Viscardi;Marcello Caleffi","doi":"10.1109/TNSM.2024.3452326","DOIUrl":"10.1109/TNSM.2024.3452326","url":null,"abstract":"Multipartite entanglement distribution is a key functionality of the Quantum Internet. However, quantum entanglement is very fragile, easily degraded by decoherence, which strictly constraints the time horizon within the distribution has to be completed. This, coupled with the quantum noise irremediably impinging on the channels utilized for entanglement distribution, may imply the need to attempt the distribution process multiple times before the targeted network nodes successfully share the desired entangled state. And there is no guarantee that this is accomplished within the time horizon dictated by the coherence times. As a consequence, in noisy scenarios requiring multiple distribution attempts, it may be convenient to stop the distribution process early. In this paper, we take steps in the direction of knowing when to stop the entanglement distribution by developing a theoretical framework, able to capture the quantum noise effects. Specifically, we first prove that the entanglement distribution process can be modeled as a Markov decision process. Then, we prove that the optimal decision policy exhibits attractive features, which we exploit to reduce the computational complexity. The developed framework provides quantum network designers with flexible tools to optimally engineer the design parameters of the entanglement distribution process.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6041-6058"},"PeriodicalIF":4.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10660502","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Fairness-Aware VNF Mapping and Scheduling in Satellite Edge Networks for Mission-Critical Applications 面向关键任务应用的卫星边缘网络中公平感知的 VNF 映射和调度

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-29 DOI: 10.1109/TNSM.2024.3452031

Haftay Gebreslasie Abreha;Houcine Chougrani;Ilora Maity;Youssouf Drif;Christos Politis;Symeon Chatzinotas

{"title":"Fairness-Aware VNF Mapping and Scheduling in Satellite Edge Networks for Mission-Critical Applications","authors":"Haftay Gebreslasie Abreha;Houcine Chougrani;Ilora Maity;Youssouf Drif;Christos Politis;Symeon Chatzinotas","doi":"10.1109/TNSM.2024.3452031","DOIUrl":"10.1109/TNSM.2024.3452031","url":null,"abstract":"Satellite Edge Computing (SEC) is seen as a promising solution for deploying network functions in orbit to provide ubiquitous services with low latency and bandwidth. Software Defined Networks (SDN) and Network Function Virtualization (NFV) enable SEC to manage and deploy services more flexibly. In this paper, we study a dynamic and topology-aware VNF mapping and scheduling strategy within an SDN/NFV-enabled SEC infrastructure. Our focus is on meeting the stringent requirements of mission-critical (MC) applications, recognizing their significance in both satellite-to-satellite and edge-to-satellite communications while ensuring service delay margin fairness across various time-sensitive service requests. We formulate the VNF mapping and scheduling problem as an Integer Nonlinear Programming problem (\u0000<monospace>INLP</monospace>\u0000), with the objective of \u0000<italic>minimax</i>\u0000 fairness among specified requests while considering dynamic satellite network topology, traffic, and resource constraints. We then propose two algorithms for solving the \u0000<monospace>INLP</monospace>\u0000 problem: Fairness-Aware Greedy Algorithm for Dynamic VNF Mapping and Scheduling (\u0000<monospace>FAGD_MASC</monospace>\u0000) and Fairness-Aware Simulated Annealing-Based Algorithm for Dynamic VNF Mapping and Scheduling (\u0000<monospace>FASD_MASC</monospace>\u0000) which are suitable for low and high service arrival rates, respectively. Our extensive simulations demonstrate that both \u0000<monospace>FAGD_MASC</monospace>\u0000 and \u0000<monospace>FASD_MASC</monospace>\u0000 approaches are very close to the optimization-based solution and outperform the benchmark solution in terms of service acceptance rates.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6716-6730"},"PeriodicalIF":4.7,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10659145","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Data Aggregation Management With Self-Sovereign Identity in Decentralized Networks 去中心化网络中的自主身份数据聚合管理

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-29 DOI: 10.1109/TNSM.2024.3451995

Yepeng Ding;Junwei Yu;Shaowen Li;Hiroyuki Sato;Maro G. Machizawa

{"title":"Data Aggregation Management With Self-Sovereign Identity in Decentralized Networks","authors":"Yepeng Ding;Junwei Yu;Shaowen Li;Hiroyuki Sato;Maro G. Machizawa","doi":"10.1109/TNSM.2024.3451995","DOIUrl":"10.1109/TNSM.2024.3451995","url":null,"abstract":"Data aggregation management is paramount in data-driven distributed systems. Conventional solutions premised on centralized networks grapple with security challenges concerning authenticity, confidentiality, integrity, and privacy. Recently, distributed ledger technology has gained popularity for its decentralized nature to facilitate overcoming these challenges. Nevertheless, insufficient identity management introduces risks like impersonation and unauthorized access. In this paper, we propose Degator, a data aggregation management framework that leverages self-sovereign identity and functions in decentralized networks to address security concerns and mitigate identity-related risks. We formulate fully decentralized aggregation protocols for data persistence and acquisition in Degator. Degator is compatible with existing data persistence methods, and supports cost-effective data acquisition minimizing dependency on distributed ledgers. We also conduct a formal analysis to elucidate the mechanism of Degator to tackle current security challenges in conventional data aggregation management. Furthermore, we showcase the applicability of Degator through its application in the management of decentralized neuroscience data aggregation and demonstrate its scalability via performance evaluation.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6174-6189"},"PeriodicalIF":4.7,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10659216","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Is There a DDoS?: System+Application Variable Monitoring to Ascertain the Attack Presence 有 DDoS 吗？系统+应用变量监控以确定攻击是否存在

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-29 DOI: 10.1109/TNSM.2024.3451613

Gunjan Kumar Saini;Gaurav Somani

{"title":"Is There a DDoS?: System+Application Variable Monitoring to Ascertain the Attack Presence","authors":"Gunjan Kumar Saini;Gaurav Somani","doi":"10.1109/TNSM.2024.3451613","DOIUrl":"10.1109/TNSM.2024.3451613","url":null,"abstract":"The state of the art has numerous contributions which focus on combating the DDoS attacks. We argue that the mitigation methods are only useful if the victim service or the mitigation method can ascertain the presence of a DDoS attack. In many of the past solutions, the authors decide the presence of DDoS using quick and dirty checks. However, precise mechanisms are still needed so that the accurate decisions about DDoS mitigation can be made. In this work, we propose a method for detecting the presence of DDoS attacks using system variables available at the server or victim server operating system. To achieve this, we propose a machine learning based detection model in which there are three steps involved. In the first step, we monitored 14 different systems and application variables/ characteristics with and without a variety of DDoS attacks. In the second step, we trained machine learning model with monitored data of all the selected variables. In the final step, our approach uses the artificial neural network (ANN) and random forest (RF) based approaches to detect the presence of DDoS attacks. Our presence identification approach gives a detection accuracy of 88%-95% for massive attacks, 65%-77% for mixed traffic having a mixture of low-rate attack and benign requests, 58%-60% for flashcrowd, 76%-81% for mixed traffic having a mixture of massive attack and benign traffic and 58%-64% for low rate attacks with a detection time of 4-5 seconds.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6899-6908"},"PeriodicalIF":4.7,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187273","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}

引用次数: 0

QoE Estimation Across Different Cloud Gaming Services Using Transfer Learning 利用迁移学习估计不同云游戏服务的 QoE

IF 4.7 2区计算机科学

IEEE Transactions on Network and Service Management Pub Date : 2024-08-28 DOI: 10.1109/TNSM.2024.3451300

Marcos Carvalho;Daniel Soares;Daniel Fernandes Macedo

{"title":"QoE Estimation Across Different Cloud Gaming Services Using Transfer Learning","authors":"Marcos Carvalho;Daniel Soares;Daniel Fernandes Macedo","doi":"10.1109/TNSM.2024.3451300","DOIUrl":"10.1109/TNSM.2024.3451300","url":null,"abstract":"Cloud Gaming (CG) has become one of the most important cloud-based services in recent years by providing games to different end-network devices, such as personal computers (wired network) and smartphones/tablets (mobile network). CG services stand challenging for network operators since this service demands rigorous network Quality of Services (QoS). Nevertheless, ensuring proper Quality of Experience (QoE) keeps the end-users engaged in the CG services. However, several factors influence users’ experience, such as context (i.e., game type/players) and the end-network type (wired/mobile). In this case, Machine Learning (ML) models have achieved the state-of-the-art on the end-users’ QoE estimation. Despite that, traditional ML models demand a larger amount of data and assume that the training and test have the same distribution, which can make the ML models hard to generalize to other scenarios from what was trained. This work employs Transfer Learning (TL) techniques to create QoE estimation over different cloud gaming services (wired/mobile) and contexts (game type/players). We improved our previous work by performing a subjective QoE assessment with real users playing new games on a mobile cloud gaming testbed. Results show that transfer learning can decrease the average MSE error by at least 34.7% compared to the source model (wired) performance on the mobile cloud gaming and to 81.5% compared with the model trained from scratch.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"5935-5946"},"PeriodicalIF":4.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187275","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}

引用次数: 0