As a key service of the Internet of Vehicles (IoV), vehicle advertising can capture the interest of potential customers and generate revenue for nearby merchants. However, due to the dynamics of vehicles, IoV suffers from unstable communication links between vehicles, which reduces the delivery ratio of vehicle advertising. To address this challenge and progress beyond the state-of-the-art work, this letter adopts Digital Twin (DT) to construct a social relationship model of vehicles and proposes a seed determination scheme for advertising dissemination. On this basis, a Deep Q-network (DQN)-based vehicle advertising dissemination scheme is proposed to determine the updating frequency of the seeds and further improve dissemination efficiency.
{"title":"An Influence Maximization-Based Hybrid Advertising Dissemination for Internet of Vehicles","authors":"Junfang Zheng;Junling Shi;Qiang He;Enchao Zhang;Ammar Hawbani;Liang Zhao","doi":"10.1109/LNET.2023.3296081","DOIUrl":"10.1109/LNET.2023.3296081","url":null,"abstract":"As a key service of the Internet of Vehicles (IoV), vehicle advertising can capture the interest of potential customers and generate revenue for nearby merchants. However, due to the dynamics of vehicles, IoV suffers from unstable communication links between vehicles, which reduces the delivery ratio of vehicle advertising. To address this challenge and progress beyond the state-of-the-art work, this letter adopts Digital Twin (DT) to construct a social relationship model of vehicles and proposes a seed determination scheme for advertising dissemination. On this basis, a Deep Q-network (DQN)-based vehicle advertising dissemination scheme is proposed to determine the updating frequency of the seeds and further improve dissemination efficiency.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"218-222"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87705411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-18DOI: 10.1109/LNET.2023.3296350
David Tipper;Prashant Krishnamurthy;Amy Babay
Ultra-reliable low latency communication (URLLC) in mobile networks is expected to be enabled by a combination of multi-connectivity and multi-access edge computing (MEC). In this letter, we develop an availability model that can be used to characterize multi-connectivity to the MEC and the combined effect of MEC server location and the physical topology. The model incorporates the effect of the wireless link in the connection and illustrates the need for multi-connectivity to achieve high levels of availability.
{"title":"Availability Analysis of Multi-Connectivity for Providing URLLC","authors":"David Tipper;Prashant Krishnamurthy;Amy Babay","doi":"10.1109/LNET.2023.3296350","DOIUrl":"10.1109/LNET.2023.3296350","url":null,"abstract":"Ultra-reliable low latency communication (URLLC) in mobile networks is expected to be enabled by a combination of multi-connectivity and multi-access edge computing (MEC). In this letter, we develop an availability model that can be used to characterize multi-connectivity to the MEC and the combined effect of MEC server location and the physical topology. The model incorporates the effect of the wireless link in the connection and illustrates the need for multi-connectivity to achieve high levels of availability.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"223-226"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81107011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.1109/LNET.2023.3294497
Changshi Zhou;Nirwan Ansari
Network data analytics function (NWDAF), introduced to provision data analytics and machine learning model training in the 5G core network, is expected to be an essential functional entity and play a significant role in the emerging AI-native 6G wireless network. However, refining the NWDAF architecture to support machine learning (ML) model sharing among multiple NWDAFs with distributed data sources and different privacy constraints remains a major challenge. To address this challenge, we propose a federated learning enabled NWDAF architecture with Partial Homomorphic Encryption to secure ML model sharing with privacy preserving. Simulation results demonstrate the feasibility of our proposed architecture.
{"title":"Securing Federated Learning Enabled NWDAF Architecture With Partial Homomorphic Encryption","authors":"Changshi Zhou;Nirwan Ansari","doi":"10.1109/LNET.2023.3294497","DOIUrl":"10.1109/LNET.2023.3294497","url":null,"abstract":"Network data analytics function (NWDAF), introduced to provision data analytics and machine learning model training in the 5G core network, is expected to be an essential functional entity and play a significant role in the emerging AI-native 6G wireless network. However, refining the NWDAF architecture to support machine learning (ML) model sharing among multiple NWDAFs with distributed data sources and different privacy constraints remains a major challenge. To address this challenge, we propose a federated learning enabled NWDAF architecture with Partial Homomorphic Encryption to secure ML model sharing with privacy preserving. Simulation results demonstrate the feasibility of our proposed architecture.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"299-303"},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77426261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-16DOI: 10.1109/LNET.2023.3286933
Zhanwei Yu;Yi Zhao;Tao Deng;Lei You;Di Yuan
We address reducing carbon footprint (CF) in the context of edge computing. The carbon intensity of electricity supply largely varies spatially as well as temporally. We consider optimal task scheduling and offloading, as well as battery charging to minimize the total CF. We formulate this optimization problem as a mixed integer linear programming model. However, we demonstrate that, via a graph-based reformulation, the problem can be cast as a minimum-cost flow problem, and global optimum can be admitted in polynomial time. Numerical results using real-world data show that optimization can reduce up to 83.3% of the total CF.
{"title":"Less Carbon Footprint in Edge Computing by Joint Task Offloading and Energy Sharing","authors":"Zhanwei Yu;Yi Zhao;Tao Deng;Lei You;Di Yuan","doi":"10.1109/LNET.2023.3286933","DOIUrl":"https://doi.org/10.1109/LNET.2023.3286933","url":null,"abstract":"We address reducing carbon footprint (CF) in the context of edge computing. The carbon intensity of electricity supply largely varies spatially as well as temporally. We consider optimal task scheduling and offloading, as well as battery charging to minimize the total CF. We formulate this optimization problem as a mixed integer linear programming model. However, we demonstrate that, via a graph-based reformulation, the problem can be cast as a minimum-cost flow problem, and global optimum can be admitted in polynomial time. Numerical results using real-world data show that optimization can reduce up to 83.3% of the total CF.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"245-249"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10154013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139406714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1109/LNET.2023.3286443
Leon Fernandez;Gunnar Karlsson
Service providers are adopting open-source technology and open standards in their next-generation networks. This gives them great flexibility and spurs innovation. But it also means that they must ensure proper interoperability between components; otherwise, vulnerabilities might get introduced in their networks. Unfortunately, state-of-the-art vulnerability scanning tools are unable to handle the complexity of service provider networks. In this letter we show how interoperability issues between seemingly reliable components introduce an injection vulnerability that allows us to control a firewall-protected network management system. We also extend the state-of-the-art in black-box fuzzing to give service providers a tool for combating similar issues.
{"title":"Black-Box Fuzzing for Security in Managed Networks: An Outline","authors":"Leon Fernandez;Gunnar Karlsson","doi":"10.1109/LNET.2023.3286443","DOIUrl":"10.1109/LNET.2023.3286443","url":null,"abstract":"Service providers are adopting open-source technology and open standards in their next-generation networks. This gives them great flexibility and spurs innovation. But it also means that they must ensure proper interoperability between components; otherwise, vulnerabilities might get introduced in their networks. Unfortunately, state-of-the-art vulnerability scanning tools are unable to handle the complexity of service provider networks. In this letter we show how interoperability issues between seemingly reliable components introduce an injection vulnerability that allows us to control a firewall-protected network management system. We also extend the state-of-the-art in black-box fuzzing to give service providers a tool for combating similar issues.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"241-244"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90752375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1109/LNET.2023.3286581
Olga Chukhno;Olga Galinina;Sergey Andreev;Antonella Molinaro;Antonio Iera
This letter presents a practice-inspired methodology for characterizing the user and content dynamics of extended reality (XR) services over wireless networks. The proposed approach is based on a fluid approximation to capture the time and space dynamics of XR content exchange during its transient phase while considering both radio communication and edge computing resources. Hence, our methodology provides an effective tool to support resource assignment for radio and computing in 5G and beyond networks, especially under non-stationary processes with time-varying traffic arrivals, such as those with a periodic arrival rate function.
{"title":"User and Content Dynamics of Edge-Aided Immersive Reality Services","authors":"Olga Chukhno;Olga Galinina;Sergey Andreev;Antonella Molinaro;Antonio Iera","doi":"10.1109/LNET.2023.3286581","DOIUrl":"10.1109/LNET.2023.3286581","url":null,"abstract":"This letter presents a practice-inspired methodology for characterizing the user and content dynamics of extended reality (XR) services over wireless networks. The proposed approach is based on a fluid approximation to capture the time and space dynamics of XR content exchange during its transient phase while considering both radio communication and edge computing resources. Hence, our methodology provides an effective tool to support resource assignment for radio and computing in 5G and beyond networks, especially under non-stationary processes with time-varying traffic arrivals, such as those with a periodic arrival rate function.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"227-231"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10153602","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84087656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-14DOI: 10.1109/LNET.2023.3286104
Dimitrios Michael Manias;Ali Chouman;Joe Naoum-Sawaya;Abdallah Shami
In the realm of network management and orchestration, such as Virtual Network Function (VNF) lifecycle management, the dynamicity of 5G networks raises the importance of reliability and robustness when determining optimal VNF placement. Specifically, after a fault has occurred, the set of services that must maintain a certain level of performance and quality depends on the interaction between VNFs. This letter proposes a novel robust optimization model for VNF placement during post-fault status, while addressing the resilience and reliability of the 5G network in testing. The model results are compared with a deterministic placement solution with varying demand uncertainties.
{"title":"Resilient and Robust QoS-Preserving Post-Fault VNF Placement","authors":"Dimitrios Michael Manias;Ali Chouman;Joe Naoum-Sawaya;Abdallah Shami","doi":"10.1109/LNET.2023.3286104","DOIUrl":"10.1109/LNET.2023.3286104","url":null,"abstract":"In the realm of network management and orchestration, such as Virtual Network Function (VNF) lifecycle management, the dynamicity of 5G networks raises the importance of reliability and robustness when determining optimal VNF placement. Specifically, after a fault has occurred, the set of services that must maintain a certain level of performance and quality depends on the interaction between VNFs. This letter proposes a novel robust optimization model for VNF placement during post-fault status, while addressing the resilience and reliability of the 5G network in testing. The model results are compared with a deterministic placement solution with varying demand uncertainties.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"270-274"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76955116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/LNET.2023.3285295
Salwa Mostafa;Mohamed K. Abdel-Aziz;Mehdi Bennis
We consider a cooperative-navigation problem in a partially observable MADRL framework. We investigate how agents cooperate to learn a communication protocol given a very large state space while generalizing to a new environment. The proposed solution leverages the notion of structured observation and abstraction, in which the raw-pixel observations are converted into a relational graph that is then used for learning abstraction. Abstraction is performed based on compression using a relational graph autoencoder (RGAE) and a multilayer perceptron (MLP) to remove irrelevant information. The results show the effectiveness of the proposed MLP and RGAE in learning better policies with better generalization capabilities. It is also shown that communication among agents is instrumental in improving the navigation task performance.
{"title":"Cooperative Navigation via Relational Graphs and State Abstraction","authors":"Salwa Mostafa;Mohamed K. Abdel-Aziz;Mehdi Bennis","doi":"10.1109/LNET.2023.3285295","DOIUrl":"10.1109/LNET.2023.3285295","url":null,"abstract":"We consider a cooperative-navigation problem in a partially observable MADRL framework. We investigate how agents cooperate to learn a communication protocol given a very large state space while generalizing to a new environment. The proposed solution leverages the notion of structured observation and abstraction, in which the raw-pixel observations are converted into a relational graph that is then used for learning abstraction. Abstraction is performed based on compression using a relational graph autoencoder (RGAE) and a multilayer perceptron (MLP) to remove irrelevant information. The results show the effectiveness of the proposed MLP and RGAE in learning better policies with better generalization capabilities. It is also shown that communication among agents is instrumental in improving the navigation task performance.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"5 4","pages":"184-188"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74494199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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