Pub Date : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00071
Sergio Aliaga, Ali J. Alqaraghuli, J. Jornet
As the interest in the Terahertz (0.1-1THz) band grows with the technological advancements that enable communication at higher data rates, the existing use for THz-based sensing systems motivate exploration of Joint Communication and Sensing systems (JCS). Such systems can be used for the next generation of satellite constellations for the purposes of internet-backhauling, while performing scientific functions such as studying atmospheric gases. The fact that the hardware employed for both applications is highly similar, if not identical, opens the possibility of designing a new waveform that can jointly communicate and sense at the same time. In this paper, we explore Differential Absorption Radars (DAR), traditionally used for weather sensing, as a potential candidate to be operated in combination with a Chirp Spread Spectrum (CSS) modulation. We present a scenario with a satellite at Low Earth Orbit (LEO) where the CSS modulation could outperform traditional PSK modulations while making it possible to retrieve water vapor density profiles of the atmosphere with DAR. Performance of both communication and remote sensing applications are studied through simulation.
{"title":"Joint Terahertz Communication and Atmospheric Sensing in Low Earth Orbit Satellite Networks: Physical Layer Design","authors":"Sergio Aliaga, Ali J. Alqaraghuli, J. Jornet","doi":"10.1109/WoWMoM54355.2022.00071","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00071","url":null,"abstract":"As the interest in the Terahertz (0.1-1THz) band grows with the technological advancements that enable communication at higher data rates, the existing use for THz-based sensing systems motivate exploration of Joint Communication and Sensing systems (JCS). Such systems can be used for the next generation of satellite constellations for the purposes of internet-backhauling, while performing scientific functions such as studying atmospheric gases. The fact that the hardware employed for both applications is highly similar, if not identical, opens the possibility of designing a new waveform that can jointly communicate and sense at the same time. In this paper, we explore Differential Absorption Radars (DAR), traditionally used for weather sensing, as a potential candidate to be operated in combination with a Chirp Spread Spectrum (CSS) modulation. We present a scenario with a satellite at Low Earth Orbit (LEO) where the CSS modulation could outperform traditional PSK modulations while making it possible to retrieve water vapor density profiles of the atmosphere with DAR. Performance of both communication and remote sensing applications are studied through simulation.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125944479","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 : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00067
Mattia Fogli, Carlo Giannelli, C. Stefanelli
The industrial internet of things has radically modified industrial environments, not only enabling novel services but also dramatically increasing the amount of generated traffic. Nowadays, a major concern within industrial plants is to support network-intensive services, such as real-time remote vibration monitoring of autonomous guided vehicles, while ensuring the prompt and reliable delivery of mission-critical safety-related messages among machines and the control room. To this purpose, we present a novel solution jointly orchestrating content-based message management and traffic flow steering: the former enables edge-powered in-network processing modules to process packet payloads as they traverse the industrial backbone, the latter supports dynamic (re)routing of traffic flows towards such processing modules. In particular, we exploit software-defined networking for flexible traffic flow (re)routing and Kubernetes for dynamic deployment on edge nodes of in-network processing modules for content-based message management. As demonstrated by performance results based on our working proof-of-concept prototype, our solution efficiently allows to manage industrial traffic flows in a coordinated fashion, by considering requirements of concurrently running industrial applications and the current state of the overall topology.
{"title":"Joint Orchestration of Content-Based Message Management and Traffic Flow Steering in Industrial Backbones","authors":"Mattia Fogli, Carlo Giannelli, C. Stefanelli","doi":"10.1109/WoWMoM54355.2022.00067","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00067","url":null,"abstract":"The industrial internet of things has radically modified industrial environments, not only enabling novel services but also dramatically increasing the amount of generated traffic. Nowadays, a major concern within industrial plants is to support network-intensive services, such as real-time remote vibration monitoring of autonomous guided vehicles, while ensuring the prompt and reliable delivery of mission-critical safety-related messages among machines and the control room. To this purpose, we present a novel solution jointly orchestrating content-based message management and traffic flow steering: the former enables edge-powered in-network processing modules to process packet payloads as they traverse the industrial backbone, the latter supports dynamic (re)routing of traffic flows towards such processing modules. In particular, we exploit software-defined networking for flexible traffic flow (re)routing and Kubernetes for dynamic deployment on edge nodes of in-network processing modules for content-based message management. As demonstrated by performance results based on our working proof-of-concept prototype, our solution efficiently allows to manage industrial traffic flows in a coordinated fashion, by considering requirements of concurrently running industrial applications and the current state of the overall topology.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115965685","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 : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00069
F. Martelli, M. E. Renda
The problem of data privacy preservation is of central importance in ride-sharing applications, because in order to efficiently match passengers with vehicles, these services rely on exact location information. Yet, transportation and location data can reveal personal habits, preferences and behaviors, and users may prefer not to share their exact location. Masking location data in order to avoid the identification of users in case of data leakage, and/or misusage would help protect user privacy, but could also lead to poorer system performance, in terms of efficiency and quality of service as perceived by users.In this paper, we compare classic data masking techniques, namely obfuscation, k-anonymity, and l-diversity, applied to users’ location data, before sending it to a carpooling system. While the first two techniques use randomly generated points to mask the actual location, l-diversity uses actual points of interest, having the additional benefit of ensuring that the disclosed location is always an accessible and safe pickup or drop-off location. Given that users in a real ride-sharing system could choose to protect or not protect their location data when using the system, we also evaluate the effect of privacy preservation penetration rate, by varying the percentage of users choosing to have their location data protected. The results show that l-diversity performance is better than the others’ even when the privacy penetration rate is high, suggesting that this technique has the potential to meet both users’ and system’s needs, and thus being a better option to provide privacy within carpooling systems.
{"title":"Enhancing Privacy in Ride-Sharing Applications Through POIs Selection","authors":"F. Martelli, M. E. Renda","doi":"10.1109/WoWMoM54355.2022.00069","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00069","url":null,"abstract":"The problem of data privacy preservation is of central importance in ride-sharing applications, because in order to efficiently match passengers with vehicles, these services rely on exact location information. Yet, transportation and location data can reveal personal habits, preferences and behaviors, and users may prefer not to share their exact location. Masking location data in order to avoid the identification of users in case of data leakage, and/or misusage would help protect user privacy, but could also lead to poorer system performance, in terms of efficiency and quality of service as perceived by users.In this paper, we compare classic data masking techniques, namely obfuscation, k-anonymity, and l-diversity, applied to users’ location data, before sending it to a carpooling system. While the first two techniques use randomly generated points to mask the actual location, l-diversity uses actual points of interest, having the additional benefit of ensuring that the disclosed location is always an accessible and safe pickup or drop-off location. Given that users in a real ride-sharing system could choose to protect or not protect their location data when using the system, we also evaluate the effect of privacy preservation penetration rate, by varying the percentage of users choosing to have their location data protected. The results show that l-diversity performance is better than the others’ even when the privacy penetration rate is high, suggesting that this technique has the potential to meet both users’ and system’s needs, and thus being a better option to provide privacy within carpooling systems.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130895494","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 : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00086
R. Kumar, R. S. Bali, G. Aujla
Edge intelligence propelled federated learning as a promising technology for embedding distributed intelligence in the Internet of Things (IoT) ecosystem. The multidimensional data generated by IoT devices is enormous in volume and personalized in nature. Thus, integrating federated learning to train the learning model for performing analysis on source data can be helpful. Despite the above reasons, the current schemes are centralized and depend on the server for aggregation of local parameters. So, in this paper, we have proposed a model that enables the sensor to be part of a defined cluster (based on the type of data generated by the sensor) during the registration process. In this approach, the aggregation is performed at the edge server for sub-global aggregation, which further communicates the aggregated parameters for global aggregation. The sub-global model is trained by selecting an optimal value for local iterations, batch size, and appropriate model selection. The experimental setup based on the tensor flow federated framework is verified on MNSIT-10 datasets for the validity of the proposed methodology.
{"title":"A Federated Leaning Perspective for Intelligent Data Communication Framework in IoT Ecosystem","authors":"R. Kumar, R. S. Bali, G. Aujla","doi":"10.1109/WoWMoM54355.2022.00086","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00086","url":null,"abstract":"Edge intelligence propelled federated learning as a promising technology for embedding distributed intelligence in the Internet of Things (IoT) ecosystem. The multidimensional data generated by IoT devices is enormous in volume and personalized in nature. Thus, integrating federated learning to train the learning model for performing analysis on source data can be helpful. Despite the above reasons, the current schemes are centralized and depend on the server for aggregation of local parameters. So, in this paper, we have proposed a model that enables the sensor to be part of a defined cluster (based on the type of data generated by the sensor) during the registration process. In this approach, the aggregation is performed at the edge server for sub-global aggregation, which further communicates the aggregated parameters for global aggregation. The sub-global model is trained by selecting an optimal value for local iterations, batch size, and appropriate model selection. The experimental setup based on the tensor flow federated framework is verified on MNSIT-10 datasets for the validity of the proposed methodology.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121780911","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 : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00068
Sandra Zimmermann, Paul Schwenteck, Juan A. Cabrera, Giang T. Nguyen, F. Fitzek
Delivering content from a network via a client-server architecture is expensive not only for content owners but also for network operators. Moving content closer to the end user is already used in Content Delivery Networks (CDN). Multi-Access Edge Computing (MEC) enables us to shift the content even closer by using the storage of end users. But, due to the large media files, storage and transport costs for peers increase significantly. Network Coding can reduce these costs. However, peers in CDNs tend to be highly fluctuating and often need to be restored, making continuous availability of data at the network edge a problem. While for uncoded data, individual packets lost due to peer failures can be tracked to determine availability, the availability of coded data is currently distinguished only in two cases: either there are still enough linearly independent packets to decode the file, or there are not. However, we have found that the network’s combined coded cache loses quality over time due to recovery. This quality loss, which we refer to as grade, can be measured by very cost-effective monitoring. If the grade falls below a certain limit, we can intervene in the network by performing a cache refresh to prevent data becoming unavailable preemptively. In this paper, we present the cases in which such monitoring is useful, how the grade is calculated, and when a cache refresh is necessary. The results show that we can reduce network traffic by up to 34% with minimal storage costs through efficient monitoring.
{"title":"Grade to the Edge: How Many Unreliable Nodes Does It Take to Break a Content Delivery Network?","authors":"Sandra Zimmermann, Paul Schwenteck, Juan A. Cabrera, Giang T. Nguyen, F. Fitzek","doi":"10.1109/WoWMoM54355.2022.00068","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00068","url":null,"abstract":"Delivering content from a network via a client-server architecture is expensive not only for content owners but also for network operators. Moving content closer to the end user is already used in Content Delivery Networks (CDN). Multi-Access Edge Computing (MEC) enables us to shift the content even closer by using the storage of end users. But, due to the large media files, storage and transport costs for peers increase significantly. Network Coding can reduce these costs. However, peers in CDNs tend to be highly fluctuating and often need to be restored, making continuous availability of data at the network edge a problem. While for uncoded data, individual packets lost due to peer failures can be tracked to determine availability, the availability of coded data is currently distinguished only in two cases: either there are still enough linearly independent packets to decode the file, or there are not. However, we have found that the network’s combined coded cache loses quality over time due to recovery. This quality loss, which we refer to as grade, can be measured by very cost-effective monitoring. If the grade falls below a certain limit, we can intervene in the network by performing a cache refresh to prevent data becoming unavailable preemptively. In this paper, we present the cases in which such monitoring is useful, how the grade is calculated, and when a cache refresh is necessary. The results show that we can reduce network traffic by up to 34% with minimal storage costs through efficient monitoring.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128636654","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 : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00022
V. Mancuso, P. Castagno, M. Sereno, M. Marsan
We consider a radio access network slice serving mobile users whose requests imply computing requirements. Service is virtualized over either a powerful but distant cloud infrastructure or an edge computing host. The latter provides less computing and storage capacity with respect to the cloud, but can be reached with much lower delay. A tradeoff thus naturally arises between computing capacity and data transfer latency. We investigate the performance of this service model, discussing how service requests should be routed to edge or cloud servers. We look at the performance of various classes of online algorithms based on different levels of information about the system state. Our investigation is based on analytical models, simulations in OMNeT++, and a prototype implementation over operational cellular networks. First of all, we observe that distributing the load of service requests over edge and cloud is in general beneficial for performance, and simple to implement with a stateless online server selection policy that can be easily configured with near-optimal performance. Second, we shed light on the limited improvements that stateful polices can offer, notwithstanding they base their decisions on the knowledge of server congestion levels or round-trip latency conditions. Third, we unveil that stateful policies are dangerously prone to errors, which may make stateless policies preferable.
{"title":"Stateful Versus Stateless Selection of Edge or Cloud Servers Under Latency Constraints","authors":"V. Mancuso, P. Castagno, M. Sereno, M. Marsan","doi":"10.1109/WoWMoM54355.2022.00022","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00022","url":null,"abstract":"We consider a radio access network slice serving mobile users whose requests imply computing requirements. Service is virtualized over either a powerful but distant cloud infrastructure or an edge computing host. The latter provides less computing and storage capacity with respect to the cloud, but can be reached with much lower delay. A tradeoff thus naturally arises between computing capacity and data transfer latency. We investigate the performance of this service model, discussing how service requests should be routed to edge or cloud servers. We look at the performance of various classes of online algorithms based on different levels of information about the system state. Our investigation is based on analytical models, simulations in OMNeT++, and a prototype implementation over operational cellular networks. First of all, we observe that distributing the load of service requests over edge and cloud is in general beneficial for performance, and simple to implement with a stateless online server selection policy that can be easily configured with near-optimal performance. Second, we shed light on the limited improvements that stateful polices can offer, notwithstanding they base their decisions on the knowledge of server congestion levels or round-trip latency conditions. Third, we unveil that stateful policies are dangerously prone to errors, which may make stateless policies preferable.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115324066","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 : 2022-06-01DOI: 10.1109/wowmom54355.2022.00100
{"title":"Message from the Workshop Chairs: TwinNets 2022","authors":"","doi":"10.1109/wowmom54355.2022.00100","DOIUrl":"https://doi.org/10.1109/wowmom54355.2022.00100","url":null,"abstract":"","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125900954","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 : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00084
Ahmed A. A. Osman, Raouf Abozariba, A. Taufiq Asyhari, Adel Aneiba, M. Ben Farah
WebRTC is a Google-developed project that allows users to communicate directly. It is an open-source tool supported by all major browsers. Since it does not require additional installation steps and provides ultra-low latency streaming, smart city and social network applications such as WhatsApp, Facebook Messenger, and Snapchat use it as the underlying technology on the client-side both on desktop browsers and mobile apps. While the open-source tool is deemed to be secure and despite years of research and security testing, there are still vulnerabilities in the real-time communication application programming interface (API). We show in this paper how eavesdropping can be enabled by exploiting weaknesses and loopholes found in official WebRTC specifications. We demonstrate through real-world implementation how an eavesdropper can intercept WebRTC video calls by installing a malicious code onto the WebRTC webserver. Furthermore, we identify and discuss several, easy to perform, ways to detect wiretapping. Our evaluation shows that several indicators within webrtc-internals API traces can be used to detect anomalous activities, without the need for network monitoring tools.
{"title":"Detection of JavaScript Injection Eavesdropping on WebRTC communications","authors":"Ahmed A. A. Osman, Raouf Abozariba, A. Taufiq Asyhari, Adel Aneiba, M. Ben Farah","doi":"10.1109/WoWMoM54355.2022.00084","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00084","url":null,"abstract":"WebRTC is a Google-developed project that allows users to communicate directly. It is an open-source tool supported by all major browsers. Since it does not require additional installation steps and provides ultra-low latency streaming, smart city and social network applications such as WhatsApp, Facebook Messenger, and Snapchat use it as the underlying technology on the client-side both on desktop browsers and mobile apps. While the open-source tool is deemed to be secure and despite years of research and security testing, there are still vulnerabilities in the real-time communication application programming interface (API). We show in this paper how eavesdropping can be enabled by exploiting weaknesses and loopholes found in official WebRTC specifications. We demonstrate through real-world implementation how an eavesdropper can intercept WebRTC video calls by installing a malicious code onto the WebRTC webserver. Furthermore, we identify and discuss several, easy to perform, ways to detect wiretapping. Our evaluation shows that several indicators within webrtc-internals API traces can be used to detect anomalous activities, without the need for network monitoring tools.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129924082","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 : 2022-06-01DOI: 10.1109/wowmom54355.2022.00010
{"title":"Reviewers: ISMS 2022","authors":"","doi":"10.1109/wowmom54355.2022.00010","DOIUrl":"https://doi.org/10.1109/wowmom54355.2022.00010","url":null,"abstract":"","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121544001","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 : 2022-06-01DOI: 10.1109/WoWMoM54355.2022.00024
Leiyang Cui, Yusi Long, D. Hoang, Shiming Gong
In this paper, we focus on a multi-user wireless network coordinated by a multi-antenna access point (AP). Each user can generate the sensing information randomly and report it to the AP. The freshness of information is measured by the age of information (AoI). We formulate the AoI minimization problem by jointly optimizing the users’ scheduling and transmission control strategies. Moreover, we employ the intelligent reflecting surface (IRS) to enhance the channel conditions and thus reduce the transmission delay by controlling the AP’s beamforming vector and the IRS’s phase shifting matrices. The resulting AoI minimization becomes a mixed-integer program and difficult to solve due to uncertain information of the sensing data arrivals at individual users. By exploiting the problem structure, we devised a hierarchical deep reinforcement learning (DRL) framework to search for optimal solution in two iterative steps. Specifically, the users’ scheduling strategy is firstly determined by the outer-loop DRL approach, and then the inner-loop optimization adapts either the uplink information transmission or downlink energy transfer to all users. Our numerical results verify that the proposed algorithm can outperform typical baselines in terms of the average AoI performance.
本文主要研究由多天线接入点(AP)协调的多用户无线网络。每个用户可以随机生成感知信息并向AP报告。信息的新鲜度通过信息年龄(age of information, AoI)来衡量。通过联合优化用户调度和传输控制策略，提出了AoI最小化问题。此外，我们采用智能反射面(IRS)来改善信道条件，从而通过控制AP的波束形成矢量和IRS的相移矩阵来降低传输延迟。由此产生的AoI最小化成为一个混合整数方案，并且由于到达单个用户的传感数据信息不确定而难以求解。通过利用问题结构，我们设计了一个分层深度强化学习(DRL)框架，通过两个迭代步骤搜索最优解。具体而言，用户的调度策略首先由外环DRL方法确定，然后内环优化将上行信息传输或下行能量传输适用于所有用户。我们的数值结果验证了所提出的算法在平均AoI性能方面优于典型基线。
{"title":"Hierarchical Learning Approach for Age-of-Information Minimization in Wireless Sensor Networks","authors":"Leiyang Cui, Yusi Long, D. Hoang, Shiming Gong","doi":"10.1109/WoWMoM54355.2022.00024","DOIUrl":"https://doi.org/10.1109/WoWMoM54355.2022.00024","url":null,"abstract":"In this paper, we focus on a multi-user wireless network coordinated by a multi-antenna access point (AP). Each user can generate the sensing information randomly and report it to the AP. The freshness of information is measured by the age of information (AoI). We formulate the AoI minimization problem by jointly optimizing the users’ scheduling and transmission control strategies. Moreover, we employ the intelligent reflecting surface (IRS) to enhance the channel conditions and thus reduce the transmission delay by controlling the AP’s beamforming vector and the IRS’s phase shifting matrices. The resulting AoI minimization becomes a mixed-integer program and difficult to solve due to uncertain information of the sensing data arrivals at individual users. By exploiting the problem structure, we devised a hierarchical deep reinforcement learning (DRL) framework to search for optimal solution in two iterative steps. Specifically, the users’ scheduling strategy is firstly determined by the outer-loop DRL approach, and then the inner-loop optimization adapts either the uplink information transmission or downlink energy transfer to all users. Our numerical results verify that the proposed algorithm can outperform typical baselines in terms of the average AoI performance.","PeriodicalId":275324,"journal":{"name":"2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131317649","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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