Satellite routers in emerging space-terrestrial integrated networks (STINs) are operated in a failure-prone, intermittent and resource-constrained space environment, making it very critical but challenging to cope with various network failures effectively. Existing resilient routing approaches either suffer from continuous re-convergences with low network reachability, or involve prohibitive pre-computation and storage overhead due to the huge amount of possible failure scenarios in STINs.This paper presents StarCure, a novel resilient routing mechanism for futuristic STINs. StarCure aims at achieving fast and efficient routing restoration, while maintaining the low-latency, high-bandwidth service capabilities in failure-prone space environments. First, StarCure incorporates a new network model, called the topology-stabilizing model (TSM) to eliminate topological uncertainty by converting the topology variations caused by various failures to traffic variations. Second, StarCure adopts an adaptive hybrid routing scheme, collaboratively combining a constraint optimizer to efficiently handle predictable failures, together with a location-guided protection routing strategy to quickly deal with unexpected failures. Extensive evaluations driven by realistic constellation information show that, StarCure can protect routing against various failures, achieving close-to-100% reachability and better performance restoration with acceptable system overhead, as compared to other existing resilience solutions.
{"title":"Achieving Resilient and Performance-Guaranteed Routing in Space-Terrestrial Integrated Networks","authors":"Zeqi Lai, Hewu Li, Yikun Wang, Qian Wu, Yangtao Deng, Jun Liu, Yuan-Fang Li, Jianping Wu","doi":"10.1109/INFOCOM53939.2023.10229104","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229104","url":null,"abstract":"Satellite routers in emerging space-terrestrial integrated networks (STINs) are operated in a failure-prone, intermittent and resource-constrained space environment, making it very critical but challenging to cope with various network failures effectively. Existing resilient routing approaches either suffer from continuous re-convergences with low network reachability, or involve prohibitive pre-computation and storage overhead due to the huge amount of possible failure scenarios in STINs.This paper presents StarCure, a novel resilient routing mechanism for futuristic STINs. StarCure aims at achieving fast and efficient routing restoration, while maintaining the low-latency, high-bandwidth service capabilities in failure-prone space environments. First, StarCure incorporates a new network model, called the topology-stabilizing model (TSM) to eliminate topological uncertainty by converting the topology variations caused by various failures to traffic variations. Second, StarCure adopts an adaptive hybrid routing scheme, collaboratively combining a constraint optimizer to efficiently handle predictable failures, together with a location-guided protection routing strategy to quickly deal with unexpected failures. Extensive evaluations driven by realistic constellation information show that, StarCure can protect routing against various failures, achieving close-to-100% reachability and better performance restoration with acceptable system overhead, as compared to other existing resilience solutions.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131930245","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}
As a promising infrastructure, edge storage systems have drawn many attempts to efficiently distribute and share data among edge servers. However, it remains open to meeting the increasing demand for similarity retrieval across servers. The intrinsic reason is that the existing solutions can only return an exact data match for a query while more general edge applications require the data similar to a query input from any server. To fill this gap, this paper pioneers a new paradigm to support high-dimensional similarity search at network edges. Specifically, we propose Prophet, the first known architecture for similarity data indexing. We first divide the feature space of data into plenty of subareas, then project both subareas and edge servers into a virtual plane where the distances between any two points can reflect not only data similarity but also network latency. When any edge server submits a request for data insert, delete, or query, it computes the data feature and the virtual coordinates; then iteratively forwards the request through greedy routing based on the forwarding tables and the virtual coordinates. By Prophet, similar high-dimensional features would be stored by a common server or several nearby servers. Compared with distributed hash tables in P2P networks, Prophet requires logarithmic servers to access for a data request and reduces the network latency from the logarithmic to the constant level of the server number. Experimental results indicate that Prophet achieves comparable retrieval accuracy and shortens the query latency by 55%~70% compared with centralized schemes.
{"title":"Prophet: An Efficient Feature Indexing Mechanism for Similarity Data Sharing at Network Edge","authors":"Yuchen Sun, Deke Guo, Lailong Luo, Li Liu, Xinyi Li, Junjie Xie","doi":"10.1109/INFOCOM53939.2023.10228941","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228941","url":null,"abstract":"As a promising infrastructure, edge storage systems have drawn many attempts to efficiently distribute and share data among edge servers. However, it remains open to meeting the increasing demand for similarity retrieval across servers. The intrinsic reason is that the existing solutions can only return an exact data match for a query while more general edge applications require the data similar to a query input from any server. To fill this gap, this paper pioneers a new paradigm to support high-dimensional similarity search at network edges. Specifically, we propose Prophet, the first known architecture for similarity data indexing. We first divide the feature space of data into plenty of subareas, then project both subareas and edge servers into a virtual plane where the distances between any two points can reflect not only data similarity but also network latency. When any edge server submits a request for data insert, delete, or query, it computes the data feature and the virtual coordinates; then iteratively forwards the request through greedy routing based on the forwarding tables and the virtual coordinates. By Prophet, similar high-dimensional features would be stored by a common server or several nearby servers. Compared with distributed hash tables in P2P networks, Prophet requires logarithmic servers to access for a data request and reduces the network latency from the logarithmic to the constant level of the server number. Experimental results indicate that Prophet achieves comparable retrieval accuracy and shortens the query latency by 55%~70% compared with centralized schemes.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132191451","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229008
Zhiyuan Wang, Qingkai Meng, Shan Zhang, Hongbin Luo
Many Internet platforms collect fresh information of various points of interest (PoIs) relying on users who happen to be nearby the PoIs. The platform will offer reward to incentivize users and compensate their costs incurred from information acquisition. In practice, the user cost (and its distribution) is hidden to the platform, thus it is challenging to determine the optimal reward. In this paper, we investigate how the platform dynamically rewards the users, aiming to jointly reduce the age of information (AoI) and the operational expenditure (OpEx). Due to the hidden cost distribution, this is an online non-convex learning problem with partial feedback. To overcome the challenge, we first design an age-based rewarding scheme, which decouples the OpEx from the unknown cost distribution and enables the platform to accurately control its OpEx. We then take advantage of the age-based rewarding scheme and propose an exponentially discretizing and learning (EDAL) policy for platform operation. We prove that the EDAL policy performs asymptotically as well as the optimal decision (derived based on the cost distribution). Simulation results show that the age-based rewarding scheme protects the platform’s OpEx from the influence of the user characteristics, and verify the asymptotic optimality of the EDAL policy.
{"title":"The Power of Age-based Reward in Fresh Information Acquisition","authors":"Zhiyuan Wang, Qingkai Meng, Shan Zhang, Hongbin Luo","doi":"10.1109/INFOCOM53939.2023.10229008","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229008","url":null,"abstract":"Many Internet platforms collect fresh information of various points of interest (PoIs) relying on users who happen to be nearby the PoIs. The platform will offer reward to incentivize users and compensate their costs incurred from information acquisition. In practice, the user cost (and its distribution) is hidden to the platform, thus it is challenging to determine the optimal reward. In this paper, we investigate how the platform dynamically rewards the users, aiming to jointly reduce the age of information (AoI) and the operational expenditure (OpEx). Due to the hidden cost distribution, this is an online non-convex learning problem with partial feedback. To overcome the challenge, we first design an age-based rewarding scheme, which decouples the OpEx from the unknown cost distribution and enables the platform to accurately control its OpEx. We then take advantage of the age-based rewarding scheme and propose an exponentially discretizing and learning (EDAL) policy for platform operation. We prove that the EDAL policy performs asymptotically as well as the optimal decision (derived based on the cost distribution). Simulation results show that the age-based rewarding scheme protects the platform’s OpEx from the influence of the user characteristics, and verify the asymptotic optimality of the EDAL policy.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134271424","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228959
Peng Wang, S. Sourav, Hongyan Li, Binbin Chen
How to allocate network paths and their resources to minimize the delivery time of data transfer tasks over time-varying networks? Solving this MDDT (Minimizing Data Delivery Time) problem has important applications from data centers to delay-tolerant networking. In particular, with the rapid deployment of satellite networks in recent years, an efficient MDDT solver will serve as a key building block there.The MDDT problem can be solved in polynomial time by finding the maximum flow in a time-expanded graph. A binary-search-based solver incurs O(N•log N•Γ) time complexity, where N corresponds to time horizon and Γ is the time complexity to solve a maximum flow problem for one snapshot of the network. In this work, we design a one-pass solver that progressively expands the graph over time until it reaches the earliest time interval n to complete the delivery. By reusing the calculated maximum flow results from earlier iterations, it solves the MDDT problem while incurring only O(nΓ) time complexity for algorithms that can apply our technique. We apply the one-pass design to Ford-Fulkerson algorithm and evaluate our solver using a network of 184 satellites from Starlink constellations. We demonstrate >75× speed-up in the running time and show that our solution can also enable advanced applications such as preemptive scheduling.
{"title":"One Pass is Sufficient: A Solver for Minimizing Data Delivery Time over Time-varying Networks","authors":"Peng Wang, S. Sourav, Hongyan Li, Binbin Chen","doi":"10.1109/INFOCOM53939.2023.10228959","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228959","url":null,"abstract":"How to allocate network paths and their resources to minimize the delivery time of data transfer tasks over time-varying networks? Solving this MDDT (Minimizing Data Delivery Time) problem has important applications from data centers to delay-tolerant networking. In particular, with the rapid deployment of satellite networks in recent years, an efficient MDDT solver will serve as a key building block there.The MDDT problem can be solved in polynomial time by finding the maximum flow in a time-expanded graph. A binary-search-based solver incurs O(N•log N•Γ) time complexity, where N corresponds to time horizon and Γ is the time complexity to solve a maximum flow problem for one snapshot of the network. In this work, we design a one-pass solver that progressively expands the graph over time until it reaches the earliest time interval n to complete the delivery. By reusing the calculated maximum flow results from earlier iterations, it solves the MDDT problem while incurring only O(nΓ) time complexity for algorithms that can apply our technique. We apply the one-pass design to Ford-Fulkerson algorithm and evaluate our solver using a network of 184 satellites from Starlink constellations. We demonstrate >75× speed-up in the running time and show that our solution can also enable advanced applications such as preemptive scheduling.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134073958","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229073
Dan Xia, Xiaolong Zheng, L. Liu, Huadong Ma
Cross-Technology Communication (CTC) is an emerging technique that enables direct interconnection among incompatible wireless technologies. However, for the downlink from WiFi to multiple IoT technologies, serially emulating and transmitting the data of each IoT technology has extremely low spectrum efficiency. Recent parallel CTC uses IEEE 802.11g to send emulated ZigBee signal and let the BLE receiver decodes its data from the emulated ZigBee signal with a dedicated codebook. It still has a low spectrum efficiency because IEEE 802.11g exclusively uses the whole channel. Besides, the codebook design hinders the reception on commodity BLE devices. In this paper, we propose WiCast, a parallel CTC that uses IEEE 802.11ax to emulate a composite signal that can be received by commodity BLE, ZigBee, and LoRa devices. By taking advantage of OFDMA in 802.11ax, WiCast uses a single Resource Unit (RU) for parallel CTC and sets other RUs free for high-rate WiFi users. But such a sophisticated composite signal is very easily distorted by emulation imperfections, dynamic channel noises, cyclic prefix, and center frequency offset. We propose a CTC link model that jointly models the emulation errors and channel distortions. Then we carve the emulated signal with elaborate compensations in both time and frequency domains to solve the above distortion problem. We implement a prototype of WiCast on the USRP platform and commodity devices. The extensive experiments demonstrate WiCast can achieve an efficient parallel transmission with the aggregated goodput up to 390.24kbps.
{"title":"Parallel Cross-technology Transmission from IEEE 802.11ax to Heterogeneous IoT Devices","authors":"Dan Xia, Xiaolong Zheng, L. Liu, Huadong Ma","doi":"10.1109/INFOCOM53939.2023.10229073","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229073","url":null,"abstract":"Cross-Technology Communication (CTC) is an emerging technique that enables direct interconnection among incompatible wireless technologies. However, for the downlink from WiFi to multiple IoT technologies, serially emulating and transmitting the data of each IoT technology has extremely low spectrum efficiency. Recent parallel CTC uses IEEE 802.11g to send emulated ZigBee signal and let the BLE receiver decodes its data from the emulated ZigBee signal with a dedicated codebook. It still has a low spectrum efficiency because IEEE 802.11g exclusively uses the whole channel. Besides, the codebook design hinders the reception on commodity BLE devices. In this paper, we propose WiCast, a parallel CTC that uses IEEE 802.11ax to emulate a composite signal that can be received by commodity BLE, ZigBee, and LoRa devices. By taking advantage of OFDMA in 802.11ax, WiCast uses a single Resource Unit (RU) for parallel CTC and sets other RUs free for high-rate WiFi users. But such a sophisticated composite signal is very easily distorted by emulation imperfections, dynamic channel noises, cyclic prefix, and center frequency offset. We propose a CTC link model that jointly models the emulation errors and channel distortions. Then we carve the emulated signal with elaborate compensations in both time and frequency domains to solve the above distortion problem. We implement a prototype of WiCast on the USRP platform and commodity devices. The extensive experiments demonstrate WiCast can achieve an efficient parallel transmission with the aggregated goodput up to 390.24kbps.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134205886","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228903
Zhaochen She, Yancan Mao, Hailin Xiang, Xin Wang, Richard T. B. Ma
Distributed stream systems provide low latency by processing data as it arrives. However, existing systems do not provide latency guarantee, a critical requirement of real-time analytics, especially for stateful operators under burst and skewed workload. We present StreamSwitch, a control plane for stream systems to bound operator latency while optimizing resource usage. Based on a novel stream switch abstraction that unifies dynamic scaling and load balancing into a holistic control framework, our design incorporates reactive and predictive metrics to deduce the healthiness of executors and prescribes practically optimal scaling and load balancing decisions in time. We implement a prototype of StreamSwitch and integrate it with Apache Flink and Samza. Experimental evaluations on real-world applications and benchmarks show that StreamSwitch provides cost-effective solutions for bounding latency and outperforms the state-of-the-art alternative solutions.
{"title":"StreamSwitch: Fulfilling Latency Service-Layer Agreement for Stateful Streaming","authors":"Zhaochen She, Yancan Mao, Hailin Xiang, Xin Wang, Richard T. B. Ma","doi":"10.1109/INFOCOM53939.2023.10228903","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228903","url":null,"abstract":"Distributed stream systems provide low latency by processing data as it arrives. However, existing systems do not provide latency guarantee, a critical requirement of real-time analytics, especially for stateful operators under burst and skewed workload. We present StreamSwitch, a control plane for stream systems to bound operator latency while optimizing resource usage. Based on a novel stream switch abstraction that unifies dynamic scaling and load balancing into a holistic control framework, our design incorporates reactive and predictive metrics to deduce the healthiness of executors and prescribes practically optimal scaling and load balancing decisions in time. We implement a prototype of StreamSwitch and integrate it with Apache Flink and Samza. Experimental evaluations on real-world applications and benchmarks show that StreamSwitch provides cost-effective solutions for bounding latency and outperforms the state-of-the-art alternative solutions.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133272303","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229035
Zhe Chen, Tianyue Zheng, Chao Cai, Yue-Xing Gao, Pengfei Hu, Jun Luo
Vibration sensing is crucial to human life and work, as vibrations indicate the status of their respective sources (e.g., heartbeat to human health condition). Given the inconvenience of contact sensing, both academia and industry have been intensively exploring contact-free vibration sensing, with several major developments leveraging radio-frequency (RF) technologies made very recently. However, a measurement study systematically comparing these options is still missing. In this paper, we choose to evaluate five representative commercial off-the-shelf (COTS) RF technologies with different carrier frequencies, bandwidths, and waveform designs. We first unify the sensing data format and processing pipeline, and also propose a novel metric v-SNR to quantify sensing quality. Then our extensive evaluations start from controlled experiments for benchmarking, followed by investigations on two real-world applications: machinery vibration measurement and vital sign monitoring. Our comprehensive study reveals that Wi-Fi performs the worst among all five technologies, while a lesser-known UWB-based technology achieves the best overall performance, and others have respective pros and cons in different scenarios.
{"title":"Wider is Better? Contact-free Vibration Sensing via Different COTS-RF Technologies","authors":"Zhe Chen, Tianyue Zheng, Chao Cai, Yue-Xing Gao, Pengfei Hu, Jun Luo","doi":"10.1109/INFOCOM53939.2023.10229035","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229035","url":null,"abstract":"Vibration sensing is crucial to human life and work, as vibrations indicate the status of their respective sources (e.g., heartbeat to human health condition). Given the inconvenience of contact sensing, both academia and industry have been intensively exploring contact-free vibration sensing, with several major developments leveraging radio-frequency (RF) technologies made very recently. However, a measurement study systematically comparing these options is still missing. In this paper, we choose to evaluate five representative commercial off-the-shelf (COTS) RF technologies with different carrier frequencies, bandwidths, and waveform designs. We first unify the sensing data format and processing pipeline, and also propose a novel metric v-SNR to quantify sensing quality. Then our extensive evaluations start from controlled experiments for benchmarking, followed by investigations on two real-world applications: machinery vibration measurement and vital sign monitoring. Our comprehensive study reveals that Wi-Fi performs the worst among all five technologies, while a lesser-known UWB-based technology achieves the best overall performance, and others have respective pros and cons in different scenarios.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133005449","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228868
Saray Sanchez, Kubra Alemdar, Vini Chaudhary, K. Chowdhury
Small form-factor single antenna devices, typically deployed within wireless sensor networks, lack many benefits of multi-antenna receivers like leveraging spatial diversity to enhance signal reception reliability. In this paper, we introduce the theory of achieving spatial diversity in such single-antenna systems by using reconfigurable intelligent surfaces (RIS). Our approach, called ‘RIS-STAR’, proposes a method of proactively perturbing the wireless propagation environment multiple times within the symbol time (that is less than the channel coherence time) through reconfiguring an RIS. By leveraging the stationarity of the channel, RIS-STAR ensures that the only source of perturbation is due to the chosen and controllable RIS configuration. We first formulate the problem to find the set of RIS configurations that maximizes channel hardening, which is a measure of link reliability. Our solution is independent of the transceiver’s relative location with respect to the RIS and does not require channel estimation, alleviating two key implementation concerns. We then evaluate the performance of RIS-STAR using a custom-simulator and an experimental testbed composed of PCB-fabricated RIS. Specifically, we demonstrate how a SISO link can be enhanced to perform similar to a SIMO link attaining an 84.6% channel hardening improvement in presence of strong multipath and non-line-of-sight conditions.
{"title":"RIS-STAR: RIS-based Spatio-Temporal Channel Hardening for Single-Antenna Receivers","authors":"Saray Sanchez, Kubra Alemdar, Vini Chaudhary, K. Chowdhury","doi":"10.1109/INFOCOM53939.2023.10228868","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228868","url":null,"abstract":"Small form-factor single antenna devices, typically deployed within wireless sensor networks, lack many benefits of multi-antenna receivers like leveraging spatial diversity to enhance signal reception reliability. In this paper, we introduce the theory of achieving spatial diversity in such single-antenna systems by using reconfigurable intelligent surfaces (RIS). Our approach, called ‘RIS-STAR’, proposes a method of proactively perturbing the wireless propagation environment multiple times within the symbol time (that is less than the channel coherence time) through reconfiguring an RIS. By leveraging the stationarity of the channel, RIS-STAR ensures that the only source of perturbation is due to the chosen and controllable RIS configuration. We first formulate the problem to find the set of RIS configurations that maximizes channel hardening, which is a measure of link reliability. Our solution is independent of the transceiver’s relative location with respect to the RIS and does not require channel estimation, alleviating two key implementation concerns. We then evaluate the performance of RIS-STAR using a custom-simulator and an experimental testbed composed of PCB-fabricated RIS. Specifically, we demonstrate how a SISO link can be enhanced to perform similar to a SIMO link attaining an 84.6% channel hardening improvement in presence of strong multipath and non-line-of-sight conditions.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133769829","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229028
Syed Waqas Haider Shah, Sai Pavan Deram, Joerg Widmer
Reconfigurable intelligent surfaces (RISs) have great potential to improve the coverage of mmWave networks; however, acquiring perfect channel state information (CSI) of a RIS-enabled mmWave network is very costly and should thus be done infrequently. At the same time, finding an optimal RIS configuration when CSI is outdated is challenging. To this end, this work aims to provide practical insights into the tradeoff between the outdatedness of the CSI and the system performance by using the effective capacity as analytical tool. We consider a RIS-enabled mmWave downlink where the base station (BS) operates under statistical quality-of-service (QoS) constraints. We find a closed-form expression for the effective capacity that incorporates the degree of optimism of packet scheduling and correlation strength between instantaneous and outdated CSI. Moreover, our analysis allows us to find optimal values of the signal-to-interference-plus-noise-ratio (SINR) distribution parameter and their impact on the effective capacity in different network scenarios. Simulation results demonstrate that better effective capacity can be achieved with suboptimal RIS configuration when the channel estimates are known to be outdated. It allows us to design system parameters that guarantee better performance while keeping the complexity and cost associated with channel estimation to a minimum.
{"title":"On the Effective Capacity of RIS-enabled mmWave Networks with Outdated CSI","authors":"Syed Waqas Haider Shah, Sai Pavan Deram, Joerg Widmer","doi":"10.1109/INFOCOM53939.2023.10229028","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229028","url":null,"abstract":"Reconfigurable intelligent surfaces (RISs) have great potential to improve the coverage of mmWave networks; however, acquiring perfect channel state information (CSI) of a RIS-enabled mmWave network is very costly and should thus be done infrequently. At the same time, finding an optimal RIS configuration when CSI is outdated is challenging. To this end, this work aims to provide practical insights into the tradeoff between the outdatedness of the CSI and the system performance by using the effective capacity as analytical tool. We consider a RIS-enabled mmWave downlink where the base station (BS) operates under statistical quality-of-service (QoS) constraints. We find a closed-form expression for the effective capacity that incorporates the degree of optimism of packet scheduling and correlation strength between instantaneous and outdated CSI. Moreover, our analysis allows us to find optimal values of the signal-to-interference-plus-noise-ratio (SINR) distribution parameter and their impact on the effective capacity in different network scenarios. Simulation results demonstrate that better effective capacity can be achieved with suboptimal RIS configuration when the channel estimates are known to be outdated. It allows us to design system parameters that guarantee better performance while keeping the complexity and cost associated with channel estimation to a minimum.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117149000","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 : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228901
Qingsong Liu, Zhixuan Fang
We consider the task scheduling scenario where the controller activates one from K task types at each time. Each task induces a random completion time, and a reward is obtained only after the task is completed. The statistics of the completion time and the reward distributions of all task types are unknown to the controller. The controller needs to learn to schedule tasks to maximize the accumulated reward within a given time horizon T . Motivated by the practical scenarios, we require the designed policy to satisfy a system throughput constraint. In addition, we introduce the interruption mechanism to terminate ongoing tasks that last longer than certain deadlines. To address this scheduling problem, we model it as an online learning problem with deadline and throughput constraints. Then, we characterize the optimal offline policy and develop efficient online learning algorithms based on the Lyapunov method. We prove that our online learning algorithm achieves an $O(sqrt T )$ regret and zero constraint violations. We also conduct simulations to evaluate the performance of our developed learning algorithms.
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