Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651974
Chaoyi Ma, Haibo Wang, Olufemi O. Odegbile, Shigang Chen
Sampling is key to handling mismatch between the line rate and the throughput of a network traffic measurement module. Flow-spread measurement requires non-duplicate sampling, which only samples the elements (carried in packet header or payload) in each flow when they appear for the first time and blocks them for subsequent appearances. The only prior work for non-duplicate sampling incurs considerable overhead, and has two practical limitations: It lacks a mechanism to set an appropriate sampling probability under dynamic traffic conditions, and it cannot efficiently handle multiple concurrent sampling tasks. This paper proposes a virtual filter design for non-duplicate sampling, which reduces the processing overhead by about half and reduces the memory overhead by an order of magnitude or more under some practical settings. It has a mechanism to automatically adapt its sampling probability to the traffic dynamics. It can be extended to solve a new problem called non-duplicate distribution sampling, which samples packets based on a probability distribution to support multiple concurrent measurement tasks.
{"title":"Virtual Filter for Non-duplicate Sampling","authors":"Chaoyi Ma, Haibo Wang, Olufemi O. Odegbile, Shigang Chen","doi":"10.1109/ICNP52444.2021.9651974","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651974","url":null,"abstract":"Sampling is key to handling mismatch between the line rate and the throughput of a network traffic measurement module. Flow-spread measurement requires non-duplicate sampling, which only samples the elements (carried in packet header or payload) in each flow when they appear for the first time and blocks them for subsequent appearances. The only prior work for non-duplicate sampling incurs considerable overhead, and has two practical limitations: It lacks a mechanism to set an appropriate sampling probability under dynamic traffic conditions, and it cannot efficiently handle multiple concurrent sampling tasks. This paper proposes a virtual filter design for non-duplicate sampling, which reduces the processing overhead by about half and reduces the memory overhead by an order of magnitude or more under some practical settings. It has a mechanism to automatically adapt its sampling probability to the traffic dynamics. It can be extended to solve a new problem called non-duplicate distribution sampling, which samples packets based on a probability distribution to support multiple concurrent measurement tasks.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124437355","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651923
Russell Shirey, Sanjay G. Rao, S. Sundaram
Unmanned Aerial Systems (UAS) collect and transmit data such as live video and radar images, which have different latency and reliability requirements, over wireless links that exhibit much performance variability. In this paper, we make three contributions. First, we show through a characterization of two real-world UAS flight datasets that there is significant opportunity to optimize data transmission in UAS settings by exploiting knowledge of UAS flight paths. Second, we developed Chimera, a system that taps into this opportunity while transmitting heterogeneous data streams over UAS networks. Chimera learns a model online that relates UAS network throughput to the flight path, and combines the model with a control framework that optimizes transmissions based on long-range throughput prediction. Third, with a combination of emulation and simulation experiments using real-world flight traces, we show Chimera’s effectiveness. Specifically, Chimera reduces penalties related to dropped radar images by 72.4%−100% compared to an algorithm agnostic to flight path information, and achieves an average bitrate of 90.5% compared to an optimal scheme that knows the exact future throughput, with only a minimal increase in radar images dropped.
{"title":"Chimera: exploiting UAS flight path information to optimize heterogeneous data transmission","authors":"Russell Shirey, Sanjay G. Rao, S. Sundaram","doi":"10.1109/ICNP52444.2021.9651923","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651923","url":null,"abstract":"Unmanned Aerial Systems (UAS) collect and transmit data such as live video and radar images, which have different latency and reliability requirements, over wireless links that exhibit much performance variability. In this paper, we make three contributions. First, we show through a characterization of two real-world UAS flight datasets that there is significant opportunity to optimize data transmission in UAS settings by exploiting knowledge of UAS flight paths. Second, we developed Chimera, a system that taps into this opportunity while transmitting heterogeneous data streams over UAS networks. Chimera learns a model online that relates UAS network throughput to the flight path, and combines the model with a control framework that optimizes transmissions based on long-range throughput prediction. Third, with a combination of emulation and simulation experiments using real-world flight traces, we show Chimera’s effectiveness. Specifically, Chimera reduces penalties related to dropped radar images by 72.4%−100% compared to an algorithm agnostic to flight path information, and achieves an average bitrate of 90.5% compared to an optimal scheme that knows the exact future throughput, with only a minimal increase in radar images dropped.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126450191","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651988
Gaoxiong Zeng, J. Qiu, Yifei Yuan, H. Liu, Kai Chen
In recent years, large enterprises (e.g., Google, Alibaba, etc.) have been building and deploying their wide-area routers based on shallow-buffered switching chips. However, with legacy reactive transport (e.g., TCP Cubic), shallow buffer can easily get overwhelmed by large BDP wide-area traffic, leading to high packet losses and degraded throughput. To address it, we ask: can we design a transport to simultaneously achieve high throughput and low loss for shallow-buffered WAN?We answer this question affirmatively by employing proactive congestion control (PCC). However, two issues exist for existing PCC to work on WAN. Firstly, wide-area traffics have diverse RTTs, leading to what we called imperfect scheduling issue (e.g., data crash in time). Secondly, there is one RTT delay for credits to trigger data sending, which may degrade network performance. Therefore, we propose a novel PCC design - FlashPass. To address the first issue, FlashPass adopts sender-driven emulation process with send time calibration to avoid the data packet crash. To address the second issue, FLASHPASS enables early data transmission in the starting phase, and incorporates an over-provisioning with selective dropping mechanism for efficient credit allocation in the finishing phase. Our evaluation with production workload demonstrates that FlashPass reduces the overall flow completion times of TCP Cubic and ExpressPass by up to 32% and 11.4%, and the 99-th tail completion times of small flows by up to 49.5% and 38%, respectively.
{"title":"FlashPass: Proactive Congestion Control for Shallow-buffered WAN","authors":"Gaoxiong Zeng, J. Qiu, Yifei Yuan, H. Liu, Kai Chen","doi":"10.1109/ICNP52444.2021.9651988","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651988","url":null,"abstract":"In recent years, large enterprises (e.g., Google, Alibaba, etc.) have been building and deploying their wide-area routers based on shallow-buffered switching chips. However, with legacy reactive transport (e.g., TCP Cubic), shallow buffer can easily get overwhelmed by large BDP wide-area traffic, leading to high packet losses and degraded throughput. To address it, we ask: can we design a transport to simultaneously achieve high throughput and low loss for shallow-buffered WAN?We answer this question affirmatively by employing proactive congestion control (PCC). However, two issues exist for existing PCC to work on WAN. Firstly, wide-area traffics have diverse RTTs, leading to what we called imperfect scheduling issue (e.g., data crash in time). Secondly, there is one RTT delay for credits to trigger data sending, which may degrade network performance. Therefore, we propose a novel PCC design - FlashPass. To address the first issue, FlashPass adopts sender-driven emulation process with send time calibration to avoid the data packet crash. To address the second issue, FLASHPASS enables early data transmission in the starting phase, and incorporates an over-provisioning with selective dropping mechanism for efficient credit allocation in the finishing phase. Our evaluation with production workload demonstrates that FlashPass reduces the overall flow completion times of TCP Cubic and ExpressPass by up to 32% and 11.4%, and the 99-th tail completion times of small flows by up to 49.5% and 38%, respectively.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132621708","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651921
Haibo Wang, Tao Gao, Weizhen Dang, Jing’an Xue, Jiahao Cao, Fenghua Li, Jilong Wang
In recent years, more and more wireless networks support both 2.4GHz and 5GHz bands. However, in large-scale dual-band wireless networks, lack of understanding on the behavior and performance makes the network diagnosis and optimization extremely challenging. In this paper, we conduct a comprehensive measurement to characterize the behavior and performance in a large-scale dual-band wireless network (TD WLAN). We make several meaningful observations. (1) Although the 5GHz band outperforms the 2.4GHz band, 60% of devices tend to be associated with the 2.4GHz band. The device association behavior has a large impact on the performance. (2) Rogue and non-WiFi devices are prevalent, wherein hidden terminal interference increases the average loss rate by 8%, carrier sense interference increases the average WiFi latency by 45%, and RF interference further aggravates both packet loss and channel contention. (3) The dynamic channel assignment strategy is not always effective. On this basis, we propose a novel and easy-to-implement strategy to improve the wireless performance by intelligent band navigation and heuristic channel optimization. The actual deployment in TD WLAN shows the packet loss reduces by 40% on average and the WiFi latency for more than 60% of devices is below 5ms.
{"title":"Hopping on Spectrum: Measuring and Boosting a Large-scale Dual-band Wireless Network","authors":"Haibo Wang, Tao Gao, Weizhen Dang, Jing’an Xue, Jiahao Cao, Fenghua Li, Jilong Wang","doi":"10.1109/ICNP52444.2021.9651921","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651921","url":null,"abstract":"In recent years, more and more wireless networks support both 2.4GHz and 5GHz bands. However, in large-scale dual-band wireless networks, lack of understanding on the behavior and performance makes the network diagnosis and optimization extremely challenging. In this paper, we conduct a comprehensive measurement to characterize the behavior and performance in a large-scale dual-band wireless network (TD WLAN). We make several meaningful observations. (1) Although the 5GHz band outperforms the 2.4GHz band, 60% of devices tend to be associated with the 2.4GHz band. The device association behavior has a large impact on the performance. (2) Rogue and non-WiFi devices are prevalent, wherein hidden terminal interference increases the average loss rate by 8%, carrier sense interference increases the average WiFi latency by 45%, and RF interference further aggravates both packet loss and channel contention. (3) The dynamic channel assignment strategy is not always effective. On this basis, we propose a novel and easy-to-implement strategy to improve the wireless performance by intelligent band navigation and heuristic channel optimization. The actual deployment in TD WLAN shows the packet loss reduces by 40% on average and the WiFi latency for more than 60% of devices is below 5ms.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133279193","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651965
Ruyi Yao, Cong Luo, Xuandong Liu, Ying Wan, B. Liu, Wen J. Li, Yang Xu
Ternary Content-Addressable Memory (TCAM) is a popular solution for high-speed flow table lookup in Software-Defined Networking (SDN). Rule insertion in TCAM is a time-consuming operation. To ensure semantic correctness, rules overlapped must be stored in TCAM with decreasing priority order and many rule movements may be needed to make space for a single inserted rule. When a rule insertion is in progress, the regular flow table lookup will be suspended, which could lead to a degraded user experience for SDN applications. In this paper, we propose a multiple-TCAM framework named MagicTCAM to reduce the rule movements during a rule insertion. The core of MagicTCAM lies in three operations: layering, partitioning and rotating. By layering, rules with the least overlapping will be grouped (i.e., layered) into a sub-ruleset. The number of rule movements is therefore greatly reduced as most of rules in a sub-ruleset are non-overlapped. To achieve balanced load in TCAMs, rules in each sub-ruleset are further partitioned and dispatched into different TCAMs in a rotating manner. In addition, an inter-TCAM movement algorithm is proposed to allow rules to be moved between TCAMs for reduced rule movement. Experiment results show that with two half-sized TCAMs, MagicTCAM reduces the rule movements by 39% on average compared with the state-of-the-art work while the computation time is shortened by half as well.
{"title":"MagicTCAM: A Multiple-TCAM Scheme for Fast TCAM Update","authors":"Ruyi Yao, Cong Luo, Xuandong Liu, Ying Wan, B. Liu, Wen J. Li, Yang Xu","doi":"10.1109/ICNP52444.2021.9651965","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651965","url":null,"abstract":"Ternary Content-Addressable Memory (TCAM) is a popular solution for high-speed flow table lookup in Software-Defined Networking (SDN). Rule insertion in TCAM is a time-consuming operation. To ensure semantic correctness, rules overlapped must be stored in TCAM with decreasing priority order and many rule movements may be needed to make space for a single inserted rule. When a rule insertion is in progress, the regular flow table lookup will be suspended, which could lead to a degraded user experience for SDN applications. In this paper, we propose a multiple-TCAM framework named MagicTCAM to reduce the rule movements during a rule insertion. The core of MagicTCAM lies in three operations: layering, partitioning and rotating. By layering, rules with the least overlapping will be grouped (i.e., layered) into a sub-ruleset. The number of rule movements is therefore greatly reduced as most of rules in a sub-ruleset are non-overlapped. To achieve balanced load in TCAMs, rules in each sub-ruleset are further partitioned and dispatched into different TCAMs in a rotating manner. In addition, an inter-TCAM movement algorithm is proposed to allow rules to be moved between TCAMs for reduced rule movement. Experiment results show that with two half-sized TCAMs, MagicTCAM reduces the rule movements by 39% on average compared with the state-of-the-art work while the computation time is shortened by half as well.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124765052","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}
The development of datacenter applications leads to the need for end-to-end communication with microsecond latency. As a result, RDMA is becoming prevalent in datacenter networks to mitigate the latency caused by the slow processing speed of the traditional software network stack. However, existing RDMA congestion control mechanisms are either far from optimal in simultaneously achieving high throughput and low latency or in need of additional in-network function support. In this paper, by leveraging the observation that most congestion occurs at the last hop in datacenter networks, we propose RCC, a receiver-driven rapid congestion control mechanism for RDMA networks that combines explicit assignment and iterative window adjustment. Firstly, we propose a network congestion distinguish method to classify congestions into two types, last-hop congestion and innetwork congestion. Then, an Explicit Window Assignment mechanism is proposed to solve the last-hop congestion, which enables senders to converge to a proper sending rate in one-RTT. For in-network congestion, a PID-based iterative delay-based window adjustment scheme is proposed to achieve fast convergence and near-zero queuing latency. RCC does not need additional innetwork support and is friendly to hardware implementation. In our evaluation, the overall average FCT (Flow Completion Time) of RCC is 4~79% better than Homa, ExpressPass, DCQCN, TIMELY, and HPCC.
{"title":"Receiver-Driven RDMA Congestion Control by Differentiating Congestion Types in Datacenter Networks","authors":"Jiao Zhang, Jiaming Shi, Xiaolong Zhong, Zirui Wan, Yuxing Tian, Tian Pan, Tao Huang","doi":"10.1109/ICNP52444.2021.9651938","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651938","url":null,"abstract":"The development of datacenter applications leads to the need for end-to-end communication with microsecond latency. As a result, RDMA is becoming prevalent in datacenter networks to mitigate the latency caused by the slow processing speed of the traditional software network stack. However, existing RDMA congestion control mechanisms are either far from optimal in simultaneously achieving high throughput and low latency or in need of additional in-network function support. In this paper, by leveraging the observation that most congestion occurs at the last hop in datacenter networks, we propose RCC, a receiver-driven rapid congestion control mechanism for RDMA networks that combines explicit assignment and iterative window adjustment. Firstly, we propose a network congestion distinguish method to classify congestions into two types, last-hop congestion and innetwork congestion. Then, an Explicit Window Assignment mechanism is proposed to solve the last-hop congestion, which enables senders to converge to a proper sending rate in one-RTT. For in-network congestion, a PID-based iterative delay-based window adjustment scheme is proposed to achieve fast convergence and near-zero queuing latency. RCC does not need additional innetwork support and is friendly to hardware implementation. In our evaluation, the overall average FCT (Flow Completion Time) of RCC is 4~79% better than Homa, ExpressPass, DCQCN, TIMELY, and HPCC.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124553827","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651987
Hebin Yu, Jiaqi Zheng, Zhuoxuan Du, Guihai Chen
Multipath TCP (MPTCP) is a burgeoning transport protocol which enables the server to split the traffic across multiple network interfaces. Classic MPTCPs have good friendliness and practicality such as relatively low overhead, but are hard to achieve consistent high-throughput and adaptability, especially for the ability of flexibly balancing congestion among different paths. In contrast, learning-based MPTCPs can essentially achieve consistent high-throughput and adaptability, but have poor friendliness and practicality. In this paper, we proposed MPLibra, a combined multipath congestion control framework that can complement the advantages of classic MPTCPs and learning-based MPTCPs. Extensive simulations on NS3 show that MPLibra can achieve good performance and outperform state-of-the-art MPTCPs under different network conditions. MPLibra improves the throughput by 40.5% and reduces the file download time by 47.7% compared with LIA, achieves good friendliness and balances congestion timely.
{"title":"MPLibra: Complementing the Benefits of Classic and Learning-based Multipath Congestion Control","authors":"Hebin Yu, Jiaqi Zheng, Zhuoxuan Du, Guihai Chen","doi":"10.1109/ICNP52444.2021.9651987","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651987","url":null,"abstract":"Multipath TCP (MPTCP) is a burgeoning transport protocol which enables the server to split the traffic across multiple network interfaces. Classic MPTCPs have good friendliness and practicality such as relatively low overhead, but are hard to achieve consistent high-throughput and adaptability, especially for the ability of flexibly balancing congestion among different paths. In contrast, learning-based MPTCPs can essentially achieve consistent high-throughput and adaptability, but have poor friendliness and practicality. In this paper, we proposed MPLibra, a combined multipath congestion control framework that can complement the advantages of classic MPTCPs and learning-based MPTCPs. Extensive simulations on NS3 show that MPLibra can achieve good performance and outperform state-of-the-art MPTCPs under different network conditions. MPLibra improves the throughput by 40.5% and reduces the file download time by 47.7% compared with LIA, achieves good friendliness and balances congestion timely.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117119809","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651953
Kristjon Ciko, M. Welzl, P. Teymoori
Deploying a new network architecture in the Internet requires changing some, but not necessarily all elements between communicating applications. One way to achieve gradual deployment is a proxy or gateway which "translates" between the new architecture and TCP/IP. We present such a proxy, called "Performance Enhancing Proxy for Deploying Network Architectures (PEP-DNA)", which allows TCP/IP applications to benefit from advanced features of a new network architecture without having to be redeveloped. Our proxy is a kernel-based Linux implementation which can be installed wherever a translation needs to occur between a new architecture and TCP/IP domains. We discuss the proxy operation in detail and evaluate its efficiency and performance in a local testbed, demonstrating that it achieves high throughput with low additional latency overhead. In our experiments, we use the Recursive InterNetwork Architecture (RINA) and Information-Centric Networking (ICN) as examples, but our proxy is modular and flexible, and hence enables realistic gradual deployment of any new "clean-slate" approaches.
{"title":"PEP-DNA: A Performance Enhancing Proxy for Deploying Network Architectures","authors":"Kristjon Ciko, M. Welzl, P. Teymoori","doi":"10.1109/ICNP52444.2021.9651953","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651953","url":null,"abstract":"Deploying a new network architecture in the Internet requires changing some, but not necessarily all elements between communicating applications. One way to achieve gradual deployment is a proxy or gateway which \"translates\" between the new architecture and TCP/IP. We present such a proxy, called \"Performance Enhancing Proxy for Deploying Network Architectures (PEP-DNA)\", which allows TCP/IP applications to benefit from advanced features of a new network architecture without having to be redeveloped. Our proxy is a kernel-based Linux implementation which can be installed wherever a translation needs to occur between a new architecture and TCP/IP domains. We discuss the proxy operation in detail and evaluate its efficiency and performance in a local testbed, demonstrating that it achieves high throughput with low additional latency overhead. In our experiments, we use the Recursive InterNetwork Architecture (RINA) and Information-Centric Networking (ICN) as examples, but our proxy is modular and flexible, and hence enables realistic gradual deployment of any new \"clean-slate\" approaches.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131512786","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651932
Mingsheng Yin, Tuyen X. Tran, Abhigyan Sharma, M. Mezzavilla, S. Rangan
There is a growing interest in reusing cellular base stations on the ground to provide long range, high-speed wireless connectivity to UAVs. Towards this goal, we present SkyRoute – a novel and powerful simulation platform for rapid and realistic assessment of UAV cellular connectivity. SkyRoute combines real base station locations and antenna data with a lightweight version of the widely-used ns-3 simulation platform for full-stack wireless channel and cellular network simulation. As an exemplary application, we demonstrate realistic coverage and cell selection prediction in a large metropolitan area.
{"title":"Demo: SkyRoute, a Fast and Realistic UAV Cellular Simulation Framework","authors":"Mingsheng Yin, Tuyen X. Tran, Abhigyan Sharma, M. Mezzavilla, S. Rangan","doi":"10.1109/ICNP52444.2021.9651932","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651932","url":null,"abstract":"There is a growing interest in reusing cellular base stations on the ground to provide long range, high-speed wireless connectivity to UAVs. Towards this goal, we present SkyRoute – a novel and powerful simulation platform for rapid and realistic assessment of UAV cellular connectivity. SkyRoute combines real base station locations and antenna data with a lightweight version of the widely-used ns-3 simulation platform for full-stack wireless channel and cellular network simulation. As an exemplary application, we demonstrate realistic coverage and cell selection prediction in a large metropolitan area.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131158390","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 : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651919
Zeqi Lai, Qianxia Wu, Hewu Li, M. Lv, Jianping Wu
Satellite-based Earth Observation (EO) systems are gaining popularity and widely used in many time-sensitive scenarios, including disaster monitoring, emergency response, forecasting and defense. Existing efforts for gathering EO data mainly rely on either ground station networks or geostationary (GEO) satellites. However, our quantitative analysis reveals that existing approaches are either limited as their achievable latency is far away from the desired value due to the insufficient coverage of ground stations, or hard to scale as the number of sensing satellites increases because of the high cost of GEO satellite relays.This paper explores the feasibility and performance of a novel approach that leverages emerging low Earth orbit (LEO) constellations to enable low-latency and scalable EO data delivery from space. We present OrbitCast, a hybrid EO data delivery architecture upon LEO constellations and geo-distributed ground stations to forward EO data from the source remote sensing satellite to a collection of end users. To handle the network dynamicity caused by LEO satellite movements and achieve stable communication over the satellite network, we propose a geo-location driven scheme to forward and deliver data packets. To demonstrate the effectiveness of OrbitCast, we build a testbed driven by public constellation information and implement the OrbitCast prototype on top of the testbed. Extensive realistic-data-driven simulations demonstrate that OrbitCast can significantly reduce the latency as compared to other state-of-the-art approaches, and complete the data delivery within five minutes for representative EO data traffic.
{"title":"OrbitCast: Exploiting Mega-Constellations for Low-Latency Earth Observation","authors":"Zeqi Lai, Qianxia Wu, Hewu Li, M. Lv, Jianping Wu","doi":"10.1109/ICNP52444.2021.9651919","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651919","url":null,"abstract":"Satellite-based Earth Observation (EO) systems are gaining popularity and widely used in many time-sensitive scenarios, including disaster monitoring, emergency response, forecasting and defense. Existing efforts for gathering EO data mainly rely on either ground station networks or geostationary (GEO) satellites. However, our quantitative analysis reveals that existing approaches are either limited as their achievable latency is far away from the desired value due to the insufficient coverage of ground stations, or hard to scale as the number of sensing satellites increases because of the high cost of GEO satellite relays.This paper explores the feasibility and performance of a novel approach that leverages emerging low Earth orbit (LEO) constellations to enable low-latency and scalable EO data delivery from space. We present OrbitCast, a hybrid EO data delivery architecture upon LEO constellations and geo-distributed ground stations to forward EO data from the source remote sensing satellite to a collection of end users. To handle the network dynamicity caused by LEO satellite movements and achieve stable communication over the satellite network, we propose a geo-location driven scheme to forward and deliver data packets. To demonstrate the effectiveness of OrbitCast, we build a testbed driven by public constellation information and implement the OrbitCast prototype on top of the testbed. Extensive realistic-data-driven simulations demonstrate that OrbitCast can significantly reduce the latency as compared to other state-of-the-art approaches, and complete the data delivery within five minutes for representative EO data traffic.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124403554","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}