Pub Date : 2021-10-04DOI: 10.1109/infocom42981.2021.9488901
P. Muller, Guan-Ming Su, R. Hu, Nabil J. Sarhan
LCN 2019 received 135 full paper submissions. Each paper received a minimum of three reviews. In addition, a senior TPC member was assigned to each paper, who moderated the discussions and provided a final recommendation. Out of the 135 full paper submissions, 39 papers have been accepted. The authors submitted the final versions of up to 9 pages, resulting in an acceptance ratio of 28.9%. The acceptance ratio of the submitted short papers was 45%. Together with the papers transferred from the full paper track, a total of 39 short 4-page papers were accepted that will be presented as posters. The LCN conference proceedings include both full and short papers.
{"title":"Message from the TPC Chairs","authors":"P. Muller, Guan-Ming Su, R. Hu, Nabil J. Sarhan","doi":"10.1109/infocom42981.2021.9488901","DOIUrl":"https://doi.org/10.1109/infocom42981.2021.9488901","url":null,"abstract":"LCN 2019 received 135 full paper submissions. Each paper received a minimum of three reviews. In addition, a senior TPC member was assigned to each paper, who moderated the discussions and provided a final recommendation. Out of the 135 full paper submissions, 39 papers have been accepted. The authors submitted the final versions of up to 9 pages, resulting in an acceptance ratio of 28.9%. The acceptance ratio of the submitted short papers was 45%. Together with the papers transferred from the full paper track, a total of 39 short 4-page papers were accepted that will be presented as posters. The LCN conference proceedings include both full and short papers.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116356373","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488908
Kun Xie, Jiazheng Tian, Gaogang Xie, Guangxing Zhang, Dafang Zhang
Due to high network measurement cost, network-wide monitoring faces many challenges. For a network consisting of n nodes, the cost of one time network-wide monitoring will be O(n2). To reduce the monitoring cost, inspired by recent progress of matrix completion, a novel sparse network monitoring scheme is proposed to obtain network-wide monitoring data by sampling a few paths while inferring monitoring data of others. However, current sparse network monitoring schemes suffer from the problems of high measurement cost, high computation complexity in sampling scheduling, and long time to recover the un-sampled data. We propose a novel block matrix completion that can guarantee the quality of the un-sampled data inference by selecting as few as m = O(nr ln(r)) samples for a rank r N × T matrix with n = max{N,T}, which largely reduces the sampling complexity as compared to the existing algorithm for matrix completion. Based on block matrix completion, we further propose a light weight sampling scheduling algorithm to select measurement samples and a light weight data inference algorithm to quickly and accurately recover the un-sampled data. Extensive experiments on three real network monitoring data sets verify our theoretical claims and demonstrate the effectiveness of the proposed algorithms.
由于网络测量成本高，全网监控面临诸多挑战。对于由n个节点组成的网络，一次全网监控的成本为O(n2)。为了降低监控成本，受矩阵补全技术最新进展的启发，提出了一种新的稀疏网络监控方案，通过对几条路径进行采样，同时推断其他路径的监控数据，从而获得全网范围的监控数据。然而，目前的稀疏网络监测方案存在测量成本高、采样调度计算复杂度高、未采样数据恢复时间长等问题。我们提出了一种新的分块矩阵补全算法，通过对N = max{N,T}的秩为r N × T的矩阵选择m = O(nr ln(r))个样本，保证了未采样数据推断的质量，与现有的矩阵补全算法相比，大大降低了采样复杂度。在分块矩阵补全的基础上，我们进一步提出了轻量采样调度算法来选择测量样本，轻量数据推理算法来快速准确地恢复未采样数据。在三个真实网络监测数据集上进行的大量实验验证了我们的理论主张，并证明了所提出算法的有效性。
{"title":"Low Cost Sparse Network Monitoring Based on Block Matrix Completion","authors":"Kun Xie, Jiazheng Tian, Gaogang Xie, Guangxing Zhang, Dafang Zhang","doi":"10.1109/INFOCOM42981.2021.9488908","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488908","url":null,"abstract":"Due to high network measurement cost, network-wide monitoring faces many challenges. For a network consisting of n nodes, the cost of one time network-wide monitoring will be O(n2). To reduce the monitoring cost, inspired by recent progress of matrix completion, a novel sparse network monitoring scheme is proposed to obtain network-wide monitoring data by sampling a few paths while inferring monitoring data of others. However, current sparse network monitoring schemes suffer from the problems of high measurement cost, high computation complexity in sampling scheduling, and long time to recover the un-sampled data. We propose a novel block matrix completion that can guarantee the quality of the un-sampled data inference by selecting as few as m = O(nr ln(r)) samples for a rank r N × T matrix with n = max{N,T}, which largely reduces the sampling complexity as compared to the existing algorithm for matrix completion. Based on block matrix completion, we further propose a light weight sampling scheduling algorithm to select measurement samples and a light weight data inference algorithm to quickly and accurately recover the un-sampled data. Extensive experiments on three real network monitoring data sets verify our theoretical claims and demonstrate the effectiveness of the proposed algorithms.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125019812","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488673
Jhonatan Tavori, H. Levy
Geographically distributed cloud networks are used by a variety of applications and services worldwide. As the demand for these services increases, their data centers form an attractive target for malicious attackers, aiming at harming the services. In this study we address sophisticated attackers who aim at causing maximal-damage to the service.A worst-case (damage-maximizing) attack is an attack which minimizes the revenue of the system operator, due to disrupting the users from being served. A sophisticated attacker needs to decide how many attacking agents should be launched at each of the systems regions, in order to inflict maximal damage.We characterize and analyze damage-maximization strategies for a number of attacks including deterministic attack, concur-rent stochastic agents attack, approximation of a virus-spread attack and over-size binomial attack. We also address user-migration defense, allowing to dynamically migrate demands among regions, and we provide efficient algorithms for deriving worst-case attacks given a system with arbitrary placement and demands. The results form a basis for devising resource allocation strategies aiming at minimizing attack damages.
{"title":"Tornadoes In The Cloud: Worst-Case Attacks on Distributed Resources Systems","authors":"Jhonatan Tavori, H. Levy","doi":"10.1109/INFOCOM42981.2021.9488673","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488673","url":null,"abstract":"Geographically distributed cloud networks are used by a variety of applications and services worldwide. As the demand for these services increases, their data centers form an attractive target for malicious attackers, aiming at harming the services. In this study we address sophisticated attackers who aim at causing maximal-damage to the service.A worst-case (damage-maximizing) attack is an attack which minimizes the revenue of the system operator, due to disrupting the users from being served. A sophisticated attacker needs to decide how many attacking agents should be launched at each of the systems regions, in order to inflict maximal damage.We characterize and analyze damage-maximization strategies for a number of attacks including deterministic attack, concur-rent stochastic agents attack, approximation of a virus-spread attack and over-size binomial attack. We also address user-migration defense, allowing to dynamically migrate demands among regions, and we provide efficient algorithms for deriving worst-case attacks given a system with arbitrary placement and demands. The results form a basis for devising resource allocation strategies aiming at minimizing attack damages.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125134547","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488424
Borui Li, Wei Dong, Yi Gao
Programming a complete IoT application usually requires separated programming for device, edge and/or cloud sides, which slows down the development process and makes the project hardly portable. Existing solutions tackle this problem by proposing a single coherent language while leaving two issues unsolved: efficient migration among the three sides and the platform dependency of the binaries.We propose WiProg, an integrated approach to IoT application programming based on WebAssembly. WiProg proposes an edge-centric programming approach that enables developers to write the IoT application as if it runs on the edge. This is achieved by the peripheral-accessing SDKs and annotations specifying the computation placement. WiProg automatically processes the program to insert auxiliary code and then compile it to WebAssembly. At runtime, WiProg leverages dynamic code offloading with compact memory snapshotting to achieve efficient execution. WiProg also provides interfaces for the customization of offloading policies. Results on real-world applications and computation benchmarks show that WiProg achieves an average reduction by 18.7%~54.3% and 20.1%~57.6% in terms of energy consumption and execution time.
{"title":"WiProg: A WebAssembly-based Approach to Integrated IoT Programming","authors":"Borui Li, Wei Dong, Yi Gao","doi":"10.1109/INFOCOM42981.2021.9488424","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488424","url":null,"abstract":"Programming a complete IoT application usually requires separated programming for device, edge and/or cloud sides, which slows down the development process and makes the project hardly portable. Existing solutions tackle this problem by proposing a single coherent language while leaving two issues unsolved: efficient migration among the three sides and the platform dependency of the binaries.We propose WiProg, an integrated approach to IoT application programming based on WebAssembly. WiProg proposes an edge-centric programming approach that enables developers to write the IoT application as if it runs on the edge. This is achieved by the peripheral-accessing SDKs and annotations specifying the computation placement. WiProg automatically processes the program to insert auxiliary code and then compile it to WebAssembly. At runtime, WiProg leverages dynamic code offloading with compact memory snapshotting to achieve efficient execution. WiProg also provides interfaces for the customization of offloading policies. Results on real-world applications and computation benchmarks show that WiProg achieves an average reduction by 18.7%~54.3% and 20.1%~57.6% in terms of energy consumption and execution time.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125150279","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488769
Jiajie Tan, S. Chan
Wi-Fi-enabled devices such as smartphones periodically search for available networks by broadcasting probe requests which encapsulate MAC addresses as the device identifiers. To protect privacy (user identity and location), modern devices embed random MAC addresses in their probe frames, the so-called MAC address randomization. Such randomization greatly hampers statistical analysis such as people counting and trajectory inference. To mitigate its impact while respecting privacy, we propose Espresso, a simple, novel and efficient approach which establishes probe request association under MAC address randomization. Espresso models the frame association as a flow network, with frames as nodes and frame correlation as edge cost. To estimate the correlation between any two frames, it considers the multimodality of request frames, including information elements, sequence numbers and received signal strength. It then associates frames with minimum-cost flow optimization. To the best of our knowledge, this is the first piece of work that formulates the probe request association problem as network flow optimization using frame correlation. We have implemented Espresso and conducted extensive experiments in a leading shopping mall. Our results show that Espresso outperforms the state-of-the-art schemes in terms of discrimination accuracy (> 80%) and V-measure scores (> 0.85).
{"title":"Efficient Association of Wi-Fi Probe Requests under MAC Address Randomization","authors":"Jiajie Tan, S. Chan","doi":"10.1109/INFOCOM42981.2021.9488769","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488769","url":null,"abstract":"Wi-Fi-enabled devices such as smartphones periodically search for available networks by broadcasting probe requests which encapsulate MAC addresses as the device identifiers. To protect privacy (user identity and location), modern devices embed random MAC addresses in their probe frames, the so-called MAC address randomization. Such randomization greatly hampers statistical analysis such as people counting and trajectory inference. To mitigate its impact while respecting privacy, we propose Espresso, a simple, novel and efficient approach which establishes probe request association under MAC address randomization. Espresso models the frame association as a flow network, with frames as nodes and frame correlation as edge cost. To estimate the correlation between any two frames, it considers the multimodality of request frames, including information elements, sequence numbers and received signal strength. It then associates frames with minimum-cost flow optimization. To the best of our knowledge, this is the first piece of work that formulates the probe request association problem as network flow optimization using frame correlation. We have implemented Espresso and conducted extensive experiments in a leading shopping mall. Our results show that Espresso outperforms the state-of-the-art schemes in terms of discrimination accuracy (> 80%) and V-measure scores (> 0.85).","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115542794","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488768
Chao Liu, Penghao Wang, Ruobing Jiang, Yanmin Zhu
Acoustic target tracking has shown great advantages for device-free human-machine interaction over vision/RF based mechanisms. However, existing approaches for portable devices solely track single target, incapable for the ubiquitous and highly challenging multi-target situation such as double-hand multimedia controlling and multi-player gaming. In this paper, we propose AMT, a pioneering smartphone MIMO system to achieve centimeter-level multi-target tracking. Targets’ absolute distance are simultaneously ranged by performing multi-lateration locating with multiple speaker-microphone pairs. The unique challenge raised by MIMO is the superposition of multisource signals due to the cross-correlation among speakers. We tackle this challenge by applying Zadoff-Chu(ZC) sequences with strong auto-correlation and weak cross-correlation. The most distinguishing advantage of AMT lies in the elimination of target raised multipath effect, which is commonly ignored in previous work by hastily assuming targets as particles. Concerning the multipath echoes reflected by each non-particle target, we define the novel concept of primary echo to best represent target movement. AMT then improves tracking accuracy by detecting primary echo and filtering out minor echoes. Implemented on commercial smartphones, AMT achieves on average 1.13 cm and 2.46 cm error for single and double target tracking respectively and on average 97% accuracy for 6 controlling gestures recognition.
与基于视觉/射频的机制相比，声学目标跟踪在无设备人机交互方面显示出巨大的优势。然而，现有的便携式设备方法只能跟踪单个目标，无法适应双手多媒体控制和多人游戏等无处不在且极具挑战性的多目标情况。在本文中，我们提出了AMT，一个开创性的智能手机MIMO系统，以实现厘米级的多目标跟踪。采用多对扬声器-麦克风进行多平移定位，同时测距目标的绝对距离。MIMO带来的独特挑战是由于说话者之间的相互关联导致多源信号的叠加。为了解决这一问题，我们采用了强自相关和弱互相关的Zadoff-Chu(ZC)序列。AMT最显著的优势在于消除了目标引发的多径效应，而这一效应在以往的工作中往往被忽略，而将目标匆忙地假设为粒子。针对每个非粒子目标反射的多径回波，我们定义了主回波的新概念，以最好地反映目标的运动。然后，AMT通过检测主回波和滤除次要回波来提高跟踪精度。AMT在商用智能手机上实现，单目标跟踪和双目标跟踪的平均误差分别为1.13 cm和2.46 cm, 6个控制手势识别的平均准确率为97%。
{"title":"AMT: Acoustic Multi-target Tracking with Smartphone MIMO System","authors":"Chao Liu, Penghao Wang, Ruobing Jiang, Yanmin Zhu","doi":"10.1109/INFOCOM42981.2021.9488768","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488768","url":null,"abstract":"Acoustic target tracking has shown great advantages for device-free human-machine interaction over vision/RF based mechanisms. However, existing approaches for portable devices solely track single target, incapable for the ubiquitous and highly challenging multi-target situation such as double-hand multimedia controlling and multi-player gaming. In this paper, we propose AMT, a pioneering smartphone MIMO system to achieve centimeter-level multi-target tracking. Targets’ absolute distance are simultaneously ranged by performing multi-lateration locating with multiple speaker-microphone pairs. The unique challenge raised by MIMO is the superposition of multisource signals due to the cross-correlation among speakers. We tackle this challenge by applying Zadoff-Chu(ZC) sequences with strong auto-correlation and weak cross-correlation. The most distinguishing advantage of AMT lies in the elimination of target raised multipath effect, which is commonly ignored in previous work by hastily assuming targets as particles. Concerning the multipath echoes reflected by each non-particle target, we define the novel concept of primary echo to best represent target movement. AMT then improves tracking accuracy by detecting primary echo and filtering out minor echoes. Implemented on commercial smartphones, AMT achieves on average 1.13 cm and 2.46 cm error for single and double target tracking respectively and on average 97% accuracy for 6 controlling gestures recognition.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129517987","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488692
Weirong Chen, Jiaqi Zheng, Haoyu Yu
The increasing challenge in designing online algorithms lies in the distribution uncertainty. To cope with the distribution variations in online optimization, an intuitive idea is to reselect an algorithm from the candidate set that will be more suitable to future distributions. In this paper, we propose Ostasos, an automatic algorithm selection framework that can choose the most suitable algorithm on the fly with provable guarantees. Rigorous theoretical analysis demonstrates that the performance of Ostasos is no worse than that of any candidate algorithms in terms of competitive ratio. Finally, we apply Ostasos to the online car-hailing problem and trace-driven experiments verify the effectiveness of Ostasos.
{"title":"Dynamically Choosing the Candidate Algorithm with Ostasos in Online Optimization","authors":"Weirong Chen, Jiaqi Zheng, Haoyu Yu","doi":"10.1109/INFOCOM42981.2021.9488692","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488692","url":null,"abstract":"The increasing challenge in designing online algorithms lies in the distribution uncertainty. To cope with the distribution variations in online optimization, an intuitive idea is to reselect an algorithm from the candidate set that will be more suitable to future distributions. In this paper, we propose Ostasos, an automatic algorithm selection framework that can choose the most suitable algorithm on the fly with provable guarantees. Rigorous theoretical analysis demonstrates that the performance of Ostasos is no worse than that of any candidate algorithms in terms of competitive ratio. Finally, we apply Ostasos to the online car-hailing problem and trace-driven experiments verify the effectiveness of Ostasos.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128446020","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488721
Hao Song, Lingjia Liu, Bodong Shang, Scott M. Pudlewski, E. Bentley
Existing routing protocols may not be applicable in UAV networks because of their dynamic network topology and lack of accurate position information. In this paper, an enhanced flooding-based routing protocol is designed based on random network coding (RNC) and clustering for swarm UAV networks, enabling the efficient routing process without any routing path discovery or network topology information. RNC can naturally accelerate the routing process, with which in some hops fewer generations need to be transmitted. To address the issue of numerous hops and further expedite routing process, a clustering method is leveraged, where UAV networks are partitioned into multiple clusters and generations are only flooded from representatives of each cluster rather than flooded from each UAV. By this way, the amount of hops can be significantly reduced. The technical details of the introduced routing protocol are designed. Moreover, to capture the dynamic network topology, the Poisson cluster process is employed to model UAV networks. Afterwards, stochastic geometry tools are utilized to derive the distance distribution between two random selected UAVs and analytically evaluate performance. Extensive simulation studies are conducted to prove the validation of performance analysis, demonstrate the effectiveness of our designed routing protocol, and reveal its design insight.
{"title":"Enhanced Flooding-Based Routing Protocol for Swarm UAV Networks: Random Network Coding Meets Clustering","authors":"Hao Song, Lingjia Liu, Bodong Shang, Scott M. Pudlewski, E. Bentley","doi":"10.1109/INFOCOM42981.2021.9488721","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488721","url":null,"abstract":"Existing routing protocols may not be applicable in UAV networks because of their dynamic network topology and lack of accurate position information. In this paper, an enhanced flooding-based routing protocol is designed based on random network coding (RNC) and clustering for swarm UAV networks, enabling the efficient routing process without any routing path discovery or network topology information. RNC can naturally accelerate the routing process, with which in some hops fewer generations need to be transmitted. To address the issue of numerous hops and further expedite routing process, a clustering method is leveraged, where UAV networks are partitioned into multiple clusters and generations are only flooded from representatives of each cluster rather than flooded from each UAV. By this way, the amount of hops can be significantly reduced. The technical details of the introduced routing protocol are designed. Moreover, to capture the dynamic network topology, the Poisson cluster process is employed to model UAV networks. Afterwards, stochastic geometry tools are utilized to derive the distance distribution between two random selected UAVs and analytically evaluate performance. Extensive simulation studies are conducted to prove the validation of performance analysis, demonstrate the effectiveness of our designed routing protocol, and reveal its design insight.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128241018","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488843
Xu Wang, Zheng Yang, Jiahang Wu, Yi Zhao, Zimu Zhou
Accurate, real-time object detection on resource-constrained devices enables autonomous mobile vision applications such as traffic surveillance, situational awareness, and safety inspection, where it is crucial to detect both small and large objects in crowded scenes. Prior studies either perform object detection locally on-board or offload the task to the edge/cloud. Local object detection yields low accuracy on small objects since it operates on low-resolution videos to fit in mobile memory. Offloaded object detection incurs high latency due to uploading high-resolution videos to the edge/cloud. Rather than either pure local processing or offloading, we propose to detect large objects locally while offloading small object detection to the edge. The key challenge is to reduce the latency of small object detection. Accordingly, we develop EdgeDuet, the first edge-device collaborative framework for enhancing small object detection with tile-level parallelism. It optimizes the offloaded detection pipeline in tiles rather than the entire frame for high accuracy and low latency. Evaluations on drone vision datasets under LTE, WiFi 2.4GHz, WiFi 5GHz show that EdgeDuet outperforms local object detection in small object detection accuracy by 233.0%. It also improves the detection accuracy by 44.7% and latency by 34.2% over the state-of-the-art offloading schemes.
{"title":"EdgeDuet: Tiling Small Object Detection for Edge Assisted Autonomous Mobile Vision","authors":"Xu Wang, Zheng Yang, Jiahang Wu, Yi Zhao, Zimu Zhou","doi":"10.1109/INFOCOM42981.2021.9488843","DOIUrl":"https://doi.org/10.1109/INFOCOM42981.2021.9488843","url":null,"abstract":"Accurate, real-time object detection on resource-constrained devices enables autonomous mobile vision applications such as traffic surveillance, situational awareness, and safety inspection, where it is crucial to detect both small and large objects in crowded scenes. Prior studies either perform object detection locally on-board or offload the task to the edge/cloud. Local object detection yields low accuracy on small objects since it operates on low-resolution videos to fit in mobile memory. Offloaded object detection incurs high latency due to uploading high-resolution videos to the edge/cloud. Rather than either pure local processing or offloading, we propose to detect large objects locally while offloading small object detection to the edge. The key challenge is to reduce the latency of small object detection. Accordingly, we develop EdgeDuet, the first edge-device collaborative framework for enhancing small object detection with tile-level parallelism. It optimizes the offloaded detection pipeline in tiles rather than the entire frame for high accuracy and low latency. Evaluations on drone vision datasets under LTE, WiFi 2.4GHz, WiFi 5GHz show that EdgeDuet outperforms local object detection in small object detection accuracy by 233.0%. It also improves the detection accuracy by 44.7% and latency by 34.2% over the state-of-the-art offloading schemes.","PeriodicalId":293079,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130622834","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 : 2021-05-10DOI: 10.1109/INFOCOM42981.2021.9488742
I. Koutsopoulos
We study physical-layer (PHY) baseband functional split policies in 5G Centralized Radio-Access-Network (C-RAN) architectures that include a central location, the baseband unit (BBU) with some BBU servers, and a set of Base Stations (BSs), the remote radio heads (RRHs), each with a RRH server. Each RRH is connected to the BBU location through a fronthaul link. We consider a scenario with many frame streams at the BBU location, where each stream needs to be processed by a BBU server before being sent to a remote radio-head (RRH). For each stream, a functional split needs to be selected, which provides a way of partitioning the computational load of the baseband processing chain for stream frames between the BBU and RRH servers. For streams that are served by the same BBU server, a scheduling policy is also needed. We formulate and solve the joint resource allocation problem of functional split selection, BBU server allocation and server scheduling, with the goal to minimize total average end-to-end delay or to minimize maximum average delay over RRH streams. The total average end-to-end delay is the sum of (i) scheduling (queueing) and processing delay at the BBU servers, (ii) data transport delay at the fronthaul link, and (iii) processing delay at the RRH server. Numerical results show the resulting delay improvements, if we incorporate functional split selection in resource allocation.
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