2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)最新文献

{"title":"Adaptive Clustered Federated Learning for Clients with Time-Varying Interests","authors":"Ne Wang, Ruiting Zhou, Lina Su, Guang Fang, Zong-Qiang Li","doi":"10.1109/IWQoS54832.2022.9812926","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812926","url":null,"abstract":"Clustered Federated Learning (FL) addresses heterogeneous objectives from different client groups, by capturing the intrinsic relationship between data distributions of clients. This work aims to minimize the completion time of clustered FL training while guaranteeing convergence, given the following challenges. First, clients’ data distributions are not static since their interests are usually time-varying. Obsolete data may incur training failures, requiring detection of distribution changes at runtime. Second, even with the same distribution, client datasets may have different contributions to model accuracy. Besides, the training data typically arrive at clients dynamically, which brings uncertainties to assessing the quality of client data. Third, the execution environments of clients and networks are often unstable and stochastic, leading to uncertainties in calculating computation and communication time. Given the above challenges, we propose Acct with two innovations: i) change detection: we first model the time-varying interests of clients as piecewise stationary based on practical observations, then apply generalized likelihood ratio detectors to FL for detecting changes in client distributions; ii) client selection: we adopt the multi-armed bandit (MAB) technique to account for the uncertainties in measuring data quality, computation and communication time. Based on the upper confidence bound (UCB) method, we construct a novel “double UCB” policy to adaptively select clients with high data quality and low computation and communication overhead. We rigorously prove the convergence of Acct and sub-linear regret regarding the proposed client selection policy. Finally, we implement Acct using PyTorch and conduct experiments showing that Acct reduces the completion time by almost 18.2% compared with three state-of-the-art FL frameworks.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133423104","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}

{"title":"Blind-area Elimination in Video Surveillance Systems by WiFi Sensing with Minimum QoS Loss","authors":"Linqing Gui, Wenyang Yuan, Fu Xiao","doi":"10.1109/IWQoS54832.2022.9812921","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812921","url":null,"abstract":"Video surveillance systems have demonstrated their great importance in security protection these years. However, due to limited budget, installing cameras in every place of surveillance region is not practical and then blind areas become inevitable. As a result, eliminating blind areas with the lowest cost has become a tough challenge. To the best of our knowledge, this is the first work that fixes the blind spots of video surveillance systems based on WiFi sensing technique. By taking existing WiFi infrastructure as the sensing device, this paper attempts to eliminate blind spots with tiny hardware cost. Moreover, in order to completely fix blind area with minimum loss of video communication QoS, the WiFi sensing device’s location boundary that satisfies the above objective is modeled and estimated. To that end, a visitor-disturbed channel model is first derived for precisely describing the inherent relation between the appearance of visitor and the change of wireless channel. Then a location boundary model satisfying both blind-area elimination and QoS maximization is further derived. Based on the derived model, a practical system is designed to estimate the real location boundary. The simulation and experiment results have not only verified the correctness of our derived location boundary model, but also showed its good performance on both blind-area elimination and communication QoS optimization.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130406551","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}

{"title":"NQ/ATP: Architectural Support for Massive Aggregate Queries in Data Center Networks","authors":"Yixi Chen, Wenfei Wu, Shan-Hsiang Shen, Ying Zhang","doi":"10.1109/IWQoS54832.2022.9812906","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812906","url":null,"abstract":"Network queries become increasingly challenging for online service providers with massive network devices and massive network queries due to the tradeoff between system scale and query granularity. We re-architect the traditional three-tier architecture, i.e., data collection, data storage, and data query, for aggregate queries, and build a system named NQ/ATP. NQ/ATP offloads the aggregation operation in network queries onto network switches, which accelerates the query execution and frees up network resources. NQ/ATP further devises a route learning mechanism, query hierarchy load balancing policy, and hierarchy clustering mechanism to save forwarding table entries on switches, which better supports massive queries. The evaluation shows that NQ/ATP can support network aggregate queries with higher capacity, less traffic volume, finer granularity, and better scalability than traditional three-tier polling architectures. The three optimizations can effectively reduce the forwarding table usage by up to 97.55%.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131888368","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}

{"title":"FedSyL: Computation-Efficient Federated Synergy Learning on Heterogeneous IoT Devices","authors":"Hui Jiang, Min Liu, Sheng Sun, Yuwei Wang, Xiaobing Guo","doi":"10.1109/IWQoS54832.2022.9812907","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812907","url":null,"abstract":"As a popular privacy-preserving model training technique, Federated Learning (FL) enables multiple end-devices to collaboratively train Deep Neural Network (DNN) models without exposing local privately-owned data. According to the FL paradigm, resource-constrained end-devices in IoT should perform model training which is computation-intensive, whereas the edge server occupied with powerful computation capability only performs model aggregation. Due to the above unbalanced computation pattern, IoT-oriented FL is time-consuming and inefficient. In order to alleviate the computation burden of end-devices, recent countermeasures introduce the edge server to assist end-devices in model training. However, existing works neither efficiently address the computation heterogeneity across end-devices nor reduce the leakage risk of data privacy. To this end, we propose a Federated Synergy Learning (FedSyL) paradigm which innovatively strikes a balance between training efficiency and data leakage risk. We explore the complicated relationship between the local training latency and multi-dimensional training configurations, and design a uniform training latency prediction method by applying the polynomial quadratic regression analysis. Additionally, we design the optimal model offloading strategy with the consideration of resource limitation and computation heterogeneity of end-devices, so as to accurately assign capability=matched device-side sub-models for heterogeneous end-devices. We implement FedSyL on a real test-bed comprising multiple heterogeneous end-devices. Experimental results demonstrate the superiority of FedSyL on training efficiency and privacy protection.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130074947","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}

{"title":"DoCile: Taming Denial-of-Capability Attacks in Inter-Domain Communications","authors":"Marc Wyss, Giacomo Giuliari, M. Legner, A. Perrig","doi":"10.1109/IWQoS54832.2022.9812889","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812889","url":null,"abstract":"In recent years, much progress has been made in the field of Internet bandwidth reservation systems. While early designs were neither secure nor scalable, newer proposals promise attack resilience and Internet-wide scalability by using cryptographic access tokens (capabilities) that represent permissions to send at a guaranteed rate. Once a capability-based bandwidth reservation is established, the corresponding traffic is protected from both naturally occurring congestion and distributed denialof-service attacks, with positive consequences on the end-to-end quality of service (QoS) of the communication. However, high network utilization—possibly caused by adversaries—can still preclude the initial unprotected establishment of capabilities. To prevent such denial-of-capability (DoC) attacks, we present DoCile, a framework for the protection of capability establishment on Internet paths, irrespective of network utilization. We believe that DoCile, deployed alongside a capability-based bandwidth reservation system, can be the foundation of the next generation of secure and scalable QoS protocols.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121787303","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}

{"title":"iSwift: Fast and Accurate Impact Identification for Large-scale CDNs","authors":"Jiyan Sun, Tao Lin, Yinlong Liu, X. Wang, Bo Jiang, Liru Geng, Pengkun Jing, Liang Dai","doi":"10.1109/IWQoS54832.2022.9812890","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812890","url":null,"abstract":"One key challenge to maintain a large-scale Content Delivery Network (CDN) is to minimize the service downtime when severe system problems happen (e.g., hardware failures). In this case, a critical step is to quickly and accurately identify the range of users with performance degradation, termed impact identification. Successful impact identification not only helps identify impacted users but also provides meaningful information for troubleshooting. However, current practice of impact identification usually takes network engineers several hours to manually identify impacted users, which may lead to a huge business loss. The main challenges for automatic impact identification in large CDNs include the inaccuracy of underlying anomaly detection, huge search space of impact identification and severe long-tail distribution of user traffic. In this paper we propose iSwift, a system that is specifically designed for impact identification in large-scale CDNs in order to address aforementioned challenges. We evaluate the performance of iSwift on semi-synthetic datasets and the results show that iSwift can achieve a F1-score greater than 0.85 within ten seconds, which significantly outperforms state-of-the-art solutions. Furthermore, iSwift has been deployed in a production CDN around one year as a pilot project and demonstrated its online performance confirmed by the network operators.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126870659","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}

{"title":"WiVi: WiFi-Video Cross-Modal Fusion based Multi-Path Gait Recognition System","authors":"Jinmeng Fan, Hao Zhou, Fengyu Zhou, Xiaoyan Wang, Zhi Liu, Xiang Li","doi":"10.1109/IWQoS54832.2022.9812893","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812893","url":null,"abstract":"WiFi-based gait recognition is an attractive method for device-free user identification, but path-sensitive Channel State Information (CSI) hinders its application in multi-path environments, which exacerbates sampling and deployment costs (i.e., large number of samples and multiple specially placed devices). On the other hand, although video-based ideal CSI generation is promising for dramatically reducing samples, the missing environment-related information in the ideal CSI makes it unsuitable for general indoor scenarios with multiple walking paths.In this paper, we propose WiVi, a WiFi-video cross-modal fusion based multi-path gait recognition system which needs fewer samples and fewer devices simultaneously. When the subject walks naturally in the room, we determine whether he/she is walking on the predefined judgment paths with a K-Nearest Neighbors (KNN) classifier working on the WiFi-based human localization results. For each judgment path, we generate the ideal CSI through video-based simulation to decrease the number of needed samples, and adopt two separated neural networks (NNs) to fulfill environment-aware comparison among the ideal and measured CSIs. The first network is supervised by measured CSI samples, and learns to obtain the semi-ideal CSI features which contain the room-specific ‘accent’, i.e., the long-term environment influence normally caused by room layout. The second network is trained for similarity evaluation between the semi-ideal and measured features, with the existence of short-term environment influence such as channel variation or noises.We implement the prototype system and conduct extensive experiments to evaluate the performance. Experimental results show that WiVi’s recognition accuracy ranges from 85.4% for a 6-person group to 98.0% for a 3-person group. As compared with single-path gait recognition systems, we achieve average 113.8% performance improvement. As compared with the other multi-path gait recognition systems, we achieve similar or even better performance with needed samples being reduced by 57.1-93.7%","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115399275","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}

{"title":"Progressive Construction of k-identifiable Networks","authors":"Yongshuo Wan, Cuiying Feng, Kui Wu, Jianping Wang","doi":"10.1109/IWQoS54832.2022.9812924","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812924","url":null,"abstract":"Since the inception of networking technology, network topology design has been a fundamental step for any interconnected system. This classical problem has diverse forms due to various design criteria. One special criterion, the ease of monitoring the network (termed as monitorability of the network), has recently attracted much attention in the era of Industry 4.0 when many complex private networks need to be built for new industrial services. This paper extends a quantitative measure of network monitorability, k-identifiability, based on which a new form of network topology design problem is formulated. We prove that this network design problem is intractable. To solve it, we systematically analyze the topological features that are helpful for reducing the complexity of network construction. Based on the analysis, we propose a dual-heuristic method that runs two heuristics in parallel and selects the better topology as the preliminary design result. Moreover, we design an integrated algorithm that reduces unnecessary edges as the final design result. We compare our dual-heuristic algorithm with the theoretical optimal solution in small-scale networks where the brute-force search is feasible. The results demonstrate the near-optimality of our method. We also illustrate the capability of our method in designing large-scale networks.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123181398","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}

{"title":"PextCuts: A High-performance Packet Classification Algorithm with Pext CPU Instruction","authors":"Chunyang Zhang, Gaogang Xie, Peng He","doi":"10.1109/IWQoS54832.2022.9812873","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812873","url":null,"abstract":"Packet classification is the most essential component for switches and firewalls to perform network functions. In Software Defined Network, the growing scale of traffic requires the packet classification algorithm to perform high-speed lookup. Even though a lot of algorithms are proposed, the lookup performance is still the bottleneck because of the inefficient and unscientific schemes to cut rules and split trees. In this paper, we propose a novel decision-tree-based algorithm PextCuts. First, to efficiently cut rules, PextCuts applies one pext CPU instruction to select discontiguous bits rather than contiguous bits. Second, to scientifically split trees, PextCuts applies the dynamic programming method to split each field into multiple sizes rather than large and small sizes. Compared to ten representative algorithms, PextCuts has the highest lookup speed with the minimal numbers of average memory accesses, maximal memory accesses, and tree height simultaneously. It also consumes the least memory cost and the shortest construction time. For the state-of-the-art algorithm ByteCuts, PextCuts achieves 2.1x lookup speed with only 57% memory cost and 10% construction time. In addition, we implement PextCuts in DPDK to perform packet classification with optional fields and achieve 3.0x lookup speed.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"560 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123518549","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}

{"title":"Accurately Identify Time-decaying Heavy Hitters by Decay-aware Cuckoo Filter along Kicking Path","authors":"Qingjun Xiao, Haotian Wang, Guannan Pan","doi":"10.1109/IWQoS54832.2022.9812870","DOIUrl":"https://doi.org/10.1109/IWQoS54832.2022.9812870","url":null,"abstract":"In high-speed networks, flow-level traffic measurement is an essential tool to understand how network bandwidth is being utilized. It can be used to detect anomalous traffic behaviors due to operational or security issues. Perhaps the most important measurement task is to track the heavy hitters (HHs), i.e., the flows occupying the greatest shares of bandwidth. But most existing solutions have no concept of time window: Whenever a measurement period ends, the data sketch, which is deployed in the data plane for monitoring HHs, must be transferred to the control plane and then reset to zeros. It is better to capture network conditions of the continuous recent past by designing a HHs measurement solution that can support time-decaying window. As a result, recently several related works are devoted to tracking the time-decaying heavy hitters, including time-decaying CountMin and time-decaying Space-Saving. However, their memory-accuracy tradeoff is still suboptimal. In this paper, we attain higher performance by proposing a new algorithm named DecayAware Cuckoo Filter along Kicking Path (DAKP-CF). It can be regarded as a variant of cuckoo filter (an improved version of hash table with better memory efficiency), which transforms each bucket into a bucket-level min-heap. Its key advantage is that, when we update the table as a packet arrive, it can discover and replace the most time-decayed flow along the kicking path of a cuckoo filter. We deliberately avoid scanning the entire table to keep the high time efficiency. The experiment results show that our DAKP-CF can reach the same identification accuracy as existing methods with roughly 25% memory cost. In addition, we build a prototype of our DAKP-CF by P4-programmable BMv2 software switch.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122735054","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}