2021 IEEE International Performance, Computing, and Communications Conference (IPCCC)最新文献

Circuit-based PSI for Covid-19 Risk Scoring 基于电路的新型冠状病毒风险评分PSI

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679360

Leonie Reichert, Marcel Pazelt, B. Scheuermann

引用次数: 2

The Diminished Importance of Connection-based Features in Intrusion Detection 基于连接的特征在入侵检测中的重要性降低

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679417

Jessil Fuhr, Isaac Hanna, Feng Wang, Yongning Tang

{"title":"The Diminished Importance of Connection-based Features in Intrusion Detection","authors":"Jessil Fuhr, Isaac Hanna, Feng Wang, Yongning Tang","doi":"10.1109/IPCCC51483.2021.9679417","DOIUrl":"https://doi.org/10.1109/IPCCC51483.2021.9679417","url":null,"abstract":"Today, more and more Machine Learning (ML) and Deep Learning (DL) techniques are adopted to attain efficient feature selection for intrusion detection. Previous efforts have demonstrated that the major challenge of creating efficient ML and DL-based intrusion detection is to determine appropriate features without negatively affecting classification accuracy. This paper explores the impact of connection-based features on performing intrusion detection models, precisely the effect of connection-based features on detecting DDoS attacks in the CICDDoS2019 dataset. We used ML methods where samples trained with Decision Tree (DT) and Random Forest (RF) classifiers with and without connection-based features, understanding the effect on performance, stability, and its diminishing sensitivity with more samples. Our analysis shows that performing connection-based features depends on the available training sample size. Thus, connection-based features significantly impact classification accuracy concerning small training samples, how its importance is diminished along with increased sample size, and their strong effect on imbalanced malicious attacks.","PeriodicalId":125158,"journal":{"name":"2021 IEEE International Performance, Computing, and Communications Conference (IPCCC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125921678","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}

引用次数: 1

An Efficient Shuffle-Light FFT Library 一个高效的Shuffle-Light FFT库

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679431

Salvatore Servodio, Xiaoming Li

{"title":"An Efficient Shuffle-Light FFT Library","authors":"Salvatore Servodio, Xiaoming Li","doi":"10.1109/IPCCC51483.2021.9679431","DOIUrl":"https://doi.org/10.1109/IPCCC51483.2021.9679431","url":null,"abstract":"The Fast Fourier Transform (FFT) is one of the most widely used computation kernels. Its performance is highly sensitive to the efficiency of its memory operations. In particular, when the FFT is applied on large problem sizes, the overall performance becomes almost totally memory bound. In those cases, the impact of the algorithm’s computational operations is demoted to minimal. This is probably why existing efforts on optimizing large size FFTs have been focused on optimizing the memory operation efficiency. The widely adopted approach in that regard is to adapt parameters external to the FFT algorithm, such as data layout, system software memory management, etc., to the needs of FFT’s memory operation pattern.In this paper, we look into the FFT internals for a way to mitigate FFT’s memory \"boundness\". The low efficiency of FFT’s memory operation, to a large degree, is incurred by the many strided data shuffles intrinsic to the algorithm, and made worse by the fact that many of those stride sizes are power-of-two. The strided data shuffling is already one of the hard workload patterns for memory system, and the power-of-two stride sizes make such a memory access pattern even more challenging. This power-of-two strided memory access pattern is the key problem that our paper addresses and represents our main contribution. Our key idea is a complete separation of the logic indexes and the physical indexes of the data internally accessed in FFT. By maintaining an efficient mapping between the logic indexes and the physical indexes through all passes, almost any stride sizes can be used and be further tuned. As the result, FFTs can be correctly carried out without the need for most of those worst power-of-two data shuffles. This greatly improves memory performance and in turn raises the overall performance. We compare our Shuffle-Light FFT (SLFFT) library with FFTW, a very widely used FFT library, and achieve the average speedup on 24.7% on problems sizes from 26 to 226, and the maximal speedup of 39.4%.","PeriodicalId":125158,"journal":{"name":"2021 IEEE International Performance, Computing, and Communications Conference (IPCCC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115836505","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}

引用次数: 0

Private Distributed K-Means Clustering on Interval Data 区间数据的私有分布k均值聚类

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679364

Dingquan Huang, Xin Yao, Senquan An, Shengbing Ren

引用次数: 1

A Scalable Approach to Service Placement in Fog/Cloud Environments 雾/云环境中服务放置的可伸缩方法

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679396

Shehenaz Shaik, Sanjeev Baskiyar

{"title":"A Scalable Approach to Service Placement in Fog/Cloud Environments","authors":"Shehenaz Shaik, Sanjeev Baskiyar","doi":"10.1109/IPCCC51483.2021.9679396","DOIUrl":"https://doi.org/10.1109/IPCCC51483.2021.9679396","url":null,"abstract":"‘Smart Anything’ needs computation to be performed close to the device. This concept is realized by fog computing, which has applications in various domains such as smart city, smart healthcare, autonomous vehicles, etc. The realization of these applications is contingent upon the availability of physical fog nodes in the vicinity which can be leveraged dynamically by fog tenants in a self-service manner to deploy such applications. Considering the dynamic and elastic nature of application deployment requests as well as the mobility of end-users, the infrastructure resource requirements at a given location by a specific application service offering are unpredictable at best. This necessitates the availability of not just individual fog nodes, but a fog computing environment that provides the features offered by a cloud computing environment such as self-service, availability, elasticity, scalability, performance, etc. To this end, we have proposed the logical organization of fog nodes hierarchically, referred to as Hierarchical and Autonomous Fog Architecture (HAFA). Leveraging such logical organization, we have proposed a scalable, low-overhead, and fully distributed approach to select a cost-efficient fog node, considering both computation and communication costs, from the set of prospective fog nodes to host the given application service. The approach does not require the knowledge of the complete system state by any system entity. We have implemented the solution in a simulation environment and compared its performance with several approaches along with a centralized approach.","PeriodicalId":125158,"journal":{"name":"2021 IEEE International Performance, Computing, and Communications Conference (IPCCC)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115463894","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}

引用次数: 1

ELSV: An Effective Anomaly Detection System from Web Access Logs ELSV:一个有效的Web访问日志异常检测系统

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679413

Wei Wan, Xin Shi, Jinxia Wei, Jing Zhao, Chun Long

引用次数: 1

A Millimeter-wave Multi-channel MAC with Dynamic Spectrum Access Capability for Mobile Self-organizing Heterogeneous Networks 移动自组织异构网络中具有动态频谱接入能力的毫米波多通道MAC

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679371

Peng Feng, Yuebin Bai, Zerui Guo, Xiaolin Wang, Yining Zhang, Bojian Bai, Junmin Zhang

{"title":"A Millimeter-wave Multi-channel MAC with Dynamic Spectrum Access Capability for Mobile Self-organizing Heterogeneous Networks","authors":"Peng Feng, Yuebin Bai, Zerui Guo, Xiaolin Wang, Yining Zhang, Bojian Bai, Junmin Zhang","doi":"10.1109/IPCCC51483.2021.9679371","DOIUrl":"https://doi.org/10.1109/IPCCC51483.2021.9679371","url":null,"abstract":"With the rapid development of wireless network technology and the demand for interconnection of mobile edge computing, the integration of heterogeneous wireless networks is becoming more and more urgent. At the same time, the increasing scarcity of spectrum resources also requires heterogeneous net-works to effectively improve the utilization of spectrum resources without affecting the use of different licensed spectrum resources. This paper proposed a multi-channel millimeter-wave (mmWave) MAC protocol for mobile self-organizing heterogeneous networks. The mmWave Mac uses a bulk access transmission scheme to improve throughput efficiency and reduce latency for heterogeneous networks. In addition, cognitive radio technology is also introduced into the mmWave Mac to enhance the utilization of spectrum resources. Finally, by comparing the simulation results with other protocol, it is verified that the mmWave MAC protocol has good performance in terms of delay, and throughput efficiency.","PeriodicalId":125158,"journal":{"name":"2021 IEEE International Performance, Computing, and Communications Conference (IPCCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130147485","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}

引用次数: 0

PUFF: A Passive and Universal Learning-based Framework for Intra-domain Failure Detection PUFF:一个被动的通用的基于学习的域内故障检测框架

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679436

Lianjin Ye, Qing Li, Xudong Zuo, Jingyu Xiao, Yong Jiang, Zhuyun Qi, Chunsheng Zhu

{"title":"PUFF: A Passive and Universal Learning-based Framework for Intra-domain Failure Detection","authors":"Lianjin Ye, Qing Li, Xudong Zuo, Jingyu Xiao, Yong Jiang, Zhuyun Qi, Chunsheng Zhu","doi":"10.1109/IPCCC51483.2021.9679436","DOIUrl":"https://doi.org/10.1109/IPCCC51483.2021.9679436","url":null,"abstract":"The increasing amount of network devices brings significant improvement to network quality but is inevitably prone to various failures. The frequent occurrence of link failures and node failures in the real-world network, causing packet losses and delay, calls for more accurate and fast detection methods. Existing network failure detection systems focus on probes and end-to-end metrics, but are limited by overhead on bandwidth or storage. Reliance on specific deployment of monitoring systems on devices like hosts also limits the feasibility and compatibility in general network topology, ignoring the potential of transferring monitoring tasks from hosts to switches. In this paper, we propose PUFF, a passive and data-driven network failure detection system based on in-network feature collection in programmable switches and machine learning algorithms. First, PUFF explores the potential use of continuous traffic changes to detect node and link failures instead of end-to-end metrics. Second, PUFF offers a software-based prototype and compares its performance with the latest passive failure detection methods. Evaluation based on simulation on real-world topology shows that PUFF can detect nearly 90% node failures and 80% link failures with less overhead in a shorter time.","PeriodicalId":125158,"journal":{"name":"2021 IEEE International Performance, Computing, and Communications Conference (IPCCC)","volume":"302 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126807955","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}

引用次数: 1

CODS: Cloud-assisted Object Detection for Streaming Videos on Edge Devices CODS:边缘设备上流媒体视频的云辅助对象检测

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679395

Tengpeng Li, Xiaoqian Zhang, Son Nam Nguyen, B. Sheng

引用次数: 0

A Simulation Study of Hardware Parameters for Future GPU-based HPC Platforms 未来基于gpu的高性能计算平台硬件参数仿真研究

2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) Pub Date : 2021-10-29 DOI: 10.1109/IPCCC51483.2021.9679359

Saptarshi Bhowmik, Nikhil Jain, Xin Yuan, A. Bhatele

引用次数: 0