2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)最新文献_第4页

A new electromagnetic jamming system for unmanned aerial vehicles 一种新型无人机电磁干扰系统

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121921

Huaifeng Zhang, Hao Zhang, Xing Liu, T. Gulliver

引用次数: 5

A trace-driven analytical model with less profiling overhead for DRAM access latencies 跟踪驱动的分析模型，具有较少的DRAM访问延迟分析开销

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121883

Fengying Sun, Kecheng Ji, Ming Ling, Longxing Shi

{"title":"A trace-driven analytical model with less profiling overhead for DRAM access latencies","authors":"Fengying Sun, Kecheng Ji, Ming Ling, Longxing Shi","doi":"10.1109/PACRIM.2017.8121883","DOIUrl":"https://doi.org/10.1109/PACRIM.2017.8121883","url":null,"abstract":"Due to the painful time consuming of cycle-accurate simulations, analytical modeling of DRAM systems has been becoming an effective alternative to give guidance for architecture optimizations. Some analytical models forecast the DRAM performance by obtaining the proportions of different DRAM command appearances from memory trace profiling. However, existing works require too many cases composed by different DRAM commands which need lots of profiling and consume much of time. On the flip side, other methods assume that the arrival process of memory requests to the DRAM satisfies the Poisson distribution and estimate the DRAM performance based on the queueing theory. The assumption, however, will be shown not accurate by our experiments in this paper. Not surprisingly, the performance forecasting based on these models is not accurate, not to mention the cases that some researchers assume the DDR access latency as an empirical constant value. Hence, in this paper, we propose a trace-driven analytical model to quickly and precisely estimate the DDR access latency. Compared to prior studies, our model requires much less time overhead without sacrificing the forecasting precision. 17 benchmarks are adopted for the accuracy evaluation of our model. Compared with the simulation results using Gem5 and DRAMSim2, the average accuracy of our model is higher than 93.31%, while the forecasting process can be sped up by x22 times contrast to cycle-accurate simulations.","PeriodicalId":308087,"journal":{"name":"2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129969141","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

Remote control of low cost devices using SNMP agents 使用SNMP代理远程控制低成本设备

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121927

Willian Tadeu Poloni, R. Becker, R. Balbinot

引用次数: 2

Robot control and decision making through real-time sensors monitoring and analysis for industry 4.0 implementation on aerospace component manufacturing 通过实时传感器监测和分析实现机器人控制和决策，以实现工业4.0在航空航天部件制造中的应用

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121928

Tomi Wijaya, W. Caesarendra, Bobby K. Pappachan, T. Tjahjowidodo, A. Wee, M. I. Roslan

{"title":"Robot control and decision making through real-time sensors monitoring and analysis for industry 4.0 implementation on aerospace component manufacturing","authors":"Tomi Wijaya, W. Caesarendra, Bobby K. Pappachan, T. Tjahjowidodo, A. Wee, M. I. Roslan","doi":"10.1109/PACRIM.2017.8121928","DOIUrl":"https://doi.org/10.1109/PACRIM.2017.8121928","url":null,"abstract":"The industrial revolution has reached a new development cycle which uses the advantages of cyber world into the physical world of manufacturing, and called Industry 4.0. Cyber world offers Internet of Things which allows transmission and reception of data from and to anywhere on earth through Internet. In the current aerospace industry, the production of components has significant manual work involved. Meanwhile, the demand in quantity and quality of these components are increasing. In order to enhance manufacturing capability and solve this, this paper introduced a universal platform for real time sensors monitoring and analysis for Industry 4.0 implementation in aerospace industry. Our objective was to develop a universal platform that is reliable to be used in various analytical applications and investigate the supporting factors that has to be considered in applying such platform. To achieve this objective, the paper used easily available hardware which consists of ABB Robot, Wi-Fi Data Acquisition Systems (Wi-Fi DAQs), FPGA equipped CompactRIO, Wireless Access Point (WAP), sensors, and monitor. The system mentioned is made to trial for aerospace component manufacturing processes. The data acquired from the sensors is collected and transmitted by the Wi-Fi DAQs to the WAP. Consequently, the CompactRIO will collect the sensors data from the WAP and analyze them. The result will then be sent to the internet and also used to trigger necessary action for the ABB Robot based on predetermined decision making tables or resources. Ultimately, this application enables aerospace component manufacturers to enhance their capability to increase the product quality and manufacturing process safety while also reduce the manufacturing time required.","PeriodicalId":308087,"journal":{"name":"2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131317616","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: 5

Deep learning for hydrophone big data 水听器大数据的深度学习

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121894

C. McQuay, F. Sattar, P. Driessen

引用次数: 7

An improved cooperative jamming strategy for PHY security in a multi-hop communications system 一种改进的多跳通信系统物理层安全协同干扰策略

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121886

Conghui Cao, Hao Zhang, Tingting Lv, T. Gulliver

引用次数: 1

Assessing QoS consistency in cloud-based software-as-a-service deployments 评估基于云的软件即服务部署中的QoS一致性

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121889

Robert O'Dywer, S. Neville

{"title":"Assessing QoS consistency in cloud-based software-as-a-service deployments","authors":"Robert O'Dywer, S. Neville","doi":"10.1109/PACRIM.2017.8121889","DOIUrl":"https://doi.org/10.1109/PACRIM.2017.8121889","url":null,"abstract":"Cloud-deployed Software-as-a-Service (SaaS) solutions have become a common global software deployment regime. For SaaS providers success is increasingly tied to social media feedback, customer reviews, and referrals. As such, ensuring sufficiently few users experience low (or poor) quality of service (QoS) levels has become an important concern. Cloud-based SaaS QoS is primarily driven by: i) the incoming workload's pace and complexity, ii) the SaaS system's design and implementation, and iii) the cloud platform's own induced QoS variabilities. Of these, SaaS software engineers generally have the least control over (iii), making it important to properly understand and quantify. This work empirically assesses (iii) by applying statistically rigorous QoS testing to an industry-held cloud-deployed SaaS system. Identical SaaS system instances are instantiated into the same commercial cloud platform and exercised via identical synthetic in-coming workloads. The resulting run-time QoS statistical distributions of each SaaS instance are then pairwise compared via distribution-free goodness-of-fit tests. A high degree of (iii) induced statistical dissimilarity is observed, suggesting significant care is required when seeking to make QoS envelope predictions from per-instance observed SaaS QoS results. This also suggests deeper more formal efforts may be required to better understand and characterize the cloud-induced SaaS QoS consistency issues that arise within modern SaaS deployments.","PeriodicalId":308087,"journal":{"name":"2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114584563","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

Multipath TCP path schedulers for streaming video 流视频的多路径TCP路径调度器

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121920

Ryota Matsufuji, D. Cavendish, K. Kumazoe, Daiki Nobayashi, T. Ikenaga

引用次数: 6

Improving the performance of JVM startup using the shared class cache 使用共享类缓存提高JVM启动的性能

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121911

Dev Bhattacharya, K. Kent, E. Aubanel, Daniel Heidinga, Peter Shipton, Aleksandar Micic

引用次数: 6

An improved incremental/decremental delaunay mesh-generation strategy for image representation 一种改进的图像表示的增量/递减延迟网格生成策略

2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2017-08-01 DOI: 10.1109/PACRIM.2017.8121887

Badr Eddine El Marzouki, M. Adams

引用次数: 0