2013 International Conference on Parallel and Distributed Systems最新文献_第8页

Challenges of Using Edge Devices in IoT Computation Grids 在物联网计算网格中使用边缘设备的挑战

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.101

Swarnava Dey, A. Mukherjee, H. Paul, A. Pal

{"title":"Challenges of Using Edge Devices in IoT Computation Grids","authors":"Swarnava Dey, A. Mukherjee, H. Paul, A. Pal","doi":"10.1109/ICPADS.2013.101","DOIUrl":"https://doi.org/10.1109/ICPADS.2013.101","url":null,"abstract":"Internet of Things (IoT) has the potential to become a technology revolution with a vision of creating very large scale network, comprising of unprecedented number of connected devices. These devices, often referred to as smart items or intelligent things can be home appliances, healthcare devices, vehicles, buildings, factories and almost anything networked and fitted with sensors, actuators, embedded computers. There has been sustained research work and standardization effort from different IoT perspectives like integration of sensor and RFID devices to the Internet. With the increasing trend of gathering business insights from unstructured data, the high volume of data generated by such devices is also of interest. Cloud based data mining platforms are suitable for analyses of such data and researchers have proposed architectures where personal mobile phones can act as Edge Gateway between the sensor network and cloud analytics platform. It seems that the surge in the volume of data generated by huge number of Smart Items can only be matched if a large percentage of mobile users start sharing the computation capability of their personal devices and work together towards true Participatory Computing in the IoT systems. In this work we try to understand the challenges associated with running computation jobs on the mobile devices using different types of workload often observed in IoT applications. Based on the insights gained from experiments performed by us, we propose a scheme where mobile phones, residential gateways and other edge devices offer free slots to servers in a cloud based data analytics system. Based on the free time slots offered by the mobile phones, if commensurately sized computational jobs can be scheduled, the unpredictability associated with using mobile phones as grid resources can be solved.","PeriodicalId":160979,"journal":{"name":"2013 International Conference on Parallel and Distributed Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129728570","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: 29

PipeFlow Engine: Pipeline Scheduling with Distributed Workflow Made Simple PipeFlow引擎:管道调度与分布式工作流简单

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.31

Yin Li, Chuang Lin

引用次数: 0

Virtual Coordinate Based Co-moving Detection in Wireless Sensor Networks 基于虚拟坐标的无线传感器网络共移检测

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.106

Wei-Hua Chen, Guey-Yun Chang, Jen-Feng Huang

引用次数: 0

Accelerating De Bruijn Graph-Based Genome Assembly for High-Throughput Short Read Data 加速基于De Bruijn图的高通量短读数据基因组组装

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.68

Kun Zhao, Weiguo Liu, G. Voss, W. Müller-Wittig

引用次数: 1

Edge Detection for Hyperspectral Images Using the Bhattacharyya Distance 基于Bhattacharyya距离的高光谱图像边缘检测

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.127

S. Youn, Chulhee Lee

引用次数: 14

Using GPUs to Crack Android Pattern-Based Passwords 利用gpu破解Android模式密码

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.80

Jaewoo Pi, Pradipta De, Klaus Mueller

引用次数: 0

Wideband Channelization for Software-Defined Radio via Mobile Graphics Processors 基于移动图形处理器的软件无线电宽带信道化

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.24

Vignesh Adhinarayanan, Wu-chun Feng

{"title":"Wideband Channelization for Software-Defined Radio via Mobile Graphics Processors","authors":"Vignesh Adhinarayanan, Wu-chun Feng","doi":"10.1109/ICPADS.2013.24","DOIUrl":"https://doi.org/10.1109/ICPADS.2013.24","url":null,"abstract":"Wideband channelization is a computationally intensive task within software-defined radio (SDR). To support this task, the underlying hardware should provide high performance and allow flexible implementations. Traditional solutions use field-programmable gate arrays (FPGAs) to satisfy these requirements. While FPGAs allow for flexible implementations, realizing a FPGA implementation is a difficult and time-consuming process. On the other hand, multicore processors while more programmable, fail to satisfy performance requirements. Graphics processing units (GPUs) overcome the above limitations. However, traditional GPUs are power-hungry and can consume as much as 350 watts, making them ill-suited for many SDR environments, particularly those that are battery-powered. Here we explore the viability of low-power mobile graphics processors to simultaneously overcome the limitations of performance, flexibility, and power. Via execution profiling and performance analysis, we identify major bottlenecks in mapping the wideband channelization algorithm onto these devices and adopt several optimization techniques to achieve multiplicative speed-up over a multithreaded implementation. Overall, our approach delivers a speedup of up to 43-fold on the discrete AMD Radeon HD 6470M GPU and 27-fold on the integrated AMD Radeon HD 6480G GPU, when compared to a vectorized and multithreaded version running on the AMD A4-3300M CPU.","PeriodicalId":160979,"journal":{"name":"2013 International Conference on Parallel and Distributed Systems","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116171636","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: 7

On Deploying IoT Indoor: An Incremental Approach 在室内部署物联网:一种渐进的方法

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.99

Nguyen Vo Quang Dong, C. King, Cheng Chih Liu

引用次数: 1

Towards a Scalable PaaS for Service Oriented Software 面向服务软件的可伸缩PaaS

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.94

Hailong Sun, Xu Wang, Minzhi Yan, Yu Tang, Xudong Liu

引用次数: 8

Energy Saving Data Abstraction and Reformation Algorithms for Human Movement Monitoring 面向人体运动监测的节能数据提取与改造算法

2013 International Conference on Parallel and Distributed Systems Pub Date : 2013-12-15 DOI: 10.1109/ICPADS.2013.107

Toni, H. Goh, S. Liew

{"title":"Energy Saving Data Abstraction and Reformation Algorithms for Human Movement Monitoring","authors":"Toni, H. Goh, S. Liew","doi":"10.1109/ICPADS.2013.107","DOIUrl":"https://doi.org/10.1109/ICPADS.2013.107","url":null,"abstract":"Detecting human movement is an important issue in monitoring and studying human activities especially for elderly and patients. The availability of wireless sensor network eases the monitoring work. Generally, a wireless sensor node for movement detection is embedded with an accelerometer and powered by batteries. The sensor node needs to transmit the sensed data from accelerometer wirelessly to other nodes or directly to a base station. If there are more data to be transmitted, it consumes more energy and thus the batteries drain out more quickly. Thus, an energy saving scheme, called Data Abstraction and Reformation (DAR), is proposed in this paper to reduce data transmission. Through data abstraction, sensor nodes filter out insignificant sensed data but only report those significant to a base station, and with data reformation, the complete data will be reconstructed at the base station with only the received data. We show that with a good selection of data abstraction and data reformation criteria, a movement detecting sensor node will only need to report 10%~30% of the sensed data in order to provide full human movement monitoring at a base station.","PeriodicalId":160979,"journal":{"name":"2013 International Conference on Parallel and Distributed Systems","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128626958","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