2010 IEEE 16th International Conference on Parallel and Distributed Systems最新文献_第3页

SCAS: Sensing Channel ASsignment for Spectrum Sensing Using Dedicated Wireless Sensor Networks SCAS:使用专用无线传感器网络进行频谱传感的传感信道分配

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.118

Min Gao, Lan Cheng, Yunhuai Liu, L. Ni

{"title":"SCAS: Sensing Channel ASsignment for Spectrum Sensing Using Dedicated Wireless Sensor Networks","authors":"Min Gao, Lan Cheng, Yunhuai Liu, L. Ni","doi":"10.1109/ICPADS.2010.118","DOIUrl":"https://doi.org/10.1109/ICPADS.2010.118","url":null,"abstract":"Spectrum sensing is essential for the success of the cognitive radio networks. In traditional spectrum sensing schemes, Secondary Users (SUs) are responsible for the spectrum sensing which could be very time and resource consuming. It leads to a great deal of inefficiency in spectrum usage and introduces many practical challenges. To tackle these challenges and leverage the spectrum opportunity more efficiently, we propose a new system that provides a spectrum sensing service for SUs using dedicated wireless spectrum sensor networks (WSSNs). In this paper we focus on the sensing channel assignment problem in WSSNs and formulate the problem as a Sensing Effectiveness Maximization Problem (SEMP). We prove that SEMP is NP-complete under the ideal case, and show that the more challenges arises in real environments. To address the issues, we systematically study the design tradeoff and critical factors when maximizing the sensing effectiveness. Based on these study results we propose a Sensing Channel Assignment algorithm (SCAS). We conduct test-bed empirical investigations as well as comprehensive simulations. Performance evaluation results show that for both the scenarios of given deployments and manual deployments, SCAS is able to sense more channels to improve the sensing effectiveness. The improvement is up to 300% and the average improvement is 150% compared with other simple alternatives.","PeriodicalId":365914,"journal":{"name":"2010 IEEE 16th International Conference on Parallel and Distributed Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125777832","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: 3

Efficient Virtual Machine Deployment in Large Scale Resource Environment 大规模资源环境下的高效虚拟机部署

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.72

Feng Huang, Dongsheng Li

引用次数: 0

CANSE: A Churn Adaptive Approach to Network Size Estimation CANSE:一种自适应的网络大小估计方法

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.45

Xingkong Ma, Yi-Jie Wang, Zhong Zheng

引用次数: 1

ILGT: Group Reputation Aggregation Method for Unstructured Peer-to-Peer Networks 非结构化点对点网络的组声誉聚合方法

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.87

A. Matsumoto, Yo Mashimo, Masanori Yasutomi, H. Shigeno

引用次数: 8

Detection of Behavioral Contextual Properties in Asynchronous Pervasive Computing Environments 异步普适计算环境中行为上下文属性的检测

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.24

Yu Huang, Jianping Yu, Jiannong Cao, Xianping Tao

{"title":"Detection of Behavioral Contextual Properties in Asynchronous Pervasive Computing Environments","authors":"Yu Huang, Jianping Yu, Jiannong Cao, Xianping Tao","doi":"10.1109/ICPADS.2010.24","DOIUrl":"https://doi.org/10.1109/ICPADS.2010.24","url":null,"abstract":"Detection of contextual properties is one of the primary approaches to enabling context-awareness. In order to adapt to temporal evolution of the pervasive computing environment, context-aware applications often need to detect behavioral properties specified over the contexts. This problem is challenging mainly due to the intrinsic asynchrony of pervasive computing environments. However, existing schemes implicitly assume the availability of a global clock or synchronous coordination, thus not working in asynchronous environments. We argue that in pervasive computing environments, the concept of time needs to be reexamined. Toward this objective, we propose the Ordering Global Activity (OGA) algorithm, which detects behavioral contextual properties in asynchronous environments. The essence of our approach is to utilize the message causality and its on-the-fly coding as logical vector clocks. The OGA algorithm is implemented and evaluated based on the open-source context-aware middleware MIPA. The evaluation results show the impact of asynchrony on the detection of contextual properties, which justifies the primary motivation of our work. They also show that OGA can achieve accurate detection of contextual properties in dynamic pervasive computing environments.","PeriodicalId":365914,"journal":{"name":"2010 IEEE 16th International Conference on Parallel and Distributed Systems","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116605500","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

A Self-Stabilizing Locality-Aware Peer-to-Peer Network Combining Random Networks, Search Trees, and DHTs 结合随机网络、搜索树和dht的自稳定位置感知点对点网络

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.42

T. Janson, P. Mahlmann, C. Schindelhauer

引用次数: 15

Auto-tuning Dense Matrix Multiplication for GPGPU with Cache 带缓存的GPGPU密集矩阵乘法自动调优

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.64

Xiang Cui, Yifeng Chen, Changyou Zhang, Hong Mei

引用次数: 21

DSpam: Defending Against Spam in Tagging Systems via Users' Reliability 垃圾邮件:通过用户可靠性防御标签系统中的垃圾邮件

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.63

Yonggang Wang, Ennan Zhai, Cui Cao, Yongqiang Xie, Zhao Wang, Jian-bin Hu, Zhong Chen

引用次数: 8

Mixed-Parallel Implementations of Extrapolation Methods with Reduced Synchronization Overhead for Large Shared-Memory Computers 大型共享内存计算机中减少同步开销外推方法的混合并行实现

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.12

Matthias Korch, T. Rauber, C. Scholtes

引用次数: 1

Broadcasting Algorithm Via Shortest Paths 基于最短路径的广播算法

2010 IEEE 16th International Conference on Parallel and Distributed Systems Pub Date : 2010-12-08 DOI: 10.1109/ICPADS.2010.110

Hovhannes A. Harutyunyan, Wei Wang

引用次数: 23