2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems最新文献_第5页

On the Feasibility of Mass-Spring-Relaxation for Simple Self-Deployment 简单自展开质量-弹簧松弛的可行性研究

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.14

Juergen Eckert, H. Lichte, F. Dressler, Hannes Frey

引用次数: 5

A Ubiquitous Publish/Subscribe Platform for Wireless Sensor Networks with Mobile Mules 基于移动骡子的无线传感器网络无处不在的发布/订阅平台

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.65

Xiaoyu Tong, E. Ngai

引用次数: 40

In-Network Iterative Distributed Estimation for Power-Constrained Wireless Sensor Networks 功率受限无线传感器网络的网络内迭代分布式估计

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.18

Santosh Shah, B. Beferull-Lozano

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引用次数: 8

Kinsight: Localizing and Tracking Household Objects Using Depth-Camera Sensors Kinsight:使用深度相机传感器定位和跟踪家庭物体

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.27

S. Nirjon, J. Stankovic

引用次数: 20

Passive Diagnosis for WSNs Using Data Traces 基于数据轨迹的wsn被动诊断

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.63

Jiangwu Nie, Huadong Ma, Lufeng Mo

引用次数: 16

Optimal Relay Placement for Indoor Sensor Networks 室内传感器网络的最佳中继布局

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.62

Cuiyao Xue, Yanmin Zhu, Lei Ni, Minglu Li, B. Li

{"title":"Optimal Relay Placement for Indoor Sensor Networks","authors":"Cuiyao Xue, Yanmin Zhu, Lei Ni, Minglu Li, B. Li","doi":"10.1109/DCOSS.2012.62","DOIUrl":"https://doi.org/10.1109/DCOSS.2012.62","url":null,"abstract":"To many sensor networks, the robust operation depends on deploying relays to ensure wireless coverage. This paper considers the crucial problem of optimal relay placement for wireless sensor networks in indoor environments. The placement of relays is essential for ensuring communication quality and data collection. A number of existing algorithms have been proposed for ensuring full sensing coverage and network connectivity. These algorithms can hardly be applied to indoor environments because of the complexity of indoor environments, in which a radio signal can be dramatically degraded by obstacles like walls. We firstly theoretically prove that the indoor relay placement problem is NP-hard. We then predict radio coverage of a given relay deployment in indoor environments, and then propose a efficient greedy algorithm for computing the relay deployment locations for required coverage quality. This algorithm is proved to provide a Hn factor approximation to the theoretical optimum, where Hn = 1 + 1/2 + ⋯ + 1/n = ln(n) + 1, and n is the number of all grid points. Experimental results demonstrate the proposed algorithm achieves better performance than two other algorithms. To our knowledge, our work is the very first that study the optimal relay placement problem for sensor networks in complex indoor environments.","PeriodicalId":448418,"journal":{"name":"2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132781258","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

Power-Aware Joint Sensor Selection and Routing for Distributed Estimation: A Convex Optimization Approach 分布式估计的功率感知联合传感器选择和路由:一种凸优化方法

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.19

Santosh Shah, B. Beferull-Lozano

{"title":"Power-Aware Joint Sensor Selection and Routing for Distributed Estimation: A Convex Optimization Approach","authors":"Santosh Shah, B. Beferull-Lozano","doi":"10.1109/DCOSS.2012.19","DOIUrl":"https://doi.org/10.1109/DCOSS.2012.19","url":null,"abstract":"This paper considers the problem of power-efficient distributed estimation of vector parameters related to localized phenomena so that both the subset of sensor selection and the routing structure in a wireless sensor network are optimized jointly in order to obtain the best possible estimation performance at a given querying node, for a given total power budget. We first formulate our problem as an optimization problem and show that it is NP-Hard. Then, we design two algorithms: a fixed-tree relaxation-based and a novel and very efficient local distributed optimization to optimize jointly the sensor selection and the routing structure. We also provide a lower bound for our optimization problem and show that our local distributed optimization algorithm provides a performance that is close to this bound. Although there is no guarantee that the gap between this lower bound and the optimal solution of the main problem is always small, our numerical experiments support that this gap is actually very small in many cases. An important result from our work is that because of the interplay between the communication cost over the links and the gains in estimation accuracy obtained by choosing certain sensors, the traditional shortest-path-tree routing structure, widely used in practice, is no longer optimal, that is, our routing structures provide a better trade-off between the overall power efficiency and the final estimation accuracy obtained at the querying node. Comparing to more conventional sensor selection and fixed routing algorithms, our proposed joint sensor selection and routing algorithms yields a significant amount of energy saving.","PeriodicalId":448418,"journal":{"name":"2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128925742","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: 6

Timely Report Delivery in Social Swarming Applications 社会化集群应用中的及时报告交付

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.8

Bin Liu, Peter Terlecky, Xing Xu, A. Bar-Noy, R. Govindan, Dror Rawitz

{"title":"Timely Report Delivery in Social Swarming Applications","authors":"Bin Liu, Peter Terlecky, Xing Xu, A. Bar-Noy, R. Govindan, Dror Rawitz","doi":"10.1109/DCOSS.2012.8","DOIUrl":"https://doi.org/10.1109/DCOSS.2012.8","url":null,"abstract":"In social swarming applications, participants equipped with 3G and WiFi-capable smart phones are tasked to provide reports (possibly voluminous ones that include full-motion video) about their immediate environment to a central coordinator. In this paper, we consider the problem of timely delivery of these reports: each report has an associated deadline and the goal of the system is to retrieve as many reports as possible (or retrieve the most valuable reports), while satisfying each report's deadline. Reporters can use their cellular interface to upload their reports, but can also ask neighbors (using their faster WiFi interface) to help upload parts of their reports. Under an assumption that WiFi transmission delays are negligible, we first show that there exists a polynomial time optimal solution using an earliest-deadline-first (EDF) strategy for achieving the goals described above. In practice, WiFi delays are not negligible: in this case, it turns out that the scheduling problem is strongly NP-hard. We formulate two heuristic algorithms, and show, through simulations with real-world measurements, that these heuristics perform 2-4× better than without peer-assistance, and within 60% of an upper-bound on the optimal.","PeriodicalId":448418,"journal":{"name":"2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems","volume":"2548 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127482215","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: 2

Autonomous Sensors Collaboration for Moving Object Classification 自主传感器协同运动目标分类

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-16 DOI: 10.1109/DCOSS.2012.28

M. Faied

引用次数: 2

A Cross-Layer Design for Decentralized Detection in Tree Sensor Networks 树状传感器网络中分散检测的跨层设计

2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems Pub Date : 2012-05-01 DOI: 10.1109/DCOSS.2012.35

A. Tantawy, X. Koutsoukos, Gautam Biswas

{"title":"A Cross-Layer Design for Decentralized Detection in Tree Sensor Networks","authors":"A. Tantawy, X. Koutsoukos, Gautam Biswas","doi":"10.1109/DCOSS.2012.35","DOIUrl":"https://doi.org/10.1109/DCOSS.2012.35","url":null,"abstract":"The design of wireless sensor networks for detection applications is a challenging task. On one hand, classical work on decentralized detection does not consider practical wireless sensor networks. On the other hand, practical sensor network design approaches that treat the signal processing and communication aspects of the sensor network separately result in sub optimal detection performance because network resources are not allocated efficiently. In this work, we attempt to cross the gap between theoretical decentralized detection work and practical sensor network implementations. We consider a cross-layer approach, where the quality of information, channel state information, and residual energy information are included in the design process of tree-topology sensor networks. The design objective is to specify which sensors should contribute to a given detection task, and to calculate the relevant communication parameters. We compare two design schemes: (1) direct transmission, where raw data are transmitted to the fusion center without compression, and (2) in-network processing, where data is quantized before transmission. For both schemes, we design the optimal transmission control policy that coordinates the communication between sensor nodes and the fusion center. We show the performance improvement for the proposed design schemes over the classical decoupled and maximum throughput design approaches.","PeriodicalId":448418,"journal":{"name":"2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114568927","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