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Bhaskar Krishnamachari, Subhash Suri, Wendi Heinzelman, Urbashi Mitra - Distributed Computing in Sensor Systems: 5th IEEE International Conference, DCOSS 2009
Publisher: Springer | 2009-06-30 | ISBN: 3642020844 | File type: PDF | 372 pages | 12.38 mb
The book constitutes the refereed proceedings of the Fifth International Conference on Distributed Computing in Sensor Systems, DCOSS 2009, held in Marina del Rey, CA, USA, in June 2009.
The 26 revised full papers presented were carefully reviewed and selected from 116 submissions. The research contributions in this proceedings span many aspects of sensor systems, including energy efficient mechanisms, tracking and surveillance, activity recognition, simulation, query optimization, network coding, localization, application development, data and code dissemination.
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Distributed Computing in Sensor Systems: 5th IEEE International Conference, DCOSS 2009, Marina del Rey, CA, USA, June 8-10, 2009, Proceedings (Lecture. Networks and Telecommunications)
The book constitutes the refereed proceedings of the Fifth International Conference on Distributed Computing in Sensor Systems, DCOSS 2009, held in Marina del Rey, CA, USA, in June 2009. The 26 revised full papers presented were carefully reviewed and selected from 116 submissions. The research contributions in this proceedings span many aspects of sensor systems, including energy efficient mechanisms, tracking and surveillance, activity recognition, simulation, query optimization, network coding, localization, application development, data and code dissemination.
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Free ebooks since 2009
The book constitutes the refereed proceedings of the First International Conference on Distributed Computing in Sensor Systems, DCOSS 2005, held in Marina del Rey, California, USA in June/July 2005. The 26 revised full papers presented were carefully reviewed and selected from 85 submissions; also included are the abstracts of 3 invited talks, 2 short papers, 9 invited poster abstracts, and 10 contributed abstracts.The papers address all current aspects of distributed computing issues in large-scale networked sensor systems, including systematic design techniques and tools, algorithms, and applications.Volume editor Viktor K. Prasanna
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Chehri, A. Fortier, P. Tardif, P.M. Application of Ad-hoc sensor networks for localization in underground mines. In: Proc. Wireless and Microwave Technology Conference 2006 (WAMICON 2006), Florida, USA (December 2006)
Irmak, S. et al. Watermark Granular Matrix Sensor to Measure Soil Matric Potential for Irrigation Management. In: UNL Extension Circular ECL783 (2006)
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Li, L. Vuran, M.C. Akyildiz, I.F. Characteristics of Underground Channel for Wireless Underground Sensor Networks. In: Proc. Med-Hoc-Net 2007, Corfu, Greece (June 2007)
Mastarone, J.F. Chappell, W.J. Urban sensor networking using thick slots in manhole covers. In: Proc. Antennas and Propagation Society International Symposium 2006, New Mexico, USA (July 2006)
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Stuntebeck, E. Pompili, D. Melodia, T. Underground Wireless Sensor Networks Using Commodity Terrestrial Motes. In: IEEE SECON 2006, Reston, USA (September 2006) (poster presentation)
Sun, Z. Akyildiz, I.F. Channel Modeling of Wireless Networks in Tunnels. In: Proc. IEEE Globecom 2008, New Orleans, USA (November 2008)
Tiusanen, J. Wireless Soil Scout prototype radio signal reception compared to the attenuation model. Precision Agriculture (November 2008), doi:10.1007/s11119-008-9096-7
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Project Group, Institute Of Chemistry And Dynamics Of The Geosphere (ICG), Agrosphere Institute, ICG 4, SoilNet - A Zigbee based soil moisture sensor network, http://www.fz-juelich.de/icg/icg-4/index.php?index=739
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June 8 - 10, 2009
Marina Del Rey, California
The 5th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS '09) will take place on Marina Del Rey, California, USA during Monday, June 8 - Wednesday, June 10, 2009.
DCOSS 2005 (Marina del Rey, California), DCOSS 2006 (San Francisco, California), DCOSS 2007 (Santa Fe, New Mexico), and DCOSS 2008 (Santorini Island, Greece) featured high quality research papers and interesting invited and contributed posters. DCOSS '09 is intended to cover several aspects of distributed computing in sensor systems such as high level abstractions and models, systematic design methodologies, signal and information processing, algorithms, analysis and applications.
The conference will be co-located with several closely related workshops. and will provide a forum for researchers and practitioners to present their contributions related to the above high-level aspects of distributed sensor systems. In addition to contributed papers, the meeting will also include keynote addresses by leading researchers, a panel discussion, and a poster session .KEYNOTE SPEAKERS
IMPORTANT DATES Submission Deadline: 11:59PM EST Feb. 2, 2009[extended] Notification: March 24, 2009 Camera Ready: March 31, 2009
IEEE Computer Society Technical Committee on Parallel Processing (TCPP)
IEEE Computer Society Technical Committee on Distributed Processing (TCDP)
Held in co-operation with
ACM SIGARCH, ACM SIGBED, European Association for Theoretical Computer Science (EATCS), IFIP WG 10.3
Wireless systems are deployed in environments like buildings, bridges and forests - each of which has very different wireless properties. In this paper, we propose a technique to customize simulation for a new RF environment, before a physical layer model has been created for it. Our approach is to create physical layer traces or PhyTraces that capture the RF environment of a single node. These PhyTraces can then be composed in multiple ways to simulate protocol-layer performance in the target environment. This approach offers an alternative to conventional trace-based network simulation that is very realistic, but does not permit protocol-level changes after the traces are collected. We show that PhyTraces can be collected very quickly and can be used in simulation with low computational overhead to model networks of various sizes and densities. To evaluate this approach, we collect PhyTraces in 3 different physical environments using 2 different low-power radios at 4 different transmission power levels. Our analysis indicates that the PhyTraces can predict the performance of neighbor discovery algorithms, distance vector routing algorithms, and flooding algorithms in real deployments, including some effects of complex dynamics due to packet loss and wireless collisions.
RF Characaterization, Wireless Simulation, Physical Layer Traces,
Jiakang Lu, Kamin Whitehouse, "PhyTraces: Simulating New RF Environments with Physical Layer Traces", 2014 IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS). vol. 00, no. pp. 10-17, 2014, doi:10.1109/DCOSS.2014.37
Publication Year: 2014, Page(s): 1
Sensors of diverse capabilities and modalities, carried by us or deeply embedded in the physical world, have invaded our personal, social, work, and urban spaces. Our relationship with these sensors is a complicated one. On the one hand, these sensors collect rich data that are shared and disseminated, often initiated by us, with a broad array of service providers, interest groups, friends, and fa. View full abstract»
Publication Year: 2014, Page(s):2 - 9
Cited by: Papers (3)
Exploiting multiple radio channels for communication has been long known as a practical way to mitigate interference in wireless settings. In Wireless Sensor Networks, however, multi-channel solutions have not reached their full potential: the MAC layers included in TinyOS or the Contiki OS for example are mostly single-channel. The literature offers a number of interesting solutions, but experime. View full abstract»
Publication Year: 2014, Page(s):10 - 17
Wireless systems are deployed in environments like buildings, bridges and forests - each of which has very different wireless properties. In this paper, we propose a technique to customize simulation for a new RF environment, before a physical layer model has been created for it. Our approach is to create physical layer traces or PhyTraces that capture the RF environment of a single node. These Ph. View full abstract»
Publication Year: 2014, Page(s):18 - 25
Cited by: Papers (3)
Emerging low-power radio triggering techniques for wireless motes are a promising approach to prolong the lifetime of Wireless Sensor Networks (WSNs). By allowing nodes to activate their main transceiver only when data need to be transmitted or received, wake-up-enabled solutions virtually eliminate the need for idle listening, thus drastically reducing the energy toll of communication. In this pa. View full abstract»
Publication Year: 2014, Page(s):26 - 34
Topology Control Protocols configure transmission power of nodes in order to achieve specific properties to a given topology. These properties include the creation and maintenance of neighborhoods or other topological entities (like trees or clusters), load balancing in terms of connectivity degrees and provision of link symmetry. We see topology control as a two-fold problem where topological pro. View full abstract»
Publication Year: 2014, Page(s):35 - 42
This article describes a method for indoor positioning of human-carried active Radio Frequency Identification (RFID) tags based on the Sampling Importance Resampling (SIR) particle filtering algorithm. To use particle filtering methods, it is necessary to furnish statistical state transition and observation distributions. The state transition distribution is obstacle-aware and sampled from a preco. View full abstract»
Publication Year: 2014, Page(s):43 - 50
Cited by: Papers (1)
Sequence-based localization (SBL) is a technique whereby a node is localized based on the ranked sequence of signal strengths obtained from a set of beacon nodes. SBL effectively partitions the area into regions corresponding to unique ranked sequences. Prior work has developed SBL under the assumption that all beacons have the same transmit power. In this work, we consider beacons with unequal tr. View full abstract»
Publication Year: 2014, Page(s):51 - 58
We revisit the classic object tracking problem with a novel and effective, yet straightforward distributed solution for resource-lean devices. The difficulty of object tracking lies in the mismatch between the limited computational capacity of typical sensor nodes and the processing requirements of typical tracking algorithms. In this paper, we introduce an in-network system for tracking mobile ob. View full abstract»
Publication Year: 2014, Page(s):59 - 66
Low-power compact sensor nodes are being increasingly used to collect trajectory data from moving objects such as wildlife. The size of this data can easily overwhelm the data storage available on these nodes. Moreover, the transmission of this extensive data over the wireless channel may prove to be difficult. The memory and energy constraints of these platforms underscores the need for lightweig. View full abstract»
Publication Year: 2014, Page(s):67 - 74
Cited by: Papers (3)
The paper presents a new model for crowd-sensing applications, where humans are used as the sensing sources to report information regarding the physical world. In contrast to previous work on the topic, we consider a model where the sources in question are polarized. Such might be the case, for example, in political disputes and in situations involving different communities with largely dissimilar. View full abstract»
Publication Year: 2014, Page(s):75 - 82
Cited by: Papers (7)
We present MaWi - a smart phone based scalable indoor localization system. Central to MaWi is a novel framework combining two self-contained but complementary localization techniques: Wi-Fi and Ambient Magnetic Field. Combining the two techniques, MaWi not only achieves a high localization accuracy, but also effectively reduces human labor in building fingerprint databases: to avoid war-driving, M. View full abstract»
Publication Year: 2014, Page(s):83 - 91
Cited by: Papers (2)
Recently proposed applications for monitoring the behavior of real-world crowds with wireless sensor nodes rely on decentralized in-network aggregation. Although some of the aggregation algorithms for wireless sensor networks seem appealing for such applications, we are not aware of any deployments of these algorithms in real-world scenarios with crowd mobility. As a step toward filling this gap. View full abstract»
Publication Year: 2014, Page(s):92 - 100
Cited by: Papers (4)
This paper describes the exploitation of hierarchical data names to achieve information-utility maximizing data collection in social sensing applications. We describe a novel transport abstraction, called the information funnel. It encapsulates a data collection protocol for social sensing that maximizes a measure of delivered information utility, that is the minimized data redundancy, by diversif. View full abstract»
Publication Year: 2014, Page(s):101 - 110
The first wave of sensor network deployments from the early 2000s relied on aggregation-a strategy in which readings are combined locally using low-power radio links before they are communicated to the gateway. Aggregation reduced dependence on battery-draining, long-distance radio links, and reduced redundancy among reported data. We are now experiencing a second wave of sensor network research d. View full abstract»
Publication Year: 2014, Page(s):111 - 118
Cited by: Papers (1)
In this article, we rigorously compare compressive sampling (CS) to four state of the art, on-mote, lossy compression algorithms (K-run-length encoding (KRLE), lightweight temporal compression (LTC), wavelet quantization thresholding and run-length encoding (WQTR), and a low-pass filtered fast Fourier transform (FFT)). Specifically, we first simulate lossy compression on two real-world seismic dat. View full abstract»
Publication Year: 2014, Page(s):119 - 126
Cited by: Papers (3)
This paper complements the large body of social sensing literature by developing means for augmenting sensing data with inference results that "fill-in" missing pieces. Unlike trend-extrapolation methods, we focus on prediction in disaster scenarios where disruptive trend changes occur. A set of prediction heuristics (and a standard trend extrapolation algorithm) are compared that use either predo. View full abstract»
Publication Year: 2014, Page(s):127 - 134
Efficient tag identification is fundamentally required in large-scale RFID systems. Tag signal collision degrades identification efficiency as tag IDs involved in collision cannot be decoded. The situation becomes even worse in large-scale RFID systems when tag cardinality booms. Existing anti-collision protocols focus on either reducing collision probability or adopting spread spectrum techniques. View full abstract»
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