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Timely Report Delivery in Social Swarming Applications

Timely Report Delivery in Social Swarming Applications

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international conference on distributed computing in sensor systems (dcoss)

作者： Bin Liu Peter Terlecky Xing Xu Amotz Bar-Noy Ramesh Govindan Dror Rawitz University of Southern California Los Angeles USA City University of New York USA Tel Aviv University Israel

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.

关键词： Delay ieee 802.11 Standards Schedules Bandwidth Smart phones Heuristic algorithms Polynomials

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In-Network Iterative distributed Estimation for Power-Constrained Wireless sensor Networks

In-Network Iterative Distributed Estimation for Power-Constr...

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international conference on distributed computing in sensor systems (dcoss)

作者： Santosh Shah Baltasar Beferull-Lozano Group of Information and Communication Systems Instituto de Robótica y Tecnologías de la Información y las Comunicaciones Universidad de Valencia Paterna Valencia Spain

In this paper, we consider the problem of power-efficient distributed estimation of a localized event in the large-scale Wireless sensor Networks (WSNs). In order to increase the power efficiency in these networks, we develop a joint optimization problem that involves both selecting a subset of active sensors and the routing structure so that the quality of estimation at a given querying node is the best possible subject to a total imposed communication cost. 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 iterative distributed to optimize jointly the sensor selection and the routing structure. We also provide a lower bound for our optimization problem and show that our iterative distributed 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 the fact that because of the interplay between communication cost and gain in estimation when fusing measurements from different sensors, the traditional Shortest Path Tree (SPT) routing structure, widely used in practice, is no longer optimal, that is, our routing structures provide a better trade-off between the overall communication cost and estimation accuracy. Comparing to more conventional sensor selection and fixed routing algorithms, our proposed joint sensor selection and routing algorithms yield a significant amount of energy saving.

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ERRAGMap: Visualization tool

ERRAGMap: Visualization tool

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8th international conference on Information Science and Digital Content Technology, ICIDT 2012

作者： Gillani, Saira Naz, Sheneela Naeem, Muhammad Afzal, Muhammad Tanvir Qayyum, Amir M. A. Jinnah University Islamabad Pakistan Center of Excellence in Data Mining M. A. Jinnah University Islamabad Pakistan Distributed and Semantic Computing M. A. Jinnah University Islamabad Pakistan

ISBN: (纸本)9788988678695

Earthquakes are considered one of the major disastrous situations for any nation. the horrible earthquake may claim hundreds of lives, thousands of injuries and demolishing thousands of houses. When an earthquake hits a nation then number of management bodies (such as: government organizations, non-government organizations (NGOs)) are actively involved in reinstating the damages. Generally, these organizations deal with stats of build and still-to-be build infrastructure (roads, buildings, and houses etc). Currently, this information is presented to the organizations as a raw text in huge amount. therefore, it becomes difficult to highlight key areas where an immediate start of rehabilitation process is inevitable. In the past, some systems have been developed to present such information in structured form by using some visualization techniques. However, these tools are inadequate because of the following reasons: 1) Most of these tools are about geotechnical conditions of effected area and can provide help to describe seismic hazards 2) Some systems show trends of earthquakes in specific region. 3). None of the systems describe the rehabilitation process in an easily conceivable way. therefore, this becomes an interesting and challenging research problem to build such a system that can overcome the above mentioned limitations of current techniques and systems. In this research, we present such a system called ERRAGMAP. this geo spatial tool discovers and presents deep insight into the data related to rehabilitation of the destroyed houses in the earthquake affected areas. Our contributions in this research are as follows: 1) critical analysis of existing tools of visualization for earthquake rehabilitation systems 2) propose and develop a framework for converting raw data into actionable knowledge, 3) propose, develop and evaluate an innovative visualization technique. © 2012 AICIT.

关键词： Visualization

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Controlled Straight Mobility and Energy-Aware Routing in Robotic Wireless sensor Networks

Controlled Straight Mobility and Energy-Aware Routing in Rob...

引用

international conference on distributed computing in sensor systems (dcoss)

作者： Rafael Falcon Hai Liu Amiya Nayak Ivan Stojmenovic Electrical Engineering and Computer Science (EECS) University of Ottawa Ottawa Canada Computer Science Department Hong Kong Baptist University Hong Kong China

Power-aware routing and controlled mobility schemes are two commonly used mechanisms for improving communications in a wireless sensor network. While the former actively consider the transmission costs when selecting the next hop on the route, the latter instruct mobile relay nodes (either sensors or actuators) to pursue more promising locations so as to optimize end-to-end transmission power. Rarely, if ever, the two methodologies are exploited together for achieving relevant energy savings and prolonging network lifetime. In this paper, we introduce a hybrid routing-mobility model for the optimization of network communications. First, we find a multi-hop path between a source and its destination in an energy-efficient fashion and then we move all hop nodes in an uninterrupted, straight manner to some predefined spots with optimal energy-saving properties, fully preserving the path connectivity as they move. Such synergetic approach allowed us to: (1) seamlessly guarantee message delivery regardless of the network density (average number of neighbors per node), (2) easily incorporate any power-related optimization criterion to the routing protocol and (3) even target scenarios where both end nodes are actually disconnected from each other. Results gathered from extensive simulations argue for the introduction of the proposed hybrid framework.

关键词： Routing Routing protocols Relays Mobile communication Robot sensing systems Wireless sensor networks

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Neuron inspired collaborative transmission in wireless sensor networks

Neuron inspired collaborative transmission in wireless senso...

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8th Annual international conference on Mobile and Ubiquitous systems: computing, Networking and Services, MobiQuitous 2011

作者： Sigg, Stephan Jakimovski, Predrag Becker, Florian Schmidtke, Hedda R. Neumann, Alexander Ji, Yusheng Beigl, Michael Tokyo Japan Pervasive Computing Systems TecO Germany

ISBN: (纸本)9783642309724

We establish a wireless sensor network that emulates biological neuronal structures for the purpose of creating smart spaces. Two different types of wireless nodes working together are used to mimic the behaviour of a neuron consisting of dendrites, soma and synapses. the transmission among nodes that establish such a neuron structure is established by distributed beamforming techniques to enable simultaneous information transmission among neurons. through superposition of transmission signals, data from neighbouring nodes is perceived as background noise and does not interfere. In this way we show that beamforming and computation on the channel can be powerful tools to establish intelligent sensing systems even with minimal computational power. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

关键词： Neurons

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Radiation Awareness in three-Dimensional Wireless sensor Networks

Radiation Awareness in Three-Dimensional Wireless Sensor Net...

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international conference on distributed computing in sensor systems (dcoss)

作者： S. Nikoletseas D. Patroumpa V.K. Prasanna C. Raptopoulos J. Rolim Computer Technology Institute University of Patras Greece University of Southern California Los Angeles CA USA Centre Universitaire ďInformatique University of Geneva Switzerland

this research attempts a first step towards investigating the aspect of radiation awareness in environments with abundant heterogeneous wireless networking. We call radiation at a point of a 3D wireless network the total amount of electromagnetic quantity the point is exposed to, our definition incorporates the effect of topology as well as the time domain, data traffic and environment aspects. Even if the impact of radiation to human health remains largely unexplored and controversial, we believe it is worth trying to understand and control. We first analyze radiation in well known topologies (random and grids), randomness is meant to capture not only node placement but also uncertainty of the wireless propagation model. this initial understanding of how radiation adds (over space and time) can be useful in network design, to reduce health risks. We then focus on the minimum radiation path problem of finding the lowest radiation trajectory of a person moving from a source to a destination point of the network region. We propose three heuristics which provide low radiation paths while keeping path length low, one heuristic gets in fact quite close to the offline solution we compute by a shortest path algorithm. Finally, we investigate the interesting impact on the heuristics' performance of diverse node mobility.

关键词： Wireless sensor networks Random variables Electromagnetics Data communication Wireless networks Network topology

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Biologically-inspired Network "Memory" for Smarter Networking

Biologically-inspired Network "Memory" for Smarter Networkin...

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8th ieee international conference on Collaborative computing: Networking, Applications and Worksharing (CollaborateCom)

作者： Mokhtar, Bassem Eltoweissy, Mohamed Virginia Tech Bradley Dept Elect & Comp Engn Blacksburg VA 24061 USA Egypt Japan Univ Sci & Technol Dept Comp Sci & Engn Alexandria Egypt Virginia Tech ECE Dept Blacksburg VA USA Univ Arizona Tucson AZ 85721 USA

ISBN: (纸本)9781467327404;9781467327404

Emerging technologies such as the Internet of things generate huge amounts of network traffic and data which lead to significant challenges in a) ensuring availability of resources on-demand, b) recognizing emergent and abnormal behavior, and c) making effective decisions for efficient network operations. Network traffic data exhibit spatiotemporal patterns. Learning and maintaining the currently elusive rich semantics based on analyzing such patterns would help in mitigating those challenges. In this paper, we propose the concept of a network "memory" (or NetMem) to support smarter data-driven network operations as a foundational component of next generation networks. NetMem will enable networking objects to understand autonomously, at real-time, on-demand, and at low cost semantics with different levels of granularity and related to various network elements. Guided by the fact that human activities exhibit spatiotemporal data patterns;and the human memory extracts and maintains semantics to enable accordingly learning and predicting new things, we design NetMem to mimic functionalities of that memory. NetMem provides capabilities for semantics management through uniquely integrating data virtualization for homogenizing massive data originating from heterogeneous sources, cloud-like scalable storage, associative rule learning to recognize data patterns, and hidden Markov models for reasoning and extracting semantics clarifying normal/abnormal behavior. NetMem provides associative access to data patterns and relevant derived semantics to enable enhancements in early anomaly detection, more accurate behavior prediction and satisfying QoS requirements with better utilization of resources. We evaluate NetMem using simulation. Preliminary results demonstrate the positive impact of NetMem on various network management operations.

关键词： Network Semantics Data Virtualization Cloud Data Storage distributed systems Bio-inspired Design

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Power-Efficient Algorithms for Fourier Analysis over Random Wireless sensor Network

Power-Efficient Algorithms for Fourier Analysis over Random ...

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international conference on distributed computing in sensor systems (dcoss)

作者： Xi Xu Rashid Ansari Ashfaq Khokhar Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA

Reduced execution time and increased power efficiency are important objectives in the distributed execution of collaborative signal processing tasks over wireless sensor networks. the power-efficient implementation of the Fourier transform computation is an exemplar of distributed data communication and processing task widely used in the signal processing field. Past work has presented some energy-efficient in-network Fourier transform computation algorithms devised only for uniformly sampled one-dimensional (1D) sensor data. However the circumstance that sensors are randomly distributed over a 2D plane may be more practical, therefore the conventional two-dimensional Fast Fourier Transform (2D FFT) defined for data sampled on uniform grids is not directly applicable in such environments. We address this problem by designing a distributed hybrid structure consisting of local Nonequispaced Discrete Fourier Transform (NDFT) and global FFT computation. Firstly, NDFT method is applied in a suitable choice of clusters to get the initial uniform Fourier coefficients with allowable estimation error bounds. We experiment with classical linear as well as generalized interpolation methods to compute NDFT coefficients within each cluster. A separable 2D FFT is then performed over all these clusters by employing our proposed energy-efficient 1D FFT computation that reduces communication costs using a novel bit index mapping strategy for data exchanges between sensors. the proposed techniques are implemented in a SID net-SWANS platform to investigate the communication costs, execution time, and energy consumption. Our results show reduced execution time and improved energy consumption when compared with existing work.

关键词： Indexes Discrete Fourier transforms Wireless sensor networks Interpolation Algorithm design and analysis distributed databases Approximation algorithms

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A novel distributed energy-efficient self-organized algorithm for wireless ad hoc networks

A novel distributed energy-efficient self-organized algorith...

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8th international conference on Intelligent Environments, IE 2012

作者： Olascuaga-Cabrera, J. Guadalupe Mendez-Vazquez, Andres Lopez-Mellado, Ernesto CINVESTAV Unidad Guadalajara Av. del Bosque 1145 Col El Bajio 45015 Zapopan Jal Mexico

ISBN: (纸本)9780769547411

Wireless ad-hoc networks require a special management because of their hardware and energy limitations compared with wired networks. the problem of constructing a backbone structure over wireless ad-hoc networks has been widely researched. the basic problem is to minimize the wireless backbone size by taking into consideration the node's capabilities. therefore, an efficient, self-organized, scalable, and fault-tolerant algorithm is proposed, where node connection in the backbone is minimal. the proposed algorithm groups the node elements in clusters by means of a self-organization strategy based in four possible roles for each node in the network: leader, gateway, member and bridge. In order to show the performance of the algorithm, an implementation in the NS2 simulator is used. this simulation allows evaluating the structure built by the proposed algorithm. this allows showing that the proposed algorithm can obtain better results, in wireless backbone size and energy consumption, when comparing with MWAC algorithm. © 2012 ieee.

关键词： sensor networks

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Gain-Constrained Filtering with Probabilistic sensor Delays and Correlated Noises

Gain-Constrained Filtering with Probabilistic Sensor Delays ...

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18th international conference on Automation and computing (ICAC) - Integration of Design and Engineering

作者： Hu, Jun Wang, Zidong Shen, Bo Gao, Huijun Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin 150001 Peoples R China Brunel Univ Dept Informat Syst & Comp Uxbridge UB8 3PH Middx England Univ Duisburg Essen Inst Automat Control & Complex Syst D-47057 Duisburg Germany

ISBN: (纸本)9781908549006

In this paper, the gain-constrained recursive filtering problem is investigated for a class of time-varying stochastic systems with probabilistic sensor delays and correlated noises. the phenomenon of probabilistic sensor delays is modeled by introducing a diagonal matrix composed of Bernoulli distributed random variables taking values of 1 or 0, which means that the sensors may experience randomly occurring delays with individual delay characteristics. the process noise is finite-step auto-correlated. the purpose of the addressed gain-constrained filtering problem is to design a filter such that, for all probabilistic sensor delays, gain constraint as well as correlated noises, the cost function concerning the filtering error is minimized at each sampling instant, where the filter gain satisfies a certain equality constraint. A new recursive filtering algorithm is developed that ensures both the local optimality and the unbiasedness of the designed filter at each sampling instant which achieving the pre-specified filter gain constraints. A simulation example is provided to illustrate the effectiveness of the proposed filter design approach.

关键词： Time-varying systems recursive filtering probabilistic sensor delays gain constraint correlated noises

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