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检索条件"任意字段=First IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2005"

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Interconnecting WiFi Devices with ieee 802.15.4 Devices without Using a Gateway 11

Interconnecting WiFi Devices with IEEE 802.15.4 Devices with...

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ieee international conference on distributed computing in sensor systems dcoss

作者： Yin, Shengrong Li, Qiang Gnawali, Omprakash Univ Houston Dept Comp Sci Houston TX 77004 USA

ISBN: (纸本)9781479988563

In many wireless sensing and control application deployments, there is often a gateway device to bridge between the low power ieee 802.15.4 network and the Internet. The bridge has at least two interfaces. One interface communicates with the 802.15.4 wireless. The other interface either communicates with WiFi or wired network. When a user wants to send a command to the wireless controller, lets say at a smart home, the user may use a smartphone and send command over WiFi to the gateway, often through a cloud service provider. Then gateway shuttles the message from the wired or WiFi chip to the 802.15.4 chip. Then the gateway transmits the messages over the 802.15.4 chip into the 802.15.4 network. In this work, we design a novel modulation technique that runs on the WiFi devices (e.g., smartphone) and demodulation technique that runs on 802.15.4 devices (e.g., a wireless controller in a smarthome) to enable WiFi devices to directly communicate with 802.15.4 devices without any gateway. The key idea is to utilize crosstalk between 802.11 and 802.15.4 channels as the medium for communication. We implemented the proposed technique on multiple platforms and are able to successfully achieve a data rate of 2 bytes per second with less than 10% bit error rate in uncontrolled environments.

关键词： crosstalk 802.15.4 RSSI 802.11

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Routing and Data Aggregation Toward a High Speed Sink in Wireless sensor Networks 11

Routing and Data Aggregation Toward a High Speed Sink in Wir...

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ieee international conference on distributed computing in sensor systems dcoss

作者： Balico, Leandro N. Oliveira, Horacio A. B. F. Nakamura, Eduardo F. Barreto, Raimundo S. Loureiro, Antonio A. F. Univ Fed Amazonas Inst Comp Manaus Amazonas Brazil Univ Fed Minas Gerais Dept Comp Sci Belo Horizonte MG Brazil Univ Fed Roraima Dept Comp Sci Boa Vista RR Brazil

ISBN: (纸本)9781479988563

In this work, we study the impact of data aggregation in WSNs with mobile sink nodes that can move at higher speeds. In these cases, propagated queries cannot be answered by using the sink's position when the query was sent, since the sink node will probably be elsewhere. Therefore, conventional data aggregation schemes may not be appropriate due to this high speed. Thus, we propose and evaluate the performance of three new algorithms for data routing and aggregation in WSNs when the sink is moving at a high speed. These algorithms explore the sink movement to create a routing graph composed of the union paths that intersect the sink's trajectory. At each hop, the sink speed and current network delays are used as metric to guide in-network data aggregation. Our results clearly show significant energy savings and efficient data delivery achieved by the proposed algorithms in different scenarios.

关键词： wireless sensor networks routing data aggregation high speed

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High Resolution Air Pollution Maps in Urban Environments Using Mobile sensor Networks 11

High Resolution Air Pollution Maps in Urban Environments Usi...

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ieee international conference on distributed computing in sensor systems dcoss

作者： Marjovi, Ali Arfire, Adrian Martinoli, Alcherio Ecole Polytech Fed Lausanne Sch Architecture Civil & Environm Engn Distributed Intelligent Syst & Algorithms Lab Lausanne Switzerland

ISBN: (纸本)9781479988563

We propose three modeling methods using a mobile sensor network to generate high spatio-temporal resolution air pollution maps for urban environments. In our deployment in Lausanne (Switzerland), dedicated sensing nodes are anchored to the public buses and measure multiple air quality parameters including the Lung Deposited Surface Area (LDSA), a state of the art metric for quantifying human exposure to ultrafine particles. In this paper, our focus is on generating LDSA maps. In particular, since the sensor network coverage is spatially and temporally dynamic, we leverage models to estimate the values for the locations and times where the data are not available. We first discretize the area topologically based on the street segments in the city and we then propose the following three prediction models: i) a log-linear regression model based on nine meteorological (e.g., temperature and precipitations) and gaseous (e.g., NO2 and CO) explanatory variables measured at two static stations in the city, ii) a novel network-based log-linear regression model that takes into account the LDSA values of the most correlated streets and also the nine explanatory variables mentioned above, iii) a novel Probabilistic Graphical Model (PGM) in which each street segment is considered as one node of the graph, and inference on conditional joint probability distributions of the nodes results in estimating the values in the nodes of interest. More than 44 millions of geo- and time-stamped LDSA measurements (i.e., more than 14 months of real data) are used in this paper to evaluate the proposed modeling approaches in various time resolutions (hourly, daily, weekly and monthly). The results show that the three approaches bring significant improvements in R-2, RMSE and FAC metrics compared to a baseline K-Nearest Neighbor method.

关键词： Air pollution map Environmental monitoring Mobile sensor network Urban air pollution sensor networks ATMOSPHERIC HAZE urban environment environmental monitoring Air contamination Ganglia simple regression (model) state of the art Street maps

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Spatio-Temporal Hierarchical Data Aggregation using Compressive Sensing (ST-HDACS) 11

Spatio-Temporal Hierarchical Data Aggregation using Compress...

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ieee international conference on distributed computing in sensor systems dcoss

作者： Xu, Xi Ansari, Rashid Khokhar, Ashfaq Univ Illinois Dept Elect & Comp Engn Chicago IL 60607 USA IIT Dept Elect & Comp Engn Chicago IL 60616 USA

ISBN: (纸本)9781479988563

The problem of power-efficient data aggregation in wireless sensor networks (WSNs) using Compressive Sensing (CS) to reduce the amount of data communicated is addressed here. Existing CS-based data aggregation methods can be categorized as either those that apply CS spatially to minimize the amount of data to be communicated in the routing path, or those that seek to minimize the amount of data by applying CS temporally at each sensor. A recently reported scheme that is described as a Spatial-Temporal CS scheme randomly selects a subset of data but does not apply compression in the routing path. Here we formulate a spatial-temporal data collection model in WSNs and refer to it as Spatial-Temporal Hierarchical Data Aggregation using Compressive Sensing (ST-HDACS). The idea underlying ST-HDACS consists of two key components: firstly, for each time snapshot of data collected in the network, a subset of nodes is randomly selected and designated for data sensing and transmission. A power-efficient Adaptive Hierarchical Data Aggregation (A-HDACS) scheme is incorporated in our work to compress the spatial data to be communicated in the routing path. Secondly, after performing data collection over a designated time period, a Matrix Completion (MC) problem is executed in the fusion center to recover the data for the entire network over the full data collection period. The performance of the proposed method is evaluated and it is demonstrated that ST-HDACS scheme reduces the amount of data for transmission and improves the associated energy consumption more effectively than existing CS-based data aggregation schemes.

关键词： Data Aggregation Compressive Sensing Matrix Completion Wireless sensor Networks Hierarchy Power Efficient Algorithm

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Interactive Wireless Charging for Energy Balance

Interactive Wireless Charging for Energy Balance

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international conference on distributed computing systems

作者： Sotiris Nikoletseas Theofanis P. Raptis Christoforos Raptopoulos Computer Technology Institute and Press “Diophantus” Greece Department of Computer Engineering and Informatics University of Patras Greece

Wireless energy transfer is an emerging technology that is used in networks of battery-powered devices in order to deliver energy and keep the network functional. Existing state-of-the-art studies have mainly focused on applying this technology on networks of relatively strong computational and communicational capabilities (wireless sensor networks, ad-hoc networks), also they assume one-directional energy transfer from special chargers to the network nodes. Different from these works, we here study (for the first time in the state-of-theart) interactive, "peer-to-peer" wireless charging in populations of much more resource-limited, mobile agents that abstract distributed portable devices. In this new model for interactive wireless charging, we assume that the agents are capable of achieving bi-directional wireless energy transfer acting both as energy transmitters and harvesters. We consider the cases of both loss-less and lossy energy transfer and provide an upper bound on the time needed to reach a balanced energy distribution in the population. We investigate the delicate impact of the diversity of energy levels on eventual energy balance achieved and highlight some key elements of the charging procedure. In the light of the above, we design and evaluate three interaction protocols that achieve different tradeoffs between energy balance, time and energy efficiency.

关键词： Sociology Statistics Protocols Energy exchange Wireless communication Wireless sensor networks Ad hoc networks

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Scheduling Low-Utilized Real-Time systems with End-to-End Timing Constraints

Scheduling Low-Utilized Real-Time Systems with End-to-End Ti...

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ieee international conference on Embedded and Real-Time computing systems and Applications (RTCSA)

作者： Chih-Yao Chuang Yung-Chieh Chen Chih-Wen Hsueh Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan R.O.C.

ISBN: (纸本)9781509024803

End-to-end delay is one of the most important timing constraints in distributed real-time systems (DRTS) [1], especially in the area of wireless sensor network (WSN) or Internet of Things (IoT). Since we may need to collect data from sensor nodes and react immediately. Thus, tasks must be executed in a distance-constrained manner. That is, the temporal distance between any two consecutive executions of a task should always be less than a certain amount of time. In DRTS, transactions are decomposed into a group of tasks, and periodic model might not be efficient enough, since the temporal distance between two consecutive executions of task could be two times of its period in the worst case. Moreover, an execution will not be always ready in a period, which might incur extra end-to-end delay in DRTS. Pinwheel scheduling algorithms have been designed to schedule tasks with distance constraint. But meeting distance constraints in a node does not guarantee minimized end-to-end delay of a transaction. Therefore, DSr, a distributed pinwheel scheduling algorithm, focuses on reducing end-to-end delay systematically and synchronously [2]. Although the pinwheel scheduling algorithms provide simple scheduling bounds and approaches for fully utilized tasks, for the simpler sensor nodes with limited hardware timer support, it might not be easy to execute the pinwheel scheduling algorithms accordingly and guarantee the synchronous results. We find that there exists a simple feasible algorithm (e.g. first In first Out, FIFO) with tight scheduling bound. Although it is always schedulable only in low-utilized systems using FIFO, it results in shorter endto- end delays than DSr in most cases with high utilization. To simplify, we focus only on the system of two nodes with the same utilization. As shown in Figure 1, we simulate the total end-to-end delay with different number of transactions, n, and utilization, ρ, and find that FIFO outperforms DSr. That means transactions can be fini

关键词： Delays Wireless sensor networks Real-time systems Scheduling algorithms Internet of things

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Use Cases of Pervasive Artificial Intelligence for Smart Cities Challenges

Use Cases of Pervasive Artificial Intelligence for Smart Cit...

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ieee international conference on Ubiquitous Intelligence and computing

作者： Julien Nigon Estele Glize David Dupas Fabrice Crasnier Jeremy Boes Team SMAC IRIT Universitee Federale de Toulouse SWIFT

ISBN: (纸本)9781509027729

Software engineering has been historically top-down. From a fully specified problem, a software engineer needs to detail each step of the resolution to get a solution. The resulting program will be functionally adequate as long as its execution environment complies with the original specifications. With their large amount of data and their ever changing multi-level dynamics, smart cities are too complex for a top-down approach. They prompt the need for a paradigm shift in computer science. Programs should be able to self-adapt on the fly, to handle unspecified events, and to efficiently deal with tremendous amount of data. To this end, bottom-up approach should become the norm. Machine learning is a first step, and distributed computing helps. Multi-Agent systems (MAS) can combine machine learning and distributed computing and may be easily designed with a bottom-up approach. This paper explores how MASs can answer challenges at various levels of smart cities, from sensors networks to ambient intelligence.

关键词： Software engineering Smart cities distributed computing Artificial Intelligence bottom-up approach Ambient intelligence Multi-agent systems sensor networks Machine Learning Flies first Step

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CrowdMap: Accurate Reconstruction of Indoor Floor Plans from Crowdsourced sensor-Rich Videos 35

CrowdMap: Accurate Reconstruction of Indoor Floor Plans from...

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2015 ieee 35th international conference on distributed computing systems

作者： Chen, Si Li, Muyuan Ren, Kui Qiao, Chunming SUNY Buffalo Comp Sci & Engn Dept Buffalo NY USA

ISBN: (纸本)9781467372145

Lack of an accurate and low-cost method to reconstruct indoor maps is the main reason behind the current sporadic availability of digital building floor plans. The conventional approach using professional equipment is very costly and only available in the most popular areas. In this paper, we propose and demonstrate CrowdMap, a crowdsourcing system utilizing sensor-rich video data from mobile users for indoor floor plan reconstruction with low-cost. The key idea of CrowdMap is to first jointly leverage crowdsourced sensory and video data to track user movements, then use the inferred user motion traces and context of the image to produce an accurate floor plan. In particular, we exploit the sequential relationship between each consecutive frame abstracted from the video to improve system performance. Our experiments in three college buildings show that CrowdMap achieves a precision of hallway shape around 88%, a recall around 93% and a F-measure around 90%. In addition, we achieve on average 9.8% room area error and on average 6.5% room aspect ratio error. The evaluation result demonstrates a significant improvement of accuracy compared with other crowdsourcing floor plan reconstruction systems.

关键词： crowdsourcing Floorplan mobile sensing reconstruction system video

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Enhancing Dependability of Cloud-Based IoT Services through Virtualization

Enhancing Dependability of Cloud-Based IoT Services through ...

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ieee international conference on Internet-of-Things Design and Implementation (IoTDI)

作者： Kashif Sana Dar Amir Taherkordi Frank Eliassen Networks & Distributed Systems Group University of Oslo Norway

As Internet of Things (IoT) technology moves forward, more and more IoT provided services are being pushed toward clouds. Since the operation of IoT services runs the risk of failures due to lossy communication links and error prone nature of physical objects, cloud providers (offering such services) should provide suitable platforms supporting two desired service dependability features -- i.e., reliability and availability. This issue has so far been addressed for specific application scenarios and often at the network layer. In this paper, we therefore aim at proposing a generic, model-based approach for enhancing these two important features at the application layer of cloud-based IoT systems. Following the principle of dependability by design, we build a framework based on the concept of virtualized IoT services, promising a service abstraction model to efficiently and simultaneously meet the dependability requirements of multiple cloud-based IoT applications. The proposed virtualization approach supports a variety of different dependability patterns and implements them according to the demands of the target application. We implemented the virtualization framework using the SicthSense cloud platform with satisfactory evaluation results on dependability metrics, such as maximum availability and the probability of failure on demand.

关键词： Virtualization Cloud computing Wireless sensor networks Redundancy Intelligent sensors

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Adaptive Edge Analytics for distributed Networked Control of Water systems

Adaptive Edge Analytics for Distributed Networked Control of...

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ieee international conference on Internet-of-Things Design and Implementation (IoTDI)

作者： Sokratis Kartakis Weiren Yu Reza Akhavan Julie A. McCann Department of Computing Imperial College London UK

Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.

关键词： Image edge detection Algorithm design and analysis Tuning sensors Control systems Servers Vibrations

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