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Pervasive Computing and Communications (PerCom), 2010 IEEE International Conference on

Date March 29 2010-April 2 2010

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Displaying Results 1 - 25 of 34
  • Table of contents

    Page(s): 1 - 3
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    Freely Available from IEEE
  • Message from the general chairs

    Page(s): 1
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    Freely Available from IEEE
  • Message from the technical program chairs

    Page(s): 1 - 2
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    Freely Available from IEEE
  • Conference organization

    Page(s): 1 - 3
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    Freely Available from IEEE
  • Large-scale context management

    Page(s): 1
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    Freely Available from IEEE
  • Local map generation using position and communication history of mobile nodes

    Page(s): 2 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2737 KB) |  | HTML iconHTML  

    In this paper, we propose an algorithm to estimate 2D shapes and positions of obstacles such as buildings using GPS and wireless communication history of mobile nodes. Our algorithm enables quick recognition of geography, which is required in broader types of activities such as rescue activities in emergency situations. Nevertheless, detailed building maps might not be immediately available in private regions such as large factories, warehouses and universities, or prepared maps might not be effective due to collapse of buildings or roads in disaster situations. Some methodologies adopt range measurement sensors like infra-red and laser sensors or cameras. However, they require dedicated hardware and actions for the measurement. Meanwhile, the proposed method can create a rough 2D view of buildings and roads using only wireless communication history between mobile nodes and position history from GPS receivers. The results from the experiment conducted in 150 m×190 m region on our university campus assuming rescue and treatment actions by 15 members have shown that our method could generate a local map with 85% accuracy within 350 seconds. We have also validated the performance of our algorithm by simulations with various settings. View full abstract»

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  • Interactive streaming of structured data

    Page(s): 11 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1295 KB) |  | HTML iconHTML  

    We present ChunkStream, a system for efficient streaming and interactive editing of online video. Rather than using a specialized protocol and stream format, ChunkStream makes use of a generic mechanism employing chunks. Chunks are fixed-size arrays that contain a mixture of scalar data and references to other chunks. Chunks allow programmers to expose large, but fine-grained, data structures over the network. ChunkStream represents video clips using simple data types like linked lists and search trees, allowing a client to retrieve and work with only the portions of the clips that it needs. ChunkStream supports resource-adaptive playback and "live" streaming of real-time video as well as fast, frame-accurate seeking; bandwidth-efficient high-speed playback; and compilation of editing decisions from a set of clips. Benchmarks indicate that ChunkStream uses less bandwidth than HTTP Live Streaming while providing better support for editing primitives. View full abstract»

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  • Opportunistic web access via WLAN hotspots

    Page(s): 20 - 30
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1455 KB) |  | HTML iconHTML  

    Mobile phones are becoming commonplace for consuming Internet content and services. However, availability, affordability, and quality of the supposedly ubiquitous cellular network infrastructure may be limited, so that delay-tolerant web access via WLAN hotspots becomes an interesting alternative, even in urban areas. In this paper we explore mobile web access using asynchronous messaging via WLAN hotspots: for nodes directly connected to an access point and nodes relying on others for message forwarding. We investigate different routing and caching approaches using real-world access point locations in Helsinki. We find that a significant number of requests can be satisfied without requiring an always-on infrastructure, provided that users are willing to tolerate some response delay; this allows offloading traffic from the cellular network. We also report on our prototype implementation of mobile DTN-based web browsing. View full abstract»

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  • Engineering energy-efficient target detection applications in Wireless Sensor Networks

    Page(s): 31 - 39
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1589 KB) |  | HTML iconHTML  

    This paper addresses the problem of engineering energy-efficient target detection applications using unattended Wireless Sensor Networks (WSNs) for long-lasting surveillance of areas of interest. As battery energy depletion is an issue in this context, an approach consists of switching on and off sensing and communication modules of wireless sensors according to duty cycles. Making these modules work in an intermittent fashion impacts (i) the latency of notification transmission (depending on the communication duty cycle) and (ii) the probability of missed target detection (depending on the number of deployed nodes and the sensing duty cycle). In order to optimize the system parameters according to performance objectives, we first derive an analytical engineering toolkit which evaluates the probability of missed detection (Pmd), the notification transmission latency (D), and the network lifetime (¿) under the assumption of random node deployment. Then, we show how this toolbox can be used to optimally configure system parameters under realistic performance constraints. View full abstract»

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  • Blurring snapshots: Temporal inference of missing and uncertain data

    Page(s): 40 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1360 KB) |  | HTML iconHTML  

    Many pervasive computing applications continuously monitor state changes in the environment by acquiring, interpreting and responding to information from sensors embedded in the environment. However, it is extremely difficult and expensive to obtain a continuous, complete, and consistent picture of a continuously evolving operating environment. One standard technique to mitigate this problem is to employ mathematical models that compute missing data from sampled observations thereby approximating a continuous and complete stream of information. However, existing models have traditionally not incorporated a notion of temporal validity, or the quantification of imprecision associated with inferring data values from past or future observations. In this paper, we support continuous monitoring of dynamic pervasive computing phenomena through the use of a series of snapshot queries. We define a decay function and a set of inference approaches to filling in missing and uncertain data in this continuous query.We evaluate the usefulness of this abstraction in its application to complex spatio-temporal pattern queries in pervasive computing networks. View full abstract»

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  • Adaptive deployment for pervasive data gathering in connectivity-challenged environments

    Page(s): 51 - 59
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2055 KB) |  | HTML iconHTML  

    Some current and future pervasive data driven applications must operate in ¿extreme¿ environments where end-to-end connectivity cannot be guaranteed at all times. In fact, it is likely that in these environments partitions are, rather than exceptions, part of the normal network operation. In this paper, we introduce Cover, a suite of adaptive strategies to control the trajectory of ¿infrastructure¿ nodes, which are deployed to bridge network partitions and thus play a critical role in data delivery. In particular, we focus on applications where end (or target) nodes are mobile and their mobility is unknown. Our goal is then to deploy and manage infrastructure nodes so that application-level requirements such as reliable data delivery and latency are met while still limiting deployment cost and balancing the load among infrastructure nodes. Cover achieves these goals using a localized and adaptive approach to infrastructure management based on the observed mobility of target nodes. To this end, Cover takes advantage of contact opportunities between infrastructure nodes to exchange information about their covered zones, and thus, help monitor targets in a more efficient fashion. Through extensive simulations, we show how Cover's adaptive features yield a fair distribution of targets per infrastructure node based only on limited network knowledge. View full abstract»

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  • Sell your experiences: a market mechanism based incentive for participatory sensing

    Page(s): 60 - 68
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1580 KB) |  | HTML iconHTML  

    This paper studies economic models of user participation incentive in participatory sensing applications. User participation is the most important element in participatory sensing applications for providing adequate level of service quality. However, incentive mechanism and its economic model for user participation have never been addressed so far in this research domain. In order to stimulate user participation, we design and evaluate a novel Reverse Auction based Dynamic Price (RADP) incentive mechanism, where users can sell their sensing data to a service provider with users' claimed bid prices. The proposed incentive mechanism focuses on minimizing and stabilizing incentive cost while maintaining adequate number of participants by preventing users from dropping out of participatory sensing applications. Compared with a Random Selection with Fixed Price (RSFP) incentive mechanism, the proposed mechanism not only reduces the incentive cost for retaining same number of participants by more than 60% but also improves the fairness of incentive distribution and social welfare. More importantly, RADP can remove burden of accurate pricing for user sensing data, the most difficult step in RSFP. View full abstract»

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  • Ten views to context awareness

    Page(s): 69
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    Freely Available from IEEE
  • Decomposing power measurements for mobile devices

    Page(s): 70 - 78
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2891 KB) |  | HTML iconHTML  

    Modern mobile phones are an appealing platform for pervasive computing applications. However, the complexity of these devices makes it difficult for developers to understand the power consumption of their applications. Our measurement framework is the first we have seen which can produce fine-grained, annotated traces of a phone's power consumption and is designed to develop an understanding of how particular aspects of an application drive energy use. We are using our framework to analyse the power consumption of Android-based G1 and Magic handsets and show that particular choices of message size and send buffer can alter the energy required to send data by an order of magnitude in certain cases. View full abstract»

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  • An integrated network of roadside sensors and vehicles for driving safety: Concept, design and experiments

    Page(s): 79 - 87
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1250 KB) |  | HTML iconHTML  

    One major goal of the vehicular ad hoc network (VANET) is to improve driving safety. However, the VANET may not guarantee timely detection of dangerous road conditions or maintain communication connectivity when the network density is low (e.g., in rural highways), which may pose as a big threat to driving safety. Towards addressing the problem, we propose to integrate the VANET with the inexpensive wireless sensor network (WSN). That is, sensor nodes are deployed along the roadside to sense road conditions, and to buffer and deliver information about dangerous conditions to vehicles regardless of the density or connectivity of the VANET. Along with the concept of VANET-WSN integration, new challenges arise and should be addressed. In this paper, we investigate these challenges and propose schemes for effective and efficient vehicle-sensor and sensor-sensor interactions. Prototype of the designed system has been implemented and tested in the field. Extensive simulations have also been conducted to evaluate the designed schemes. The results demonstrate various design tradeoffs, and indicate that satisfactory safety and energy efficiency can be achieved simultaneously when system parameters are appropriately chosen. View full abstract»

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  • Negotiate power and performance in the reality of RFID systems

    Page(s): 88 - 97
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2175 KB) |  | HTML iconHTML  

    Recent years have witnessed the wide adoption of the RFID technology in many important application domains including logistics, inventory, retailing, public transportation, and security. Though RFID tags (transponders) can be passive, the high power consumption of RFID readers (interrogators) has become a critical issue as handheld and mobile readers are increasingly available in pervasive computing environments. Moreover, high transmission power aggravates interference, complicating the deployment and operation of RFID systems. In this paper, we present an energy-efficient RFID inventory algorithm called Automatic Power Stepping (APS). The design of APS is based on extensive empirical study on passive tags, and takes into consideration several important details such as tag response states and variable slot lengths. APS dynamically estimates the number of tags to be read, incrementally adjusts power level to use sufficient but not excessive power for communication, and consequently reduces both the energy consumption for reading a set of tags and the possibility of collisions. We design APS to be compatible with the current Class-1 Generation-2 RFID standards and hence a reader running APS can interact with existing commercial tags without modification. We have implemented APS both on the NI RFID testing platform and in a high-fidelity simulator. The evaluation shows that APS can save more than 60% energy used by RFID readers. View full abstract»

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  • An event-based approach to multi-modal activity modeling and recognition

    Page(s): 98 - 106
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (592 KB) |  | HTML iconHTML  

    The topic of human activity modeling and recognition still provides many challenges, despite receiving considerable attention. These challenges include the large number of sensors often required for accurate activity recognition, and the need for user-specific training samples. In this paper, an approach is presented for recognition of activities of daily living (ADL) using only a single camera and microphone as sensors. Scene analysis techniques are used to classify audio and video events, which are used to model a set of activities using hidden Markov models. Data was obtained through recordings of 8 participants. The events generated by scene analysis algorithms are compared to events obtained through manual annotation. In addition, several model parameter estimation techniques are compared. In a number of experiments, it is shown that if activities are fully observed these models yield a class accuracy of 97% on annotated data, and 94% on scene analysis data. Using a sliding window approach to classify activities in progress yields a class accuracy of 79% on annotated data, and 73% on scene analysis data. It is also shown that a multi-modal approach yields superior results compared to either individual modality on scene analysis data. Finally, it can be concluded the created models perform well even across participants. View full abstract»

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  • Capture, recognition, and visualization of human semantic interactions in meetings

    Page(s): 107 - 115
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1978 KB) |  | HTML iconHTML  

    Human interaction is one of the most important characteristics of group social dynamics in meetings. In this paper, we propose an approach for capture, recognition, and visualization of human interactions. Unlike physical interactions (e.g., turn-taking and addressing), the human interactions considered here are incorporated with semantics, i.e., user intention or attitude toward a topic. We adopt a collaborative approach for capturing interactions by employing multiple sensors, such as video cameras, microphones, and motion sensors. A multimodal method is proposed for interaction recognition based on a variety of contexts, including head gestures, attention from others, speech tone, speaking time, interaction occasion (spontaneous or reactive), and information about the previous interaction. A support vector machines (SVM) classifier is used to classify human interaction based on these features. A graphical user interface called MMBrowser is presented for interaction visualization. Experimental results have shown the effectiveness of our approach. View full abstract»

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  • AutoGait: A mobile platform that accurately estimates the distance walked

    Page(s): 116 - 124
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2454 KB) |  | HTML iconHTML  

    AutoGait is a mobile platform that autonomously discovers a user's walking profile and accurately estimates the distance walked. The discovery is made by utilizing the GPS in the user's mobile device when the user is walking outdoors. This profile can then be used both indoors and outdoors to estimate the distance walked. To model the person's walking profile, we take advantage of the fact that a linear relationship exists between step frequency and stride length, which is unique to individuals and applies to everyone regardless of age. Autonomous calibration invisible to users allows the system to maintain a high level of accuracy under changing conditions. AutoGait can be integrated into any pedometer or indoor navigation software on handheld devices as long as they are equipped with GPS. The main contribution of this paper is two fold: (1) we propose an auto-calibration method that trains a person's walking profile by effectively processing noisy GPS readings, and (2) we build a prototype system and validate its performance by performing extensive experiments. Our experimental results confirm that the proposed auto-calibration method can accurately estimate a person's walking profile and thus significantly reduce the error rate. View full abstract»

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  • MediAlly: A provenance-aware remote health monitoring middleware

    Page(s): 125 - 134
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1518 KB) |  | HTML iconHTML  

    This paper presents MediAlly, a middleware for supporting energy-efficient, long-term remote health monitoring. Data is collected using physiological sensors and transported back to the middleware using a smart phone. The key to MediAlly's energy efficient operations lies in the adoption of an Activity Triggered Deep Monitoring (ATDM) paradigm, where data collection episodes are triggered only when the subject is determined to possess a specified context. MediAlly supports the on-demand collection of contextual provenance using a novel low-overhead provenance collection sub-system. The behaviour of this sub-system is configured using an application-defined context composition graph. The resulting provenance stream provides valuable insight while interpreting the `episodic' sensor data streams. The paper also describes our prototype implementation of MediAlly using commercially available devices. View full abstract»

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  • Orchestrator: An active resource orchestration framework for mobile context monitoring in sensor-rich mobile environments

    Page(s): 135 - 144
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4180 KB) |  | HTML iconHTML  

    In this paper, we present Orchestrator, an active resource orchestration framework for mobile context monitoring. Emerging pervasive environments will introduce a PAN-scale sensor-rich mobile platform consisting of a mobile device and many wearable and space-embedded sensors. In such environments, it is challenging to enable multiple context-aware applications requiring continuous context monitoring to simultaneously run and share highly scarce and dynamic resources. Orchestrator enables multiple applications to effectively share the resources while exploiting the full capacity of overall system resources and providing high-quality service to users. For effective orchestration, we propose an active resource use orchestration approach that actively finds appropriate resource uses for applications and flexibly utilizes them depending on dynamic system conditions. Orchestrator is built upon a prototype platform that consists of off-the-shelf mobile devices and sensor motes. We present the detailed design, implementation, and evaluation of Orchestrator. The evaluation results show that Orchestrator enables applications in a resource-efficient way. View full abstract»

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  • Taming software adaptability with architecture-centric framework

    Page(s): 145 - 151
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1989 KB) |  | HTML iconHTML  

    In many cases, we would like to enhance the predefined adaptability of a running application, for example, to enable it to cope with a strange environment. To make such kind of runtime modifications is a challenging task. In existing engineering practices, the online policy upgrade approach just focuses on the modification of adaptation decision logic and lacks system-level means to assess the validity of an upgrade. This paper proposes a framework for adaptive software that supports the online reconfiguration of each concern in the ¿sensing-decision-execution¿ adaptation loop. To achieve this goal, our framework supports an architecture style which encapsulates adaptation concerns as software architecture elements. And then, it maintains a runtime architecture model to enable the dynamic reconfiguration of those elements as well as help to ensure the validity of a change. A third party can selectively add, remove or replace part of this model to enhance the running application's adaptability. We validated this framework by two cases extracted from real life. View full abstract»

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  • Pervasive computing: What next?

    Page(s): 152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (51 KB) |  | HTML iconHTML  

    Each year more than ten billion embedded microprocessors are produced. This number is expected to increase spectacularly over the next decade, making electronic devices more and more pervasive. Such devices will range from a few hundred transistors (small sensors, actuators, etc.) to millions of transistor devices (multicore processors, displays, memories, sensors etc.). Wired and wireless network technologies are used to interconnect these components to realise broader, more capable, networks. Electronic devices and systems exist around us providing different services to the people in different situations: at home, at work, in their office, or driving a car on the street or at car park. View full abstract»

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  • Tuning to your position: FM radio based indoor localization with spontaneous recalibration

    Page(s): 153 - 161
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2124 KB) |  | HTML iconHTML  

    Position of mobile users has become highly important information in pervasive computing environments. Indoor localization systems based on Wi-Fi signal strength fingerprinting techniques are widely used in office buildings with existing Wi-Fi infrastructure. Our previous work has proposed a solution based on exploitation of FM signal to deal with environments not covered with Wi-Fi signal or environments with only single Wi-Fi access point. However, a general problem of indoor wireless positioning systems pertains to signal degradation due to the environmental factors affecting signal propagation. Therefore, in order to maintain a desirable level of localization accuracy, it becomes necessary to perform periodic calibration of the system, which is either time consuming or requires dedicated equipment and expert knowledge. In this paper, we present a comparison of FM versus Wi-Fi positioning systems and a combination of both systems, exploiting their strengths for indoors positioning. Finally, we address the problem of recalibration by introducing a novel concept of spontaneous recalibration and demonstrate it using the FM localization system. View full abstract»

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  • Dead reckoning from the pocket - An experimental study

    Page(s): 162 - 170
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4223 KB) |  | HTML iconHTML  

    Modern mobile phones enable absolute positioning based on GPS or WiFi. However, incremental positioning based on dead reckoning is an interesting source of complementary information, e.g., for indoor positioning or for filling in reception gaps. In the literature however, reasonable dead reckoning accuracies have been reported for fixed and typically a priori known device placements only, e.g., on the hip. Therefore, this paper contributes an experimental study of several published as well as novel approaches for dead reckoning in a scenario with unconstrained placement of a device in the user's trouser pockets. Utilizing the movement of a sensor in a trouser pocket due to body motion, we estimate the user's walking direction and steps robustly for arbitrary placements in the pocket and without additional body-worn sensors. We evaluate these methods on a large dataset of 23 traces of 8 different persons, and compare different approaches. View full abstract»

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