We propose a distributed coalition formation strategy for collaborative sensing tasks in camera sensor networks. The proposed model supports task-dependent node selection and aggregation through an announcement/biddin...
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ISBN:
(纸本)9783540730897
We propose a distributed coalition formation strategy for collaborative sensing tasks in camera sensor networks. The proposed model supports task-dependent node selection and aggregation through an announcement/bidding/ selection strategy. It resolves node assignment conflicts by solving an equivalent constraint satisfaction problem. Our technique is scalable, as it lacks any central controller, and it is robust to node failures and imperfect communication. Another unique aspect of our work is that we advocate visually and behaviorally realistic virtual environments as a simulation tool in support of research on large-scale camera sensor networks. Specifically, our visual sensor network comprises uncalibrated static and active simulated video surveillance cameras deployed in a virtual train station populated by autonomously self-animating pedestrians. The readily reconfigurable virtual cameras generate synthetic video feeds that emulate those generated by real surveillance cameras monitoring public spaces. Our simulation approach, which runs on high-end commodity PCs, has proven to be beneficial because this type of research would be difficult to carry out in the real world in view of the impediments to deploying and experimenting with an appropriately complex camera network in extensive public spaces.
Empirical studies show that wireless sensor networks (WSNs) are extremely prone to the hidden terminal problem. As much as 50% of packet losses have been blamed to the hidden terminal problem under bursty communicatio...
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Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values, and thus are...
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sensor network troubleshooting is a notoriously difficult task, further exacerbated by resource constraints, unreliable components, unpredictable natural phenomena, and experimental programming paradigms. This paper p...
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ISBN:
(纸本)9783540730897
sensor network troubleshooting is a notoriously difficult task, further exacerbated by resource constraints, unreliable components, unpredictable natural phenomena, and experimental programming paradigms. This paper presents SNTS (sensor Network Troubleshooting Suite), a tool that performs automated failure diagnosis in sensor networks. SNTS can be used to monitor network conditions using simple visualization techniques as well as to troubleshoot deployed distributedsensorsystems using data mining approaches. It is composed of (i) a data collection front-end that records events internal to the network and (ii) a data processing back-end for subsequent analysis. We use data mining techniques to automate failure diagnosis on the back-end. The assumption is that the occurrence of execution conditions that cause failures (e.g., traversal of an execution path that contains a "bug" or occurrence of a sequence of events that a protocol was not designed to handle) will have a measurable correlation (by causality) with the resulting failure itself. Hence, by mining for network conditions that correlate with failure states the root causes of failure are revealed with high probability. To evaluate the effectiveness of the tool, we have used it to troubleshoot a tracking system called EnviroTrack [4], which, although performs well most of the time, occasionally fails to track targets correctly. Results show that SNTS can identify the major causes of the problem and give developers useful hints on improving the performance of the tracking system.
The geographic routing is an ideal approach to realize point-to-point routing in wireless sensor networks because packets can be delivered by only maintaining a small set of neighbors' physical positions. The geog...
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ISBN:
(纸本)9783540730897
The geographic routing is an ideal approach to realize point-to-point routing in wireless sensor networks because packets can be delivered by only maintaining a small set of neighbors' physical positions. The geographic routing assumes that a packet can be moved closer to the destination in the network topology if it is moved geographically closer to the destination in the physical space. This assumption, however, only holds in an ideal model where uniformly distributed nodes communicate with neighbors through wireless channels with perfect reception. Because this model oversimplifies the spatial complexity of a wireless sensor network, the geographic routing may often lead a packet to the local minimum or low quality route. Unlike the geographic forwarding, the ETX-embedding proposed in this paper can accurately encode both a network's topological structure and channel quality to small size nodes' virtual coordinates, which makes it possible for greedy forwarding to guide a packet along an optimal routing path. Our performance evaluation based on both the MICA2 sensor platform and TOSSIM simulator shows that the greedy forwarding based on ETX-embedding outperforms previous geographic routing approaches.
We introduce a virtual-node based mobile object tracking algorithm for mobile sensor networks, VINESTALK. The algorithm uses the Virtual Stationary Automata programming layer, consisting of mobile clients, virtual tim...
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Although the content of sensor messages describing "events of interest" may be encrypted to provide confidentiality, the context surrounding these events may also be sensitive and therefore should be protect...
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Wireless sensor networking, an emerging new field in technology, now opens a vast horizon of application scenarios including environment monitoring, home security and earthquake warning. Since the sensor nodes have li...
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Many Ubiquitous computing applications can be considered as planning and acting problems in environments characterised by uncertainty and partial observability Such systems rely on sensor data for information about th...
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ISBN:
(纸本)9780769528472
Many Ubiquitous computing applications can be considered as planning and acting problems in environments characterised by uncertainty and partial observability Such systems rely on sensor data for information about their environment and use stochastic or probabilistic reasoning algorithms to infer system state from sensor data. We propose a domain modelling technique that characterises the sensor and actuator infrastructure and the set of system states in Ubicomp application domains. We capture the location and geometry of all domain model elements and use these spatial properties to tailor system state determination to reflect the quality and spread of the sensor and actuator platform. tThe domain model is used to support the development of Ubicomp applications and allows us calculate the degree of observability that exists over the state space in the environment. The degree of observability over the state space can act as an input into determining the state inference and action selection algorithms used in Ubicomp systems. In this paper we present the design of our Ubicomp domain model. We show that the proposed model contains information necessary to support Ubicomp application development. The expressiveness of the proposed design has been tested by building a model of an Urban Traffic Control application for Dublin city.
With the proliferation of various kinds of sensor networks, we will see large amounts of heterogeneous data. They have different characteristics such as data content, formats, modality and quality. Existing research h...
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ISBN:
(纸本)9783540730897
With the proliferation of various kinds of sensor networks, we will see large amounts of heterogeneous data. They have different characteristics such as data content, formats, modality and quality. Existing research has largely focused on issues related to individual sensor networks;how to make use of diverse data beyond the individual network level is largely unaddressed. In this paper, we propose a semantics-based approach for this problem and describe a system that constructs applications that utilize many sources of data simultaneously. We propose models to formally describe the semantics of data sources, and processing modules that perform various kinds of operations on data. Based on such formal semantics, our system composes data sources and processing modules together in response to users' queries. The semantics provides a common ground such that data sources and processing modules from various parties can be shared and reused among applications. We describe our system architecture, illustrate application deployment, and share our experiences in the semantic approach.
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