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103
Towards realtime information processing of sensor network data using computationally efficient multi-output gaussian processes
, 2008
"... In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information pro ..."
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Cited by 43 (17 self)
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In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England. 1
Wireless sensor networks in permafrost research - concept, requirements, implementation and challenges
- Proc. 9th Int’l Conf. on Permafrost (NICOP 2008
, 2008
"... In a joint project of computer- and geo-scientists, wireless sensor networks (WSNs) are customized for permafrost monitoring in alpine areas. In this paper, we discuss requirements for a rugged setup of such a network that is adapted to operation in a difficult environment. The experiences with a fi ..."
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Cited by 20 (13 self)
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In a joint project of computer- and geo-scientists, wireless sensor networks (WSNs) are customized for permafrost monitoring in alpine areas. In this paper, we discuss requirements for a rugged setup of such a network that is adapted to operation in a difficult environment. The experiences with a first deployment at Jungfraujoch (Switzerland) show that, beside hardware modifications of existing WSN platforms, special emphasis should be given to the development of robust synchronization and low-power data routing algorithms. This results from the fact that standard software tools are not capable in dealing with the high-temperature fluctuations found in high-mountains without compromising the power consumption and the network topology. Enhancements resulted in a second deployment at Matterhorn (Switzerland), from where we expect results in the near future. Once the technology of WSNs is a science-grade instrument, it will be a powerful tool to gather spatial permafrost data in near real-time.
SNEE: a query processor for wireless sensor networks
- DISTRIB PARALLEL DATABASES (2011 ) 29 : 31–85
, 2011
"... A wireless sensor network (WSN) can be construed as an intelligent, largescale device for observing and measuring properties of the physical world. In recent years, the database research community has championed the view that if we construe a WSN as a database (i.e., if a significant aspect of its ..."
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Cited by 15 (8 self)
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A wireless sensor network (WSN) can be construed as an intelligent, largescale device for observing and measuring properties of the physical world. In recent years, the database research community has championed the view that if we construe a WSN as a database (i.e., if a significant aspect of its intelligent behavior is that it can execute declaratively-expressed queries), then one can achieve a significant reduction in the cost of engineering the software that implements a data collection program for the WSN while still achieving, through query optimization, very favorable cost:benefit ratios. This paper describes a query processing framework for WSNs that meets many desiderata associated with the view of WSN as databases. The framework is presented in the form of compiler/optimizer, called SNEE, for a continuous declarative query language over sensed data streams, called SNEEql. SNEEql can be shown to meet the expressiveness requirements of a large class of applications. SNEE can be shown to generate effective and efficient query evaluation plans. More specifically, the paper describes the following contributions: (1) a user-level syntax and physical
Clustering Algorithms for Heterogeneous Wireless Sensor Network: A Survey
- International Journal of Applied Engineering Research
"... Potential use of wireless sensor networks (WSNs) can be seen in various fields like disaster management, battle field surveillance and border security surveillance since last few years. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomousl ..."
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Cited by 12 (0 self)
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Potential use of wireless sensor networks (WSNs) can be seen in various fields like disaster management, battle field surveillance and border security surveillance since last few years. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Sensor nodes are considered to be homogeneous since the researches in the field of WSNs have been evolved, but some nodes may be of different energy to prolong the lifetime of a WSN and its reliability. In this paper, we study the impact of heterogeneity of nodes to the performance of WSNs. This paper surveys different clustering algorithms for heterogeneous WSNs by classifying algorithms depending upon various clustering attributes.
Article Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing
, 2009
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Information-Acquisition-as-a-Service for Cyber-Physical Cloud Computing ∗
"... Data center cloud computing distinguishes computational services such as database transactions and data storage from computational resources such as server farms and disk arrays. Cloud computing enables a software-as-a-service business model where clients may only pay for the service they really nee ..."
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Cited by 11 (5 self)
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Data center cloud computing distinguishes computational services such as database transactions and data storage from computational resources such as server farms and disk arrays. Cloud computing enables a software-as-a-service business model where clients may only pay for the service they really need and providers may fully utilize the resources they actually have. The key enabling technology for cloud computing is virtualization. Recent developments, including our own work on virtualization technology for embedded systems, show that service-oriented computing through virtualization may also have tremendous potential on mobile sensor networks where the emphasis is on information acquisition rather than computation and storage. We propose to study the notion of information-acquisitionas-a-service of mobile sensor networks, instead of server farms, for cyber-physical cloud computing. In particular, we discuss the potential capabilities and design challenges of software abstractions and systems infrastructure for performing information acquisition missions using virtualized versions of aerial vehicles deployed on a fleet of high-performance model helicopters. 1
An Effective Coreset Compression Algorithm for Large Scale Sensor Networks
"... The wide availability of networked sensors such as GPS and cameras is enabling the creation of sensor networks that generate huge amounts of data. For example, vehicular sensor networks where in-car GPS sensor probes are used to model and monitor traffic can generate on the order of gigabytes of dat ..."
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Cited by 8 (1 self)
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The wide availability of networked sensors such as GPS and cameras is enabling the creation of sensor networks that generate huge amounts of data. For example, vehicular sensor networks where in-car GPS sensor probes are used to model and monitor traffic can generate on the order of gigabytes of data in real time. How can we compress streaming highfrequency data from distributed sensors? In this paper we construct coresets for streaming motion. The coreset of a data set is a small set which approximately represents the original data. Running queries or fitting models on the coreset will yield similar results when applied to the original data set. We present an algorithm for computing a small coreset of a large sensor data set. Surprisingly, the size of the coreset is independent of the size of the original data set. Combining map-and-reduce techniques with our coreset yields a system capable of compressing in parallel a stream of O(n) points using space and update time that is only O(log n). We provide experimental results and compare the algorithm to the popular Douglas-Peucker heuristic for compressing GPS data.
Mechanism design for the truthful elicitation of costly probabilistic estimates in distributed information systems
- Artif. Intell
"... This paper reports on the design of a novel two-stage mechanism, based on strictly proper scoring rules, that allows a centre to acquire a costly forecast of a future event (such as a meteorological phenomenon) or a probabilistic estimate of a specific parameter (such as the quality of an expected s ..."
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Cited by 8 (2 self)
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This paper reports on the design of a novel two-stage mechanism, based on strictly proper scoring rules, that allows a centre to acquire a costly forecast of a future event (such as a meteorological phenomenon) or a probabilistic estimate of a specific parameter (such as the quality of an expected service), with a speci-fied minimum precision, from one or more agents. In the first stage, the centre elicits the agents ’ true costs and identifies the agent that can provide an estimate of the specified precision at the lowest cost. Then, in the second stage, the centre uses an appropriately scaled strictly proper scoring rule to incentivise this agent to generate the estimate with the required precision, and to truthfully report it. In particular, this is the first mechanism that can be applied to settings in which the centre has no knowledge about the actual costs involved in the generation an agents ’ estimates and also has no external means of evaluating the quality and accuracy of the estimates it receives. En route to this mechanism, we first consider a setting in which any single agent can provide an estimate of the required precision, and the centre can evaluate this estimate by comparing it with the outcome which is observed at a later stage. This mechanism is then extended, so that it can be applied in a setting where the agents ’ different capabilities are reflected in the maximum precision of the estimates that they can provide, potentially requiring the centre to select mul-
Development of a dynamic web mapping service for vegetation productivity using earth observation and in situ sensors in a sensor web based approach. Sensors 9
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A Semantically Enabled Service Architecture for Mashups over Streaming and Stored Data
"... Abstract. Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g. flood emergency response. However, in order to interpret the readings from the sensors, the d ..."
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Cited by 8 (2 self)
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Abstract. Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g. flood emergency response. However, in order to interpret the readings from the sensors, the data needs to be put in context through correlation with other sensor readings, sensor data histories, and stored data, as well as juxtaposing with maps and forecast models. In this paper we use a flood emergency response planning application to identify requirements for a semantic sensor web. We propose a generic service architecture to satisfy the requirements that uses semantic annotations to support well-informed interactions between the services. We present the SemSor-Grid4Env realisation of the architecture and illustrate its capabilities in the context of the example application.
