http://www.eecs.ucf.edu/~dcm/Teaching/COT4810-Spring2011/Literature/SensorNetworksSurvey.pdf

Wireless sensor networks: a survey

https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/WSNSurvey2.pdf

Wireless sensor network survey

Cloud computing has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is attractive to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the fact that cloud computing offers huge opportunities to the IT industry, the development of cloud computing technology is currently at its infancy, with many issues still to be addressed. In this paper, we present a survey of cloud computing, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges. The aim of this paper is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this increasingly important area.

/pdf/cloud-computing-state-of-the-art-and-research-challenges-49ws7tdgj3.pdf

Cloud computing: state-of-the-art and research challenges

The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things.

/pdf/internet-of-things-vision-applications-and-research-4xfstaiv80.pdf

Internet of things: Vision, applications and research challenges

In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.

/pdf/energy-conservation-in-wireless-sensor-networks-a-survey-1bl7d2obnm.pdf

Energy conservation in wireless sensor networks: A survey

Significant opportunities for power optimization exist at application design stage and are not yet fully exploited by system and application designers. We describe the challenges developers face in optimizing software for energy efficiency by exploiting application-level knowledge. To address these challenges, we propose the development of automated tools that profile the energy usage of various resource components used by an application and guide the design choices accordingly. We use a preliminary version of a tool we have developed to demonstrate how automated energy profiling helps a developer choose between alternative designs in the energy-performance trade-off space.

/pdf/fine-grained-energy-profiling-for-power-aware-application-4uqn00cupm.pdf

Fine-grained energy profiling for power-aware application design

Monitoring of environmental phenomena with embedded networked sensing confronts the challenges of both unpredictable variability in the spatial distribution of phenomena, coupled with demands for a high spatial sampling rate in three dimensions. For example, low distortion mapping of critical solar radiation properties in forest environments may require two-dimensional spatial sampling rates of greater than 10 samples/m² over transects exceeding 1000 m². Clearly, adequate sampling coverage of such a transect requires an impractically large number of sensing nodes. This paper describes a new approach where the deployment of a combination of autonomous-articulated and static sensor nodes enables sufficient spatiotemporal sampling density over large transects to meet a general set of environmental mapping demands. To achieve this we have developed an embedded networked sensor architecture that merges sensing and articulation with adaptive algorithms that are responsive to both variability in environmental phenomena discovered by the mobile sensors and to discrete events discovered by static sensors. We begin by describing the class of important driving applications, the statistical foundations for this new approach, and task allocation. We then describe our experimental implementation of adaptive, event aware, exploration algorithms, which exploit our wireless, articulated sensors operating with deterministic motion over large areas. Results of experimental measurements and the relationship among sampling methods, event arrival rate, and sampling performance are presented.

Call and Response: Experiments in Sampling the Environment

Image text enhancement techniques are described. In an implementation, graphically represented text included in an original image is converted into process capable text. The process capable text may be used to generate a text image which may replace the original text to enhance the image. In further implementations the process capable text may be translated from a first language to a second language for inclusion in the enhanced image.

Image text replacement

Monitoring of environmental phenomena with embedded networked sensing confronts the challenges of both unpredictable variability in the spatial distribution of phenomena, coupled with demands for a high spatial sampling rate in three dimensions. For example, low distortion mapping of critical solar radiation properties in forest environments may require two-dimensional spatial sampling rates of greater than 10 samples/m2 over transects exceeding 1000 m2. Clearly, adequate sampling coverage of such a transect requires an impractically large number of sensing nodes. This paper describes a new approach where the deployment of a combination of autonomous-articulated and static sensor nodes enables sufficient spatiotemporal sampling densityo ver large transects to meet a general set of environmental mapping demands.To achieve this we have developed an embedded networked sensor architecture that merges sensing and articulation with adaptive algorithms that are responsive to both variabilityin environmental phenomena discovered bythe mobile sensors and to discrete events discovered byst atic sensors. We begin byde scribing the class of important driving applications, the statistical foundations for this new approach, and task allocation. We then describe our experimental implementation of adaptive, event aware, exploration algorithms, which exploit our wireless, articulated sensors operating with deterministic motion over large areas. Results of experimental measurements and the relationship among sampling methods, event arrival rate, and sampling performance are presented.

/pdf/call-and-response-experiments-in-sampling-the-environment-45rsev81eb.pdf

Call and response: experiments in sampling the environment

An implementation of automated location estimation using image analysis is described. In this implementation, an image of a place is obtained and matched with previously stored images. The matching may be achieved by employing methods based on key feature extraction algorithm, color histogram analysis, pattern matching or other image comparison techniques. Upon determining a match, the location information associated with the matched previously stored images provides the location. The location information may be in the form of location tags or location keywords and the location information may be used by the user or other applications for the purposes of location determination. The above technique also allows for the user to enter location information to improve accuracy. The location information may also be assigned to the previously stored images residing in local and remote databases for users and applications to automatically assign information or keywords to images.

Aman Kansal

Papers

Fine-grained energy profiling for power-aware application design

Call and Response: Experiments in Sampling the Environment

Image text replacement

Call and response: experiments in sampling the environment

Automated Location Estimation Using Image Analysis