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

The use of mobility has been shown to be beneficial in wireless ad hoc and sensor networks, for improving communication performance and other functionality. This paper discusses the communication throughput, goodput and delay considerations when a set of mobile nodes is used as relays to transfer data among multiple static nodes. While previous work has considered randomly mobile nodes, we consider controlled mobile agents. Randomly mobile agents are not available in many network scenarios, such as embedded sensor network deployments, and the use of controllably mobile agents has been considered for such networks. We derive results for the worst case delay, throughput and goodput with controllably mobile relays. Our analysis indicates that this scenario differs fundamentally from the random mobility case. This scenario could, however, be used in defense applications for better communications yield. Further, our results are guaranteed to be achieved in a particular topology, as opposed to previous results which are probabilistic for a particular deployment. We also discuss practical algorithms that can be used to control the routes of mobile agents.

/pdf/goodput-and-delay-in-networks-with-controlled-mobility-1utg28c6d0.pdf

Goodput and Delay in Networks with Controlled Mobility

Magnetic stripe-based transaction enabled mobile communication device embodiments are presented which generally involve a mobile communication device which has been configured to perform transactions that heretofore were completed using a magnetic stripe found on magnetic-stripe cards. In one general embodiment, a mobile communication device generates magnetic stripe data which is used to perform a magnetic stripe-based transaction. To this end, the mobile communication device includes a magnetic stripe device and a computing device. The computing device stores the magnetic stripe data, and the magnetic stripe device is employed to transfer the stored magnetic stripe information so that it can be used to conduct transactions as if a traditional magnetic stripe card were being used.

Magnetic stripe-based transactions using mobile communication devices

Various technologies described herein pertain to detection of an opportune time period to deliver a notification. Responsive to receipt of the notification (e.g., at a user device), analysis of an attention state of a user can be initialized. Further, the opportune time period to deliver the notification can be detected based on the analysis of the attention state of the user. The opportune time period can be during a breakpoint or an influential context. The breakpoint is when the user has switched between tasks and lacks engagement with the tasks. The influential context is a particular context in which the user is available to attend to the notification. Moreover, the notification can be delivered during the opportune time period.

User interruptibility aware notifications

Peak power management of datacenters has tremendous cost implications. While numerous mechanisms have been proposed to cap power consumption, real datacenter power consumption data is scarce. To address this gap, we collect power demands at multiple spatial and fine-grained temporal resolutions from the load of geo-distributed datacenters of Microsoft over 6 months. We conduct aggregate analysis of this data, to study its statistical properties. With workload characterization a key ingredient for systems design and evaluation, we note the importance of better abstractions for capturing power demands, in the form of peaks and valleys. We identify and characterize attributes for peaks and valleys, and important correlations across these attributes that can influence the choice and effectiveness of different power capping techniques. With the wide scope of exploitability of such characteristics for power provisioning and optimizations, we illustrate its benefits with two specific case studies.

/pdf/ace-abstracting-characterizing-and-exploiting-peaks-and-53fkh06ih2.pdf

ACE: abstracting, characterizing and exploiting peaks and valleys in datacenter power consumption

Embodiments include processes, systems, and devices for developing a virtual sensor. The virtual sensor includes one or more inference models. A decision engine utilizes an inference model associated with a mobile device to determine another inference model that is configured to accept physical sensor data from another mobile device. In this way, the virtual sensor can be developed for use with many mobile devices using initial inference models developed for a small number of mobile devices or a single mobile device. Embodiments also include methods to select mobile devices from which to request physical sensor data for virtual sensor input. Embodiments also include architectures that provide a library of virtual sensors.

Aman Kansal

Papers

Goodput and Delay in Networks with Controlled Mobility

Magnetic stripe-based transactions using mobile communication devices

User interruptibility aware notifications

ACE: abstracting, characterizing and exploiting peaks and valleys in datacenter power consumption

Virtual sensor development