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  1. Proceedings of the 2nd Workshop on Experiences in the Design and Implementation of Smart Objects (SmartObjects '16)
  2. Data-oriented abstraction of virtual sensors for energy-aware embedded software systems
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A smart spa: having fun with physical activities
Determining the relative position of vehicles considering bidirectional traffic scenarios in VANETS
Cloud storage for mobile users using pre-positioned storage facilities
Enhancing compressive sensing encryption in constrained devices using chaotic sequences
RECKON: an analytics framework for app developers
DataTweet for user-centric and geo-centric IoT communications
Low-cost, low-power and long-range image sensor for visual surveillance
Abstractions and solutions to support smart-objects in the future internet
LuxLeak: capturing computing activity using smart device ambient light sensors
Data-oriented abstraction of virtual sensors for energy-aware embedded software systems

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Data-oriented abstraction of virtual sensors for energy-aware embedded software systems

Content Provider ACM Digital Library
Author Iannelli, Michael Ravindran, Kaliappa
Abstract We analyze the computing and communications as incorporated in networked objects (IoT): such as sensors, with focus on the performance and QoS aspects (e.g., latency of sensor data delivery to end-user). We advocate the offloading of complex computational tasks from the field-deployed low-capability sensor devices to cloud-based remote machines when feasible. In addition to the improved latency performance, the offloading of complex sensor tasks lowers the energy consumption of sensor devices. A key element of our IoT system architecture is the use of layered sensing techniques to determine the offloading of sensor tasks and the network transfer of sensor data. The computational cycles expended and network data transfer overhead vis-a-vis the energy consumption incurred therein, are factored in the partitioning of sensor tasks. Given the large-dimensionality of sensor input data, our architecture incorporates the accuracy and timeliness of sensor outputs as the controllable application-level quality parameters. The paper describes a case study of Optical Character Recognition to corroborate our approach.
Starting Page 53
Ending Page 58
Page Count 6
File Format PDF EPUB
ISBN 9781450342544
DOI 10.1145/2980147.2980157
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-10-03
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Adaptive sensing Replica voting Distributed control & management Sensor faults & data errors Large-dimensional data Sensor replication systems
Content Type Text
Resource Type Article
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