abstract: Video capture, storage, and distribution in wireless video sensor networks
(WVSNs) critically depends on the resources of the nodes forming the sensor
networks. In the era of big data, Internet of Things (IoT), and distributed
demand and solutions, there is a need for multi-dimensional data to be part of
the Sensor Network data that is easily accessible and consumable by humanity as
well as machinery. Images and video are expected to become as ubiquitous as is
the scalar data in traditional sensor networks. The inception of video-streaming
over the Internet, heralded a relentless research for effective ways of
distributing video in a scalable and cost effective way. There has been novel
implementation attempts across several network layers. Due to the inherent
complications of backward compatibility and need for standardization across
network layers, there has been a refocused attention to address most of the
video distribution over the application layer. As a result, a few video
streaming solutions over the Hypertext Transfer Protocol (HTTP) have been
proposed. Most notable are Apple’s HTTP Live Streaming (HLS) and the Motion
Picture Experts Groups Dynamic Adaptive Streaming over HTTP (MPEG-DASH). These
frameworks, do not address the typical and future WVSN use cases. A highly
flexible Wireless Video Sensor Network Platform and compatible DASH (WVSNP-DASH)
are introduced. The platform's goal is to usher video as a data element that
can be integrated into traditional and non-Internet networks. A low cost,
scalable node is built from the ground up to be fully compatible with the
Internet of Things Machine to Machine (M2M) concept, as well as the ability to
be easily re-targeted to new applications in a short time. Flexi-WVSNP design
includes a multi-radio node, a middle-ware for sensor operation and
communication, a cross platform client facing data retriever/player framework,
scalable security as well as a cohesive but decoupled hardware and software
design. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017
| Identifer | oai:union.ndltd.org:asu.edu/item:44275 |
| Date | January 2017 |
| Contributors | Seema, Adolph (Author), Reisslein, Martin (Advisor), Kitchen, Jennifer (Committee member), Seeling, Patrick (Committee member), Zhang, Yanchao (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 239 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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