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Optimized Hexagon-Based Deployment for Large-Scale Ubiquitous Sensor Networks
Date
2018-04-01
Author
Al-Turjman, Fadi
Metadata
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Ubiquitous Sensor Network describes an application platform comprised of intelligently networked sensors deployed over a large area, supporting multiple application scenarios. On one hand, at the user-end, storing and managing the large amount of heterogeneous data generated by the network is a daunting task. On the other hand, at the network-end, ensuring network connectivity and longevity in a dynamically changing network environment, while trying to provide context-aware application data to the end-users are very challenging for the resource constrained sensor network. While cloud computing offers a cost-effective solution for storage of the large volume of data generated by the underlying heterogeneous network, an equally elegant solution does not exist on the network interface to provide application-aware data. In this paper, we propose the use of cognitive nodes (CNs) in the underlying sensor network to provide intelligent information processing and knowledge-based services to the end-users. We identify tools and techniques to implement the cognitive functionality and formulate a strategy for the deployment of CNs in the underlying sensor network to ensure a high probability of successful data reception among communicating nodes. From Matlab simulations, we were able to verify that in a network with randomly deployed sensor nodes, CNs can be strategically deployed at pre-determined positions, to deliver application-aware data that satisfies the end-user's quality of information requirements, even at high application payloads.
Subject Keywords
Internet of things
,
Cognitive nodes
,
Deployment strategy
,
Energy-efficiency
,
Quality of information
URI
https://hdl.handle.net/11511/64271
Journal
JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT
DOI
https://doi.org/10.1007/s10922-017-9415-2
Collections
Engineering, Article
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F. Al-Turjman, “Optimized Hexagon-Based Deployment for Large-Scale Ubiquitous Sensor Networks,”
JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT
, pp. 255–283, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64271.