Paper Info
Title
A Neural-Network-Based Realization Of In-Network Computation For The Internet Of Things
Abstract
Ultra-dense Internet of Things (IoT) networks and machine type communications herald an enormous opportunity for new computing paradigms and are serving as a catalyst for profound change in the evolution of the Internet. We explore leveraging the communication within IoT to serve data processing by appropriately shaping the aggregate behavior of a network to parallel more traditional computation methods. This paper presents an element of this vision, whereby we map the operations of an artificial neural network onto the communication of an IoT network for simultaneous data processing and transfer. That is, we provide a framework to treat a network holistically as an artificial neural network, rather than placing neural networks within the network. The operation of components of a neural network, neurons and connections between neurons, are performed by the various elements of the IoT network, i.e., the devices and their connections. The proposed approach reduces the latency in delivering processed information and supports the locality of information inherent to IoT by removing the need for transfer to remote data processing sites.
Year
Venue
Keywords
2017
2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC)
Internet of Things, Artificial Neural Networks, Wireless Sensor Networks
Field
DocType
ISSN
Edge computing,Nervous system network models,Computer science,Network simulation,Computer network,Network architecture,Network topology,Artificial neural network,Intelligent computer network,Distributed computing,The Internet
Conference
1550-3607
Citations 
PageRank 
References 
4
0.38
13
Authors
9
Name
Order
Citations
PageRank
Nicholas J. Kaminski1619.28
Irene Macaluso211922.24
Emanuele Di Pascale3111.93
Avishek Nag4101.24
John Brady540.38
Mark Y. Kelly6100.90
Keith E. Nolan716916.75
Wael Guibène8223.88
Linda E. Doyle930434.70