Paper Info
Title
A Low Complexity Relaxation for Minimizing Bandwidth Use in IoT Storage Without Newcomers
Abstract
This paper proposes a low-complexity solution for the data protection problem without newcomer nodes in Internet of Things (IoT) scenarios, i.e., when device losses cannot be replaced by new devices. Application scenarios include environmental monitoring, data collection, and industrial automation. Although the optimal solution and optimization framework have been studied in previous work to minimize the network costs and storage capacity requirements, this paper shows that the optimal solution has a high complexity as the number of devices increases. Given the massive number of IoT devices, we propose a relaxation to the cut capacity constraints that (a) guarantees data recoverability, (b) achieves the minimum network use, and (c) reduces the problem’s complexity dramatically. Our numerical results show that the proposed relaxation allows us to change the computational scaling of the problem. More specifically, we show that the time taken to compute the optimal transmission policy with the relaxation for a system with 800 devices is the same as the time it takes the optimal solution to solve the case of 15 devices.
Year
DOI
Venue
2019
10.1109/CCNC.2019.8651819
2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)
Keywords
Field
DocType
Maintenance engineering,Complexity theory,Bandwidth,Data protection,Internet of Things,Linear programming,Conferences
Data collection,Computer science,Computer network,Automation,Bandwidth (signal processing),Linear programming,Data Protection Act 1998,Computational lithography,Environmental monitoring,Maintenance engineering,Distributed computing
Conference
ISSN
ISBN
Citations 
2331-9852
978-1-5386-5553-5
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Xiaobo Zhao111.71
Daniel E. Lucani223642.29
Xiao-Hong Shen33213.95
Haiyan Wang432.10