NDLI: Layered fault management scheme for end-to-end transmission in internet of things

Content Provider	IEEE Xplore Digital Library
Author	Li Xi Ji Hong Li Yi
Copyright Year	2011
Description	Author affiliation: Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, China (Li Xi; Ji Hong; Li Yi)
Abstract	Internet of things (IoT) network makes the interaction between people and things more active and provides the connection among different existing networks. To ensure the reliability of end-to-end transmission through the hierarchical networks, fault management is of great importance. Current relative fault detection algorithms are designed for specified network, not suited to this complex communication environment. In this paper, we propose a layered fault management scheme for IoT with uniform observing points setting around. In order to distinguish between the real fault and false alarm, fuzzy cognitive maps theory is introduced to set up the monitoring model. By adjusting the weighting rules in the model, different observing points may realize flexible judgment of the link failure risk in their authorities. After locating the fault roots, original recovery method for individual networks may be used to rescue the broken transmission. The distributed working mode makes the proposed scheme more efficient and strong. This design may both realize quick fault discovery and use the existing implementation to the maximum extent. Simulation results show the effectiveness of the proposed scheme.
Starting Page	1021
Ending Page	1025
File Size	259647
Page Count	5
File Format	PDF
ISBN	9781457701009
e-ISBN	9781457701016
DOI	10.1109/ChinaCom.2011.6158306
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis fault management fuzzy cognitive maps Fault detection internet of things Fuzzy cognitive maps Fault location Internet Monitoring Delay
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Layered Fault Management Scheme for End-to-end Transmission in Internet of Things

A fuzzy-based algorithm to remove clock skew and reset from one-way delay measurement [Internet end-to-end performance measurement]

An adaptive fault location method for smart distribution and transmission grids

Detection of Fault Location in Transmission Line Using Internet of Things (IOT)

Application of Fault Tree Analysis and Fuzzy Neural Networks to Fault Diagnosis in the Internet of Things (IoT) for Aquaculture

A Quick-Response Real-Time Stepping Stone Detection Scheme

Evaluation of waste management systems using fuzzy cognitive maps and optimization

Two-end fault location on long transmission lines with in-line shunt reactors

Risk Analysis Using Extended Fuzzy Cognitive Maps

Layered fault management scheme for end-to-end transmission in internet of things

Similar Documents

Layered Fault Management Scheme for End-to-end Transmission in Internet of Things

A fuzzy-based algorithm to remove clock skew and reset from one-way delay measurement [Internet end-to-end performance measurement]

An adaptive fault location method for smart distribution and transmission grids

Detection of Fault Location in Transmission Line Using Internet of Things (IOT)

Application of Fault Tree Analysis and Fuzzy Neural Networks to Fault Diagnosis in the Internet of Things (IoT) for Aquaculture

A Quick-Response Real-Time Stepping Stone Detection Scheme

Evaluation of waste management systems using fuzzy cognitive maps and optimization

Two-end fault location on long transmission lines with in-line shunt reactors

Risk Analysis Using Extended Fuzzy Cognitive Maps

Layered fault management scheme for end-to-end transmission in internet of things