Grants and Contributions:

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Title:

On Network Reliability

Agreement Number:

RGPIN

Agreement Value:

$70,000.00

Agreement Date:

May 10, 2017 -

Organization:

Natural Sciences and Engineering Research Council of Canada

Location:

Nova Scotia, CA

Reference Number:

GC-2017-Q1-01958

Agreement Type:

Grant

Report Type:

Grants and Contributions

Additional Information:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

Recipient's Legal Name:

Cox, Danielle (Mount Saint Vincent University)

Program:

Discovery Grants Program - Individual

Program Purpose:

In today's technologically advanced world, the study of network reliability is very important. Many different reliability models have been developed to represent a variety of desired network properties. These models fall into one of two categories: coherent or non-coherent reliability systems.

In this proposed research I will investigate specific reliability models from both categories, with the purpose of understanding the properties of general coherent and non-coherent reliability systems. The goals of the proposed research are as follows:

1) To deepen our understanding of the behaviour of the reliability polynomial on [0,1].
2) To analyse the underlying combinatorial structure of reliability systems.
3) To apply the theoretical study of reliability systems to the real world design of networks.

To achieve these goals, I will study specific reliability models by using and expanding on techniques from my previous successful network reliability investigations. I will answer questions regarding the analytic properties and behaviour of the reliability polynomial on [0,1], as well as propose optimal network designs. The anticipated research will advance the knowledge of reliability systems and have direct applications to the design of networks. The introduction of a new non-coherent reliability system, the strongly connected node failure reliability model, will provide new problems to investigate and have applications to directed networks with potential node failures.