In case of Linear Models, we assume a linear relationship between the mean of the response variable and a set of explanatory variables with inference assuming that response variable has a Normal conditional distribution with constant variance. The Generalized Linear Model permits the distribution for the Response Variable other than the normal and permits modeling of non-linear functions of the mean. Linear models are special case of GLM.

Introduction

Introduction

I have always found TCP congestion control algorithms fascinating, and at the same time, I know very little about them. As an engineer working on the roads, it’s essential to understand the traffic requirement and service levels. Similarly, It’s good to understand the transport behavior riding our networks. Once in a while, I will feel guilty about it and spend time on the topic with the hope of gaining some new insights.

Introduction

Following up on the last post, we will explore IS-IS Area Proxy in this post. The main goal of the IS-IS Area proxy is to provide abstraction by hiding the topology. Looking at our toy topology, we see that we have fabrics connected, and the whole network is a single flat level-2 flooding domain. The edge nodes are connected at the ends, transiting multiple fabrics, and view all the nodes in the topology.

Introduction

In recent years, a lot of work has been done to scale IGPs for dense topologies, making IGPs again an interesting area. In this blog post, we will look at IS-IS Flooding and how we can measure the flooding rate, and in the future post explore Dynamic Flooding and Area Proxy.