Measurement and estimation of packet loss characteristics are challenging due to the relatively rare occurrence and typically short duration of packet loss episodes. While active probe tools are commonly used to measure packet loss on end-to-end paths, there has been little analysis of the accuracy of these tools or their impact on the network. The objective of our study is to understand how to measure packet loss episodes accurately with end-to-end probes. We begin by testing the capability of standard Poisson- modulated end-to-end measurements of loss in a controlled laboratory environment using IP routers and commodity end hosts.
Our tests show that loss characteristics reported from such Poisson-modulated probe tools can be quite inaccurate over a range of traffic conditions. Motivated by these observations, we introduce a new algorithm for packet loss measurement that is designed to overcome the deficiencies in standard Poisson-based tools. Specifically, our method entails probe experiments that follow a geometric distribution to 1) enable an explicit trade-off between accuracy and impact on the network, and 2) enable more accurate measurements than standard Poisson probing at the same rate.
We evaluate the capabilities of our methodology experimentally by developing and implementing a prototype tool, called BADABING. The experiments demonstrate the trade-offs between impact on the network and measurement accuracy. We show that BADABING reports loss characteristics far more accurately than traditional loss measurement tools.
In an Existing System, they analyze the usefulness of Poisson Arrivals See Time Averages in the networking context. Of particular relevance to our work is Paxsonís recommendation and use of Poisson- modulated active probe streams to reduce bias in delay and loss measurements.
Several studies include the use of loss measurements to estimate network properties such as bottleneck buffer size and cross traffic intensity, which is not accurate. Network tomography based on using both multicast and unicast probes has also been demonstrated to be in-effective (in some cases) for inferring loss rates on internal links on end-to-end paths.
The purpose of our study was to understand how to measure end-to-end packet loss characteristics accurately with probes and in a way that enables us to specify the impact on the bottleneck queue.
The goal of our study is to understand how to accurately measure loss characteristics on end-to-end paths with probes.
Specifically, our method entails probe experiments that follow a geometric distribution to 1) enable an explicit trade-off between accuracy and impact on the network, and 2) enable more accurate measurements than standard Poisson probing at the same rate.
Our study consists of three parts: (i) empirical evaluation of the currently prevailing approach, (ii) development of estimation techniques that are based on novel experimental design, novel probing techniques, and simple validation tests, and (iii) empirical evaluation of this new methodology.
- Packet Separation:
In this module we have to separate the input data into packets. These packets are then sent to the Queue.
- Designing the Queue:
The Queue is designed in order to create the packet loss. The queue receives the packets from the Sender, creates the packet loss and then sends the remaining packets to the Receiver.
- Packet Receiver:
The Packet Receiver is used to receive the packets from the Queue after the packet loss. Then the receiver displays the received packets from the Queue.
- User Interface Design:
In this module we design the user interface for Sender, Queue, Receiver and Result displaying window. These windows are designed in order to display all the processes in this project.
- Packet Loss Calculation:
The calculations to find the packet loss are done in this module. Thus we are developing the tool to find the packet loss.