The Laboratory of Computer Communication and Networking

 

Projects for

 Spring 2011 Semester

Course 236340

        

We will cooperate during the Spring semester with:

Qualcomm:  http://www.qualcomm.com/ 

Amdocs:  http://www.amdocs.com/ 

Telematics and Elbit in CORNET (Israel Consortium for Cognitive radio)

The VideoPoint: http://thevideopoint.com/AboutUs.asp

 

HTTP Live Streaming Prototype   with Qualcomm http://www.qualcomm.com/
 

The video delivery over the Web is one of the major media delivery methods nowadays. To cooperate with the user needs, various standardization organizations and companies are investigating in better ways of video delivery over IP networks. The examples of this trend of enhancement are development in codec compression, increase in network bandwidth, proposals of efficient switching mechanisms of different video quality schemes and more.

In this project the students will be asked to design and implement the client side of the new advanced video delivery method denoted HTTP Live Streaming. In this method the media is stored on the server side as a series of files instead of one file in the usual case. If in the usual case the server side stores the same content encoded in different bitrates for flows with different bandwidth limitation, in the case of HTTP Live Streaming, the server stores a different set of small files for each of the bandwidth bounds. The latter division into small files allows the client side (during the playback) to select a different file set visually seamlessly according to the currently experienced network bandwidth.

 

Objectives:

+ Setup the server side of the HTTP Live Streaming

+ Design and Develop HTTP Live Streaming Application

+ Demonstrate the developed application playing non-encrypted Live Streaming audio/video content

+ Development platform: Linux

+ Programming Language: C++

 

Additional Information:

+ http://en.wikipedia.org/wiki/HTTP_Live_Streaming

+ http://tools.ietf.org/html/draft-pantos-http-live-streaming-04

+ http://developer.apple.com/resources/http-streaming/

 

GEO-IP Database Correlation tool

 

Background:

 

Geo location capabilities are key point elements in today building block of creating user based applications and services. Knowing user geo location in an accurate real time mode is essential for building user dedicated personal offering such as Ads and services.

 

IP address can provide such identification however its accuracy is not guarantied as GPS.

There are several engines that provides geo location based on IP addresses , some of them are paid and some them are free. These engines are based in general on ISPs generosity. The cost of these engines varies from free lite packages to paid hundreds USD per month per database.

 

We assume that correlating between multiple free database may give better results. Solving collision between database by using on demand services and operating networking protocols such as SNMP or trace routing might give additional information which will solve the specific collision.. 

 

Project description:

 

 Building an automatic tool that crawls and correlate free databases from the Internet.

The tool create single database where its input are which value are agreed on all sources and where is the collision.

The collision will be examined by using additional on line queries such as trace routing the destination , doing SNMP queries of multiple MIB o the path to the end point and additional networking ideas provided by the team.

 

 web site sources ( will be happy that more are used ):

 

http://software77.net/geo-ip/

http://www.maxmind.com/

http://www.geodatasource.com/

http://www.ouova.com/geolocation

http://www.ip2location.com/

http://www.hostip.info/

http://www.ipchecking.com/

 

 

 

FTTH spatial placement optimization algorithm with Amdocs http://www.amdocs.com/

 

Project description:

 

FTTH: Fiber to the Home, a form of broadband internet connectivity based on GPON (gigabit passive optical network)  technology.

The FTTH technology connects a OLT (optical line terminator) in a CO(central office) to ONU (optical network unit) in households, using an optical fiber cable.

Cables are passed on the ground through a grid of ducts which are pipes characterized by a certain capacity (number of cables), length and connectivity with other ducts.

One fiber starting in an OLT is split several times, using passive splitters, 1:4, 1:16, etc. up to 32 or 64 households, reducing bandwidth, but providing service to more houses.

The problem to resolve is the optimal placement of splitters on a given geographical area, minimize the use of ducts, keeping cable length constraints, according to a splitting scheme.

 

The application needs to:

1.      Represent the duct grid (a directional graph) with constraints such as fiber capacity, length, and spatial coordinates.

2.      Represent the CO and households in spatial coordinates

3.      Optimize the placement of splitters according to constraints of total fiber length, splitting scheme and groups of houses (number of houses), minimizing the number of cables in the OLT.

4.      Optional: the results should be visualized using a standard geographical map, e.g. Google Map or Google Earth.

 

Technical Expertise required:

Java, Optimization algorithms, graph theory, basic telecommunications.

 

FTTH Network: splitting schema

 

 

 

Routing Improvements in Cognitive Radio Networks   

 

Cognitive radio  - a communication approach where the transmitters and the receivers change their  transmission or reception parameters in accordance to various decisions such as radio frequency spectrum, user behavior and network state.

This project will check  multi-hop routing and resource allocation in distributed cognitive radio networks. Specifically we will focus in protocols and algorithms that determine channel allocations for groups in distributed cognitive networks. We will consider two types of communication range: 1) communication inside the group and 2) communication between groups. We will look for efficient ways to find neighbours (both from the same group and from other groups), using an application feedback to the cognitive engine.

We assume that all the network nodes are routers. On the first stage, the cognitive engine on each node will make a local channel decision in accordance to frequency  disturbances scheme.

Then, for each end to end application needs,  an algorithm that decides which route to take and if to change the cognitive engine decision will be operated.

You will check and compare two proposed algorithms and will have to add one of your own.