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RESOURCES WITH PRE - KNOWN INFORMATION Students : Avi Shahimov, - PowerPoint PPT Presentation

D YNAMICALLY REALLOCATING RESOURCES WITH PRE - KNOWN INFORMATION Students : Avi Shahimov, Ariel Slonim , Nave Ariel , Yuri Gabaev , Yuval Kovler, Dima Kupershmidt Mentor: Segev Cohen. Supervisor: Eli Itin Hanoch Sapoznikov Month Year


  1. D YNAMICALLY REALLOCATING RESOURCES WITH PRE - KNOWN INFORMATION Students : Avi Shahimov, Ariel Slonim , Nave Ariel , Yuri Gabaev , Yuval Kovler, Dima Kupershmidt Mentor: Segev Cohen. Supervisor: Eli Itin Hanoch Sapoznikov Month Year Lead of Worldwide Academic Relations 30 Oct 2011

  2. I NTRODUCTION  Analyzing Network topology and recognizing daily/weekly patterns/change in trends – Areas in which there is a need in a bigger 1. bandwidth Areas in which there is a low usage in a bandwidth 2. Rerouting the resources from one to the other.  Our goal is to allocate enough resources to overly high load areas.

  3. C URRENT S ITUATION  There are areas with high load usage in specific periods of time that cause denial of service.  . The current solution may be  Costly  Inefficient  Lacking scalability  Technologically backwards  Non-existent!

  4. O BJECTIVES  Development of a software which will allow to use statistical information to predict areas with high load usage in a specific periods of time and also to recognize change in trends. Input : Network topology with statistical information form the OSS data. Output : Reallocating recourses

  5. F EATURES  Graph Algorithms – weighted edges  Identify and Highlight the over loaded areas  Move network resources.

  6. M ETHODOLOGY  Define xml which describes the network map (input and output file).  Define a DB for the identified patterns.  Learn how to do statistical evolution and then Build a small framework that does that.  Learn how to reallocate network resources  Create an application that uses the framework form before and applies the reallocation of resources

  7. R ISKS  Relocating resources wrongly  Loss of control  Potential for malicious use / abuse  The inability to reallocate resources

  8. M ILESTONES Legal research (Weeks 1-3) Deliverables: all related legal aspects. Statistical analyzing model(Week 4-7) Deliverables: model of how to analyze the statistical information Product design (Weeks 7-10) Deliverable: Architecture of the platform Development (Week 10-15) Deliverables: final product – platform ready for deployment Requirements & Technology Research (Weeks 1-3) –

  9. D EVELOPMENT E NVIRONMENT  Language: Java  IDE: Eclipse  Technologies:  Applet  Graphical network view library  XML

  10. F INAL D ELIVERABLES  Hardware – if needed a mobile network resource  Software  Well documented source code  XML example files of network topology maps  Useful statistical analyzing model  Documentation  Final Presentation  Installation Guide  User Guide.

  11. Thank you…

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