SlideShare ist ein Scribd-Unternehmen logo
1 von 32
OLPC Mesh network improving



                 Arina Rudakova
  (Saint-Petersburg Elelectrotechnical University «LETI»)



              3rd FRUCT seminar


                  Saint-Petersburg
                   23 May 2008
Agenda
 Introduction
 Problem definition
 Domain analysis
 Solution
 Project timeline
I. Introduction
One Laptop Per Child
          
              Home: http://laptop.org


          
              The mission of the One Laptop
              per Child association is to
              develop a low-cost laptop—the
              "XO Laptop"— to revolutionize
              how we educate the world's
              children. Goal is to provide
              children around the world with
              new opportunities to explore,
              experiment, and express
              themselves.
XO laptops hardware

    Dimensions: 242mm × 228mm × 32mm

 CPU x86-compatible processor AMD Geode LX-700 433 Mhz, 64KB each L1 I and D
cache; at least 128KB L2 cache

    DRAM memory: 256 MiB dynamic RAM

    BIOS: 1024KiB SPI-interface flash ROM

    Mass storage: 1024 MiB SLC NAND flash, high-speed flash controller

    Display: Liquid-crystal display: 7.5” dual-mode TFT display

    Keyboard: 80+ keys, 1.0mm stroke; sealed rubber-membrane key-switch assembly

    Gamepad: Two sets of four-direction cursor-control keys

    Touchpad: Dual capacitance/resistive touchpad; supports written-input mode

    Audio: AC’97 compatible audio subsystem

    Integrated color video camera: 640 x 480 resolution at 30 FPS

 Wireless Networking: Integrated 802.11b/g (2.4GHz) interface; 802.11s (Mesh)
networking supported; dual adjustable, rotating antennas support diversity reception;
capable of mesh operation when CPU is powered down;
XO laptops software

    Operating system: Linux Kernel: Linux 2.6.22; Fedora 7 base environment.

    User environment: Sugar GUI, written in Python, on top of the X Window and the Matchbox WM

    Programming environments (main):

        −   Python (Version 2.5);
        −   JavaScript;
        −   Csound, music programming language;
        −   Etoys, an implementation of Squeak using Smalltalk, an object-based programming
            language;
        −   Turtle Art, a graphical programming environment;
        −   Adobe's Flash Player, Java, Gnash

    Libraries

        −       Mozilla Gecko/Xulrunner (the Firefox web engine);
        −       GUI toolkit (GTK+) (Gnome);
        −       Matchbox window manager;
        −       X Window System X.org Foundation;
        −       Multimedia framework: GStreamer and RealNetworks;
        −       Gettext, the GNU internationalization library
Neighborhood:
Collaboration interface
                The Neighbourhood view
                   displays all the connected
                   XO laptops within a child’s
                   community, and what
                   activities they are sharing.


                Each child is represented by a
                   different colour


                If there is a shared document
                   or activity being
                   collaborated on by a
                   number of children, it will
                   show up within this view.
XO Mesh goals

    Ability to act as a mesh point when laptop's main CPU is off.

    Support for asymmetric links/paths.

    Incremental releases—mesh networking is available immediately
    on XO; Upgrades will continue to improve functionality and
    adherence with standards.

    Simultaneously acts as a mesh point and an infrastructure node.

    Standards Compliance: follow 802.11s draft when possible.
II. Problem definition
Mesh network types

    Infrastructure wireless mesh networks: Mesh
    routers form an infrastructure for clients.

    Client wireless mesh networks: Client nodes
    constitute the actual network to perform routing
    and configuration functionalities.

    Hybrid wireless mesh networks: Mesh clients can
    perform mesh functions with other mesh clients as
    well as accessing the network
Distinguishing features

    dynamics

    structure
Routing mechanism in mesh

    Redundante links usage
    −   Fault tolerance
    −   Load sharing

    Traffic analysis

    Network diversity

    Route aggregation
Routing overhead reasons

    Nodes number influence on the amount
    of control traffic

    Network changes dynamics influence on
    the amount of control traffic

    Route length influence on the amount of
    control traffic
Project Goals

    Reducing Routing overhead

    OLPC implementation
III. Domain analysis
Ad-hoc Routing types

    Pro-active or Table-driven

    Reactive Routing or On-demand

    Flow Oriented

    Adaptive Routing or Situation-Aware

    Hybrid (Pro-Active and Reactive)
Industrial and open source
          implementations

    AWDS (Ad-hoc Wireless Distribution Service) http://awds.berlios.de/

    DSDV (Highly Dynamic Destination-Sequenced Distance Vector routing
    protocol) – based on Bellman-Ford Routing Protocol

    AODV (Ad-hoc On-demand Distance Vector)

    Mobile Ad-hoc On-Demand Data Delivery Protocol

    MPRDV (Multipoint Relay Distance Vector protocol)

    SSR (Signal Stability Routing protocol)

    PLBR (Preferred link based routing)

    TORA (Temporally-Ordered Routing Algorithm routing protocol)

    HRPLS (Hybrid Routing Protocol for Large Scale Mobile Ad-Hoc Networks
    with Mobile Backbones)

    HSLS (Hazy Sighted Link State routing protocol)

    ZRP (Zone Routing Protocol)
IV. Solution
Solution components

    Routing area restriction

    Dynamic selection of optimization radius

    External definition of routing overhead
Routing overhead chart

    m — tree arity

    n — nodes number

    R — dynamics
Possible reasons of
      routing overhead increase

    Number of nodes increase

    Network dynamics increase

    Network radius increase

    Using aggressive updating strategy
Routing area restriction
For effective routing area definition we should
 introduce some definitions.

G(t)=<V,E>, where V – set of nodes, E – arches
G(t) describes network topology
d(vi,vj) – distance between vi and vj
vi: Ri>0, G (vi , Ri ) ⊂ G (t ), d (vi , v j ) ≤ Ri
Choose Ri with regard to time needed for collection
 of information about G(vi,Ri)
G(vi,Ri) - effective routing area for vi, G (vi , Ri ) ≡ R(vi )
External and internal
             routing records

    External routing
    records (only in
    edge nodes)

    Internal routing
    records (always
    true)
Routing optimization area

    Local optimization

    Global optimization

    Optimization in restricted area
Local sample

    Information collection – 1 hop

    Route defining – 1 hop

    «Trust» zone – 1 hop

    Control traffic is minimum
Global sample

    Information collection –
    whole net

    Route defining – whole net

    «Trust» zone – whole net

    Control traffic is maximum
Restricted sample

    Information collection is
    restricted with R

    Route defining – within R
    radius

    «Trust» zone – within R
    radius

    Control traffic is restricted
Failure detection
               
                   At first only one
                   router knows
                   about a route
                   failure
               
                   After the
                   message to
                   sender about
                   the
                   impossibility of
                   passing, the
                   whole effective
                   routing area is
                   informed
               
                   The sender gets
                   informed when
                   its timer is over
Routing overhead analysis
V. Project timeline
Global plan
The past

    2007 Autumn, generic task definition, domain investigation

    2008 Winter, getting XO devices, experience XO system
    programming
The future

    2008 Summer, public presentation our of solution ideas
    (conference proceedings or paper)

    2008 Autumn, implement modules for NS2 and simulations

    2008 Winter, contribute some code for XO laptops

    2009 Spring, defence of the master thesises at LETI
Thank you.
Any questions?

Weitere ähnliche Inhalte

Was ist angesagt?

Use of NS-2 to Simulate MANET Routing Algorithms
Use of NS-2 to Simulate MANET Routing AlgorithmsUse of NS-2 to Simulate MANET Routing Algorithms
Use of NS-2 to Simulate MANET Routing AlgorithmsGiancarlo Romeo
 
Mobility, traffic engineering and redundancy using RPL
Mobility, traffic engineering and redundancy using RPLMobility, traffic engineering and redundancy using RPL
Mobility, traffic engineering and redundancy using RPLMaxime Denis
 
Backplane Technology Overview for AdvancedTCA
Backplane Technology Overview for AdvancedTCABackplane Technology Overview for AdvancedTCA
Backplane Technology Overview for AdvancedTCAhuichenphd
 
MARC ONERA Toulouse2012 Altreonic
MARC ONERA Toulouse2012 AltreonicMARC ONERA Toulouse2012 Altreonic
MARC ONERA Toulouse2012 AltreonicEric Verhulst
 
Multicastingand multicast routing protocols
Multicastingand multicast routing protocolsMulticastingand multicast routing protocols
Multicastingand multicast routing protocolsIffat Anjum
 
On-Demand Multicast Routing Protocol
On-Demand Multicast Routing ProtocolOn-Demand Multicast Routing Protocol
On-Demand Multicast Routing ProtocolSenthil Kanth
 
Multicastingand multicast routing protocols
Multicastingand multicast routing protocolsMulticastingand multicast routing protocols
Multicastingand multicast routing protocolsIffat Anjum
 
Internet Of Things: Vision, Prerequisites and OpenSpime
Internet Of Things: Vision, Prerequisites and OpenSpimeInternet Of Things: Vision, Prerequisites and OpenSpime
Internet Of Things: Vision, Prerequisites and OpenSpimeRoberto Ostinelli
 
Stefano Giordano
Stefano GiordanoStefano Giordano
Stefano GiordanoGoWireless
 
Performance analysis of aodv protocol on blackhole attack
Performance analysis of aodv protocol on blackhole attackPerformance analysis of aodv protocol on blackhole attack
Performance analysis of aodv protocol on blackhole attackMehedi
 

Was ist angesagt? (19)

Use of NS-2 to Simulate MANET Routing Algorithms
Use of NS-2 to Simulate MANET Routing AlgorithmsUse of NS-2 to Simulate MANET Routing Algorithms
Use of NS-2 to Simulate MANET Routing Algorithms
 
Mobility, traffic engineering and redundancy using RPL
Mobility, traffic engineering and redundancy using RPLMobility, traffic engineering and redundancy using RPL
Mobility, traffic engineering and redundancy using RPL
 
Backplane Technology Overview for AdvancedTCA
Backplane Technology Overview for AdvancedTCABackplane Technology Overview for AdvancedTCA
Backplane Technology Overview for AdvancedTCA
 
Introduction to Serial RapidIO® (SRIO) by IDT
Introduction to Serial RapidIO® (SRIO) by IDTIntroduction to Serial RapidIO® (SRIO) by IDT
Introduction to Serial RapidIO® (SRIO) by IDT
 
Ipmulticasting
IpmulticastingIpmulticasting
Ipmulticasting
 
MARC ONERA Toulouse2012 Altreonic
MARC ONERA Toulouse2012 AltreonicMARC ONERA Toulouse2012 Altreonic
MARC ONERA Toulouse2012 Altreonic
 
AODV protocol
AODV protocolAODV protocol
AODV protocol
 
Internship end
Internship endInternship end
Internship end
 
Multicastingand multicast routing protocols
Multicastingand multicast routing protocolsMulticastingand multicast routing protocols
Multicastingand multicast routing protocols
 
On-Demand Multicast Routing Protocol
On-Demand Multicast Routing ProtocolOn-Demand Multicast Routing Protocol
On-Demand Multicast Routing Protocol
 
Multicastingand multicast routing protocols
Multicastingand multicast routing protocolsMulticastingand multicast routing protocols
Multicastingand multicast routing protocols
 
Internet Of Things: Vision, Prerequisites and OpenSpime
Internet Of Things: Vision, Prerequisites and OpenSpimeInternet Of Things: Vision, Prerequisites and OpenSpime
Internet Of Things: Vision, Prerequisites and OpenSpime
 
Mpls
MplsMpls
Mpls
 
Multicast
MulticastMulticast
Multicast
 
V25112115
V25112115V25112115
V25112115
 
AODV Protocol
AODV ProtocolAODV Protocol
AODV Protocol
 
Stefano Giordano
Stefano GiordanoStefano Giordano
Stefano Giordano
 
Performance analysis of aodv protocol on blackhole attack
Performance analysis of aodv protocol on blackhole attackPerformance analysis of aodv protocol on blackhole attack
Performance analysis of aodv protocol on blackhole attack
 
Address Interleaving in NoCs
Address Interleaving in NoCsAddress Interleaving in NoCs
Address Interleaving in NoCs
 

Andere mochten auch

N8xx olpc connectivity
N8xx olpc connectivityN8xx olpc connectivity
N8xx olpc connectivityOSLL
 
[MDBCI] Mariadb continuous integration tool
[MDBCI] Mariadb continuous integration tool[MDBCI] Mariadb continuous integration tool
[MDBCI] Mariadb continuous integration toolOSLL
 
Implementation of the new REST API for Open Source LBS-platform Geo2Tag
Implementation of the new REST API for Open Source LBS-platform Geo2TagImplementation of the new REST API for Open Source LBS-platform Geo2Tag
Implementation of the new REST API for Open Source LBS-platform Geo2TagOSLL
 
MOOCs Virtual Lab in Modern Education
MOOCs Virtual Lab in Modern EducationMOOCs Virtual Lab in Modern Education
MOOCs Virtual Lab in Modern EducationOSLL
 
Обзор файловой системы GlusterFS
Обзор файловой системы GlusterFSОбзор файловой системы GlusterFS
Обзор файловой системы GlusterFSOSLL
 
Обзор Btrfs
Обзор BtrfsОбзор Btrfs
Обзор BtrfsOSLL
 
SVG-player plugin for ns2 simulations
SVG-player plugin for ns2 simulationsSVG-player plugin for ns2 simulations
SVG-player plugin for ns2 simulationsOSLL
 
Fruct4 n8xx olpc-connectivity
Fruct4 n8xx olpc-connectivityFruct4 n8xx olpc-connectivity
Fruct4 n8xx olpc-connectivityOSLL
 
E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...
E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...
E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...OSLL
 
Обзор архитектуры [файловой] системы Ceph
Обзор архитектуры [файловой] системы CephОбзор архитектуры [файловой] системы Ceph
Обзор архитектуры [файловой] системы CephOSLL
 
Testing with Selenium
Testing with SeleniumTesting with Selenium
Testing with SeleniumOSLL
 
Работа с геоданными в MongoDb
Работа с геоданными в MongoDbРабота с геоданными в MongoDb
Работа с геоданными в MongoDbOSLL
 
Обзор Linux Control Groups
Обзор Linux Control GroupsОбзор Linux Control Groups
Обзор Linux Control GroupsOSLL
 
Open Source implementation of ZigBee
Open Source implementation of ZigBeeOpen Source implementation of ZigBee
Open Source implementation of ZigBeeOSLL
 
Пространства имен Linux (linux namespaces)
Пространства имен Linux (linux namespaces)Пространства имен Linux (linux namespaces)
Пространства имен Linux (linux namespaces)OSLL
 
Virtual-HSM: Virtualization of Hardware Security Modules in Linux Containers
Virtual-HSM: Virtualization of Hardware Security Modules in Linux ContainersVirtual-HSM: Virtualization of Hardware Security Modules in Linux Containers
Virtual-HSM: Virtualization of Hardware Security Modules in Linux ContainersOSLL
 
Кратчайшее введение в docker по-русски
Кратчайшее введение в docker по-русскиКратчайшее введение в docker по-русски
Кратчайшее введение в docker по-русскиOSLL
 
Linuxvirt seminar-csc-2015
Linuxvirt seminar-csc-2015Linuxvirt seminar-csc-2015
Linuxvirt seminar-csc-2015OSLL
 
Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015
Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015
Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015OSLL
 
Geo2tag LBS platform training at FRUCT12
Geo2tag LBS platform training at FRUCT12Geo2tag LBS platform training at FRUCT12
Geo2tag LBS platform training at FRUCT12OSLL
 

Andere mochten auch (20)

N8xx olpc connectivity
N8xx olpc connectivityN8xx olpc connectivity
N8xx olpc connectivity
 
[MDBCI] Mariadb continuous integration tool
[MDBCI] Mariadb continuous integration tool[MDBCI] Mariadb continuous integration tool
[MDBCI] Mariadb continuous integration tool
 
Implementation of the new REST API for Open Source LBS-platform Geo2Tag
Implementation of the new REST API for Open Source LBS-platform Geo2TagImplementation of the new REST API for Open Source LBS-platform Geo2Tag
Implementation of the new REST API for Open Source LBS-platform Geo2Tag
 
MOOCs Virtual Lab in Modern Education
MOOCs Virtual Lab in Modern EducationMOOCs Virtual Lab in Modern Education
MOOCs Virtual Lab in Modern Education
 
Обзор файловой системы GlusterFS
Обзор файловой системы GlusterFSОбзор файловой системы GlusterFS
Обзор файловой системы GlusterFS
 
Обзор Btrfs
Обзор BtrfsОбзор Btrfs
Обзор Btrfs
 
SVG-player plugin for ns2 simulations
SVG-player plugin for ns2 simulationsSVG-player plugin for ns2 simulations
SVG-player plugin for ns2 simulations
 
Fruct4 n8xx olpc-connectivity
Fruct4 n8xx olpc-connectivityFruct4 n8xx olpc-connectivity
Fruct4 n8xx olpc-connectivity
 
E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...
E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...
E.Kalishenko, K.Krinkin, S.P.Shiva Prakash. Process Mining Approach for Traff...
 
Обзор архитектуры [файловой] системы Ceph
Обзор архитектуры [файловой] системы CephОбзор архитектуры [файловой] системы Ceph
Обзор архитектуры [файловой] системы Ceph
 
Testing with Selenium
Testing with SeleniumTesting with Selenium
Testing with Selenium
 
Работа с геоданными в MongoDb
Работа с геоданными в MongoDbРабота с геоданными в MongoDb
Работа с геоданными в MongoDb
 
Обзор Linux Control Groups
Обзор Linux Control GroupsОбзор Linux Control Groups
Обзор Linux Control Groups
 
Open Source implementation of ZigBee
Open Source implementation of ZigBeeOpen Source implementation of ZigBee
Open Source implementation of ZigBee
 
Пространства имен Linux (linux namespaces)
Пространства имен Linux (linux namespaces)Пространства имен Linux (linux namespaces)
Пространства имен Linux (linux namespaces)
 
Virtual-HSM: Virtualization of Hardware Security Modules in Linux Containers
Virtual-HSM: Virtualization of Hardware Security Modules in Linux ContainersVirtual-HSM: Virtualization of Hardware Security Modules in Linux Containers
Virtual-HSM: Virtualization of Hardware Security Modules in Linux Containers
 
Кратчайшее введение в docker по-русски
Кратчайшее введение в docker по-русскиКратчайшее введение в docker по-русски
Кратчайшее введение в docker по-русски
 
Linuxvirt seminar-csc-2015
Linuxvirt seminar-csc-2015Linuxvirt seminar-csc-2015
Linuxvirt seminar-csc-2015
 
Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015
Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015
Fast Artificial Landmark Detection for indoor mobile robots AIMAVIG'2015
 
Geo2tag LBS platform training at FRUCT12
Geo2tag LBS platform training at FRUCT12Geo2tag LBS platform training at FRUCT12
Geo2tag LBS platform training at FRUCT12
 

Ähnlich wie OLPC Mesh networking improvements

Wireless mesh networkk routing
Wireless mesh networkk routingWireless mesh networkk routing
Wireless mesh networkk routingAbhishek Kona
 
เทคโนโลยีสารสนเทศสำหรับครู
เทคโนโลยีสารสนเทศสำหรับครูเทคโนโลยีสารสนเทศสำหรับครู
เทคโนโลยีสารสนเทศสำหรับครูBeauso English
 
Mba admission in india
Mba admission in indiaMba admission in india
Mba admission in indiaEdhole.com
 
Spring sim 2010-riley
Spring sim 2010-rileySpring sim 2010-riley
Spring sim 2010-rileySopna Sumāto
 
Robot Operating Systems (Ros) Overview &amp; (1)
Robot Operating Systems (Ros) Overview &amp; (1)Robot Operating Systems (Ros) Overview &amp; (1)
Robot Operating Systems (Ros) Overview &amp; (1)Piyush Chand
 
Robot operating systems (ros) overview & (1)
Robot operating systems (ros) overview & (1)Robot operating systems (ros) overview & (1)
Robot operating systems (ros) overview & (1)Piyush Chand
 
Software defined network
Software defined networkSoftware defined network
Software defined networkBogamoga1
 
Network the 4th layer
Network the 4th layerNetwork the 4th layer
Network the 4th layerkachbourimed
 
A Process Oriented Development Flow for Wireless System Networks by Bernard P...
A Process Oriented Development Flow for Wireless System Networks by Bernard P...A Process Oriented Development Flow for Wireless System Networks by Bernard P...
A Process Oriented Development Flow for Wireless System Networks by Bernard P...ESUG
 
Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...
Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...
Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...Stefano Salsano
 
NetSim Webinar on Cognitive Radio Networks
NetSim Webinar on Cognitive Radio NetworksNetSim Webinar on Cognitive Radio Networks
NetSim Webinar on Cognitive Radio NetworksSANJAY ANAND
 
PERFORMANCE STUDIES ON THE VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKS
PERFORMANCE STUDIES ON THE  VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKSPERFORMANCE STUDIES ON THE  VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKS
PERFORMANCE STUDIES ON THE VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKSJYoTHiSH o.s
 
Designing High-Performance and Scalable Middleware for HPC, AI and Data Science
Designing High-Performance and Scalable Middleware for HPC, AI and Data ScienceDesigning High-Performance and Scalable Middleware for HPC, AI and Data Science
Designing High-Performance and Scalable Middleware for HPC, AI and Data ScienceObject Automation
 
Networking Basics
Networking BasicsNetworking Basics
Networking BasicsCarlo Fonda
 

Ähnlich wie OLPC Mesh networking improvements (20)

Wireless mesh networkk routing
Wireless mesh networkk routingWireless mesh networkk routing
Wireless mesh networkk routing
 
Haystack Technology Overview
Haystack Technology OverviewHaystack Technology Overview
Haystack Technology Overview
 
Wiki2010 Unit 4
Wiki2010 Unit 4Wiki2010 Unit 4
Wiki2010 Unit 4
 
Ods chapter7
Ods chapter7Ods chapter7
Ods chapter7
 
เทคโนโลยีสารสนเทศสำหรับครู
เทคโนโลยีสารสนเทศสำหรับครูเทคโนโลยีสารสนเทศสำหรับครู
เทคโนโลยีสารสนเทศสำหรับครู
 
Mba admission in india
Mba admission in indiaMba admission in india
Mba admission in india
 
Spring sim 2010-riley
Spring sim 2010-rileySpring sim 2010-riley
Spring sim 2010-riley
 
Robot Operating Systems (Ros) Overview &amp; (1)
Robot Operating Systems (Ros) Overview &amp; (1)Robot Operating Systems (Ros) Overview &amp; (1)
Robot Operating Systems (Ros) Overview &amp; (1)
 
Robot operating systems (ros) overview & (1)
Robot operating systems (ros) overview & (1)Robot operating systems (ros) overview & (1)
Robot operating systems (ros) overview & (1)
 
Software defined network
Software defined networkSoftware defined network
Software defined network
 
Network the 4th layer
Network the 4th layerNetwork the 4th layer
Network the 4th layer
 
TransPAC3/ACE Measurement & PerfSONAR Update
TransPAC3/ACE Measurement & PerfSONAR UpdateTransPAC3/ACE Measurement & PerfSONAR Update
TransPAC3/ACE Measurement & PerfSONAR Update
 
A Process Oriented Development Flow for Wireless System Networks by Bernard P...
A Process Oriented Development Flow for Wireless System Networks by Bernard P...A Process Oriented Development Flow for Wireless System Networks by Bernard P...
A Process Oriented Development Flow for Wireless System Networks by Bernard P...
 
Introduction to socket programming nbv
Introduction to socket programming nbvIntroduction to socket programming nbv
Introduction to socket programming nbv
 
Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...
Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...
Superfluid Deployment of Virtual Functions: Exploiting Mobile Edge Computing ...
 
NetSim Webinar on Cognitive Radio Networks
NetSim Webinar on Cognitive Radio NetworksNetSim Webinar on Cognitive Radio Networks
NetSim Webinar on Cognitive Radio Networks
 
PERFORMANCE STUDIES ON THE VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKS
PERFORMANCE STUDIES ON THE  VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKSPERFORMANCE STUDIES ON THE  VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKS
PERFORMANCE STUDIES ON THE VARIOUS ROUTING PROTOCOLS IN AD-HOC NETWORKS
 
Manet algo
Manet algoManet algo
Manet algo
 
Designing High-Performance and Scalable Middleware for HPC, AI and Data Science
Designing High-Performance and Scalable Middleware for HPC, AI and Data ScienceDesigning High-Performance and Scalable Middleware for HPC, AI and Data Science
Designing High-Performance and Scalable Middleware for HPC, AI and Data Science
 
Networking Basics
Networking BasicsNetworking Basics
Networking Basics
 

Mehr von OSLL

SLAM Constructor Framework for ROS
SLAM Constructor Framework for ROSSLAM Constructor Framework for ROS
SLAM Constructor Framework for ROSOSLL
 
Студентам и не только. Как выступить с докладом по своей научной работе
Студентам и не только. Как выступить с докладом по своей научной работеСтудентам и не только. Как выступить с докладом по своей научной работе
Студентам и не только. Как выступить с докладом по своей научной работеOSLL
 
Full Automated Continuous Integration and Testing Infrastructure for Maxscale...
Full Automated Continuous Integration and Testing Infrastructure for Maxscale...Full Automated Continuous Integration and Testing Infrastructure for Maxscale...
Full Automated Continuous Integration and Testing Infrastructure for Maxscale...OSLL
 
Microservice architecture for Geo2Tag
Microservice architecture for Geo2TagMicroservice architecture for Geo2Tag
Microservice architecture for Geo2TagOSLL
 
Block-level compression in Linux. Pro et contra
Block-level compression in Linux. Pro et contraBlock-level compression in Linux. Pro et contra
Block-level compression in Linux. Pro et contraOSLL
 
Raspberry Pi robot with ROS
Raspberry Pi robot with ROSRaspberry Pi robot with ROS
Raspberry Pi robot with ROSOSLL
 
Source code analyzer
Source code analyzer Source code analyzer
Source code analyzer OSLL
 
Fruct14 sholokhova
Fruct14 sholokhovaFruct14 sholokhova
Fruct14 sholokhovaOSLL
 
SECR'13 Lightweight linux shared libraries profiling
SECR'13 Lightweight linux shared libraries profilingSECR'13 Lightweight linux shared libraries profiling
SECR'13 Lightweight linux shared libraries profilingOSLL
 
Smart-M3 and Geo2Tag integration
Smart-M3 and Geo2Tag integrationSmart-M3 and Geo2Tag integration
Smart-M3 and Geo2Tag integrationOSLL
 
HTML5 Intro and Tizen Web API
HTML5 Intro and Tizen Web APIHTML5 Intro and Tizen Web API
HTML5 Intro and Tizen Web APIOSLL
 
Fruct13 geo2tag-training
Fruct13 geo2tag-trainingFruct13 geo2tag-training
Fruct13 geo2tag-trainingOSLL
 
Json protocol, Geo2tag REST API fundamentals
Json protocol, Geo2tag REST API fundamentalsJson protocol, Geo2tag REST API fundamentals
Json protocol, Geo2tag REST API fundamentalsOSLL
 
Introduction to geo-tagging and geo2tag platform
Introduction to geo-tagging and geo2tag platformIntroduction to geo-tagging and geo2tag platform
Introduction to geo-tagging and geo2tag platformOSLL
 
Detection pulse by video
Detection pulse by video Detection pulse by video
Detection pulse by video OSLL
 
Using Intel NAS-PT for testing NAS disks
Using Intel NAS-PT for testing NAS disksUsing Intel NAS-PT for testing NAS disks
Using Intel NAS-PT for testing NAS disksOSLL
 

Mehr von OSLL (16)

SLAM Constructor Framework for ROS
SLAM Constructor Framework for ROSSLAM Constructor Framework for ROS
SLAM Constructor Framework for ROS
 
Студентам и не только. Как выступить с докладом по своей научной работе
Студентам и не только. Как выступить с докладом по своей научной работеСтудентам и не только. Как выступить с докладом по своей научной работе
Студентам и не только. Как выступить с докладом по своей научной работе
 
Full Automated Continuous Integration and Testing Infrastructure for Maxscale...
Full Automated Continuous Integration and Testing Infrastructure for Maxscale...Full Automated Continuous Integration and Testing Infrastructure for Maxscale...
Full Automated Continuous Integration and Testing Infrastructure for Maxscale...
 
Microservice architecture for Geo2Tag
Microservice architecture for Geo2TagMicroservice architecture for Geo2Tag
Microservice architecture for Geo2Tag
 
Block-level compression in Linux. Pro et contra
Block-level compression in Linux. Pro et contraBlock-level compression in Linux. Pro et contra
Block-level compression in Linux. Pro et contra
 
Raspberry Pi robot with ROS
Raspberry Pi robot with ROSRaspberry Pi robot with ROS
Raspberry Pi robot with ROS
 
Source code analyzer
Source code analyzer Source code analyzer
Source code analyzer
 
Fruct14 sholokhova
Fruct14 sholokhovaFruct14 sholokhova
Fruct14 sholokhova
 
SECR'13 Lightweight linux shared libraries profiling
SECR'13 Lightweight linux shared libraries profilingSECR'13 Lightweight linux shared libraries profiling
SECR'13 Lightweight linux shared libraries profiling
 
Smart-M3 and Geo2Tag integration
Smart-M3 and Geo2Tag integrationSmart-M3 and Geo2Tag integration
Smart-M3 and Geo2Tag integration
 
HTML5 Intro and Tizen Web API
HTML5 Intro and Tizen Web APIHTML5 Intro and Tizen Web API
HTML5 Intro and Tizen Web API
 
Fruct13 geo2tag-training
Fruct13 geo2tag-trainingFruct13 geo2tag-training
Fruct13 geo2tag-training
 
Json protocol, Geo2tag REST API fundamentals
Json protocol, Geo2tag REST API fundamentalsJson protocol, Geo2tag REST API fundamentals
Json protocol, Geo2tag REST API fundamentals
 
Introduction to geo-tagging and geo2tag platform
Introduction to geo-tagging and geo2tag platformIntroduction to geo-tagging and geo2tag platform
Introduction to geo-tagging and geo2tag platform
 
Detection pulse by video
Detection pulse by video Detection pulse by video
Detection pulse by video
 
Using Intel NAS-PT for testing NAS disks
Using Intel NAS-PT for testing NAS disksUsing Intel NAS-PT for testing NAS disks
Using Intel NAS-PT for testing NAS disks
 

Kürzlich hochgeladen

Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostZilliz
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfPrecisely
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 

Kürzlich hochgeladen (20)

Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 

OLPC Mesh networking improvements

  • 1. OLPC Mesh network improving Arina Rudakova (Saint-Petersburg Elelectrotechnical University «LETI») 3rd FRUCT seminar Saint-Petersburg 23 May 2008
  • 2. Agenda  Introduction  Problem definition  Domain analysis  Solution  Project timeline
  • 4. One Laptop Per Child  Home: http://laptop.org  The mission of the One Laptop per Child association is to develop a low-cost laptop—the "XO Laptop"— to revolutionize how we educate the world's children. Goal is to provide children around the world with new opportunities to explore, experiment, and express themselves.
  • 5. XO laptops hardware  Dimensions: 242mm × 228mm × 32mm  CPU x86-compatible processor AMD Geode LX-700 433 Mhz, 64KB each L1 I and D cache; at least 128KB L2 cache  DRAM memory: 256 MiB dynamic RAM  BIOS: 1024KiB SPI-interface flash ROM  Mass storage: 1024 MiB SLC NAND flash, high-speed flash controller  Display: Liquid-crystal display: 7.5” dual-mode TFT display  Keyboard: 80+ keys, 1.0mm stroke; sealed rubber-membrane key-switch assembly  Gamepad: Two sets of four-direction cursor-control keys  Touchpad: Dual capacitance/resistive touchpad; supports written-input mode  Audio: AC’97 compatible audio subsystem  Integrated color video camera: 640 x 480 resolution at 30 FPS  Wireless Networking: Integrated 802.11b/g (2.4GHz) interface; 802.11s (Mesh) networking supported; dual adjustable, rotating antennas support diversity reception; capable of mesh operation when CPU is powered down;
  • 6. XO laptops software  Operating system: Linux Kernel: Linux 2.6.22; Fedora 7 base environment.  User environment: Sugar GUI, written in Python, on top of the X Window and the Matchbox WM  Programming environments (main): − Python (Version 2.5); − JavaScript; − Csound, music programming language; − Etoys, an implementation of Squeak using Smalltalk, an object-based programming language; − Turtle Art, a graphical programming environment; − Adobe's Flash Player, Java, Gnash  Libraries − Mozilla Gecko/Xulrunner (the Firefox web engine); − GUI toolkit (GTK+) (Gnome); − Matchbox window manager; − X Window System X.org Foundation; − Multimedia framework: GStreamer and RealNetworks; − Gettext, the GNU internationalization library
  • 7. Neighborhood: Collaboration interface The Neighbourhood view displays all the connected XO laptops within a child’s community, and what activities they are sharing. Each child is represented by a different colour If there is a shared document or activity being collaborated on by a number of children, it will show up within this view.
  • 8. XO Mesh goals  Ability to act as a mesh point when laptop's main CPU is off.  Support for asymmetric links/paths.  Incremental releases—mesh networking is available immediately on XO; Upgrades will continue to improve functionality and adherence with standards.  Simultaneously acts as a mesh point and an infrastructure node.  Standards Compliance: follow 802.11s draft when possible.
  • 10. Mesh network types  Infrastructure wireless mesh networks: Mesh routers form an infrastructure for clients.  Client wireless mesh networks: Client nodes constitute the actual network to perform routing and configuration functionalities.  Hybrid wireless mesh networks: Mesh clients can perform mesh functions with other mesh clients as well as accessing the network
  • 11. Distinguishing features  dynamics  structure
  • 12. Routing mechanism in mesh  Redundante links usage − Fault tolerance − Load sharing  Traffic analysis  Network diversity  Route aggregation
  • 13. Routing overhead reasons  Nodes number influence on the amount of control traffic  Network changes dynamics influence on the amount of control traffic  Route length influence on the amount of control traffic
  • 14. Project Goals  Reducing Routing overhead  OLPC implementation
  • 16. Ad-hoc Routing types  Pro-active or Table-driven  Reactive Routing or On-demand  Flow Oriented  Adaptive Routing or Situation-Aware  Hybrid (Pro-Active and Reactive)
  • 17. Industrial and open source implementations  AWDS (Ad-hoc Wireless Distribution Service) http://awds.berlios.de/  DSDV (Highly Dynamic Destination-Sequenced Distance Vector routing protocol) – based on Bellman-Ford Routing Protocol  AODV (Ad-hoc On-demand Distance Vector)  Mobile Ad-hoc On-Demand Data Delivery Protocol  MPRDV (Multipoint Relay Distance Vector protocol)  SSR (Signal Stability Routing protocol)  PLBR (Preferred link based routing)  TORA (Temporally-Ordered Routing Algorithm routing protocol)  HRPLS (Hybrid Routing Protocol for Large Scale Mobile Ad-Hoc Networks with Mobile Backbones)  HSLS (Hazy Sighted Link State routing protocol)  ZRP (Zone Routing Protocol)
  • 19. Solution components  Routing area restriction  Dynamic selection of optimization radius  External definition of routing overhead
  • 20. Routing overhead chart  m — tree arity  n — nodes number  R — dynamics
  • 21. Possible reasons of routing overhead increase  Number of nodes increase  Network dynamics increase  Network radius increase  Using aggressive updating strategy
  • 22. Routing area restriction For effective routing area definition we should introduce some definitions. G(t)=<V,E>, where V – set of nodes, E – arches G(t) describes network topology d(vi,vj) – distance between vi and vj vi: Ri>0, G (vi , Ri ) ⊂ G (t ), d (vi , v j ) ≤ Ri Choose Ri with regard to time needed for collection of information about G(vi,Ri) G(vi,Ri) - effective routing area for vi, G (vi , Ri ) ≡ R(vi )
  • 23. External and internal routing records  External routing records (only in edge nodes)  Internal routing records (always true)
  • 24. Routing optimization area  Local optimization  Global optimization  Optimization in restricted area
  • 25. Local sample  Information collection – 1 hop  Route defining – 1 hop  «Trust» zone – 1 hop  Control traffic is minimum
  • 26. Global sample  Information collection – whole net  Route defining – whole net  «Trust» zone – whole net  Control traffic is maximum
  • 27. Restricted sample  Information collection is restricted with R  Route defining – within R radius  «Trust» zone – within R radius  Control traffic is restricted
  • 28. Failure detection  At first only one router knows about a route failure  After the message to sender about the impossibility of passing, the whole effective routing area is informed  The sender gets informed when its timer is over
  • 31. Global plan The past  2007 Autumn, generic task definition, domain investigation  2008 Winter, getting XO devices, experience XO system programming The future  2008 Summer, public presentation our of solution ideas (conference proceedings or paper)  2008 Autumn, implement modules for NS2 and simulations  2008 Winter, contribute some code for XO laptops  2009 Spring, defence of the master thesises at LETI

Hinweis der Redaktion

  1. 1. This is a research project 2. Project has next parts: 1) Research/investigation 2) Modelling/analysis 3) Implementation
  2. мы рассматриваем клиентские сети
  3. Отличительные особенности
  4. Only dynamic routing can allow and make use of redundante links. A router is able to make decisions about which link to use based on a set of configurable measures. Once the redundant links exist, if a link goes down, an alternative path around the failed node will be automatically found and used. Even if links do not actually go down, the routers can distribute the traffic load across the available paths in proportion to the bandwidth available on each path. Routers&apos; reports about what they are doing make it easy to produce good statistics about network utilisation which would allow us to hilight areas of heavy traffic, for example, and plan acordingly. Using routers at a backbone level would allow people running Access Point to run pretty much networking software and formats. Routers can aggregate routes to subnets that are part of the same larger network into a single route to advertise to the rest of the world.
  5. http://www.cse.unsw.edu.au/~nrl/researchprojects.htm#jqadir On Reducing Routing Overhead in MANET Ph.D Candidate: Quan Jun (Jerry) Chen Description: Reducing Routing overhead is one of the most important tasks in wireless network. Particularly, in Mobile Adhoc Network (MANET), where topology changes frequently, routing protocols may generate considerable routing overhead when conquering the uncertainty of mobile nodes. Excessive routing overhead consumes valuable resources, such as bandwidth and power, and causes frequent packet collisions, which finally degrade network throughput and end-to-end delay. In our work, we decompose routing protocols into two fundamental building blocks: 1) beacon broadcasting (route maintenance) and 2) flooding rebroadcasting (route discovery), and we propose two frameworks respectively to reduce routing overhead occurred. For the first one, we propose the framework of “Adaptive Beacon Broadcasting (ABB)”, which adapts beacon broadcasting to nodes mobility and traffic load. For the second one, by exploiting the relationship between flooding distance and the number of hops, we propose “Distance-based Flooding Restriction (DFR)”. Both frameworks are evaluated by theoretical model and simulation. The results show ABB and DFR can significantly reduce routing overhead without compromising other performance metrics.
  6. Pro-active This type of protocols maintains fresh lists of destinations and their routes by periodically distributing routing tables throughout the network. The main disadvantages of such algorithms are - 1. Respective amount of data for maintenance. 2. Slow reaction on restructuring and failures. Reactive This type of protocols finds a route on demand by flooding the network with Route Request packets. The main disadvantages of such algorithms are - 1. High latency time in route finding. 2. Excessive flooding can lead to network clogging. Flow-Oriented This type of protocols finds a route on demand by following present flows. One option is to unicast consecutively when forwarding data while promoting a new link The main disadvantages of such algorithms are - 1. Takes long time when exploring new routes without a priori knowledge. 2. May refer to entitative existing traffic to compensate for missing knowledge on routes. Adaptive This type of protocols combines the advantages of proactive and of reactive routing. The routing is initially established with some proactively prospected routes and then serves the demand from additionally activated nodes through reactive flooding. Some metrics must support the choice of reaction. The main disadvantages of such algorithms are - 1. Advantage depends on amount of nodes activated. 2. Reaction to traffic demand depends on gradient of traffic volume. Hybrid This type of protocols combines the advantages of proactive and of reactive routing. The routing is initially established with some proactively prospected routes and then serves the demand from additionally activated nodes through reactive flooding. The choice for one or the other method requires predetermination for typical cases. The main disadvantages of such algorithms are - 1. Advantage depends on amount of nodes activated. 2. Reaction to traffic demand depends on gradient of traffic volume.
  7. Restrict routing area. Efficient routing area definition. Optimal routing inside the effective routing area. Not guaranteed — outside. Change optimization radius to control network services&apos; QoS. Limit routing overhead externally in order to provide this requirement. Trade-off between traffic overhead and routes quality.
  8. Арность дерева — число несвязанных узлов в дереве, с которыми связан каждый узел дерева Дерево — худший из возможных вариантов маршрутизации
  9. Общая идея такая: чем большее число узлов каждый маршрутизатор (node в данном случае) будет использовать для поиска маршрута, тем большие накладные расходы
  10. d(v i ,v j ) – distance between v i and v j - min hop count With right R i number nodes will have all necessary information for optimal route definition. Calculation expenses for effective route search algorithms are low.