Final Review 1203
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CACHING STRATEGIES BASED ON INFORMATION DENSITY ESTIMATION IN WIRELESS AD-HOC NETWORKSPresented by, G.Bhaskar(08S11A1203) N.V.Mahesh(08S11A1259) A.Devisree(08S11A1211)
Under the guidance of, J.Santhosh Kumar Goud
Abstract We address cooperative caching in wireless networks, where the nodes may be mobile and exchange information in a peer-to-peer fashion. We devise two different strategies for both large and small sized caches, where the result is creation of content diversity within the nodes neighbourhood, so that a requesting user likely finds the desired information, thus leading to a resource-efficient information access.
Introduction to project By title itself our project explains about caching mechanisms based on information flow in wireless networks & deals with problems like congestion control Our project is based on two strategies 1)Router 2) virtual machine
Objective Data caching strategy for ad hoc networks. Content diversity within the nodes.
User gets the desired information. Caches Compares with each other.
A cache is a place to store something temporarily
Caching helps in reducing communication, this results in savings in bandwidth, as well as battery energy.Two types of caches exists: Large sized and small sized caches
Ad hoc networks
it can self organize into a network without the help of an existing infrastructure.
Existing system Manet uses Flooding type Routing protocols like hash based or router based which faces several disadvantages. Network Bandwidth is wasted. Messages can also become duplicated ie.,no content diversity. Selective flooding partially addresses these issues by only sending packets to routers in the same direction.
Proposed system Caching scheme here will succeed in content diversity. The solution that was proposed is based on the formation of an overlay network composed of mediator nodes. Eliminates unnecessary flooding,by cooperative caching. A route is established only when it is required.
Advantage Reduces the access latency and bandwidth usage. Requires the manual setting of a network wide Caching zone,which is challenging task,but very efficient.
SELF ORGANIZING SELFADDRESSING INTEGRATED CACHEROUTING LOCALIZED CACHING POLICY DISTRIBUTED CACHING ALGORITHM
Hardware & software Requirements HARDWARE REQUIREMENTS: Processor : Pentium IV 2.8GHz. RAM : 512 MB RAM. Hard Disk : 40 GB. Input device : Standard Keyboard and Mouse. Output device : VGA and High Resolution Monitor.
SOFTWARE REQUIREMENTS: Operating System : Windows XP Language : JDK 1.6.
SDLC life cycleSpiral model
UML diagramsClass diagramNetwork +sender()
AddNodes +nodeinCreation() +nodeInCell()
DataCaching +startMobility() +refreshNodes()
CachingPath +adjacentNodes() +totalNodes() +getShortest() +getCachingNodes() +pathDifference()
Use case diagramJoin Receive
Send heart beat signals
Recieve signals Routing Host Network GetAddress Organizing
Disconnect from Network
Sequence diagramNew Node Network Parent
1 : enter thw network() 2 : find the parent()
3 : return the parent node position()
4 : attach as child node() 5 : Reorganizw the network() 6 : calculate the new address()
7 : update routing tables()
8 : return adress and rouitng table()
Collaboration diagramParent5.Reorganize the network
4.Attach as child node
3.Return the parent node position
2:Find the parent
6.Calculate the new address 7.Updating routing table
8.Return address and routing table
New Node1.Enter the network
Activity diagramwait for new nodes
if node enters
Calculate new Adrress
Update Routiing Tables
Testing WHITE BOX TESTING
BLACK BOX TESTING PROGRAM TESTING VERIFICATION TESTING
Literature survey Cooperative Caching Content diversity Caching with limited storage capabilty Data replication
Data Flow Diagram: Level-0Join Request
Data Flow Diagram: Level-1New nodeJoin request nodes Address & Routing table
Un addressed Tree
Routing Cache Routing System
Conclusion In particular, we have considered memory capacity constraint of the network nodes. Efficient data caching algorithms where developed to determine near optimal cache placements to maximize reduction in overall access cost. Content diversity within the nodes neighborhood so that a requesting user likely finds the desired information nearby.
Future enhancement User nodes can overhear queries for content and relative responses within their radio proximity by exploiting the broadcast nature of the wireless medium. User nodes can estimate their distance in hops from the query source and the responding node due to a hop-count field in the messages