An energy efficient flooding algorithm in ad hoc network ape
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An Energy-Efficient Flooding Algorithm in ad hoc network(APE). Concrete Mathematic mid-term presentation of term project Professor: Kwangjo Kim Group 16: Tran Minh Trung, Nguyen Duc Long. An Energy-efficient Flooding Algorithm in ad hoc network (EFA). Introduction Related works

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An Energy-Efficient Flooding Algorithm in ad hoc network(APE)

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An energy efficient flooding algorithm in ad hoc network ape

An Energy-Efficient Flooding Algorithm in ad hoc network(APE)

Concrete Mathematic

mid-term presentation of term project

Professor:Kwangjo Kim

Group 16: Tran Minh Trung, Nguyen Duc Long


An energy efficient flooding algorithm in ad hoc network efa

An Energy-efficient Flooding Algorithm in ad hoc network (EFA)

  • Introduction

  • Related works

  • Proposed solution

  • Simulation (Ongoing)


I introduction 1 ad hoc network

I. Introduction(1) – Ad hoc Network

  • Ad hoc Network

    • lack of fixed infrastructure

    • peer-to-peer (all nodes act as routers)

    • multi-hop routing

    • frequent connection / topology changes

  • Challenges:

    • Security, Scalability

    • QOS, load balancing

    • Effect on device’s battery life – Network’s life time


I introduction 2 paper objective

I. Introduction(2) – Paper objective

  • Objective

    • Prolong Network life

    • Reduce traffic load at Routing discovery phase

  • Related works: MBCR, MMBCR

    • Make power consumptions eventually distributed on every node.

  • Limitations:

    • Redundancy routing discovery processes

    • All nodes take part in a routing process passively that makes a nodes run out of energy fast, especially, when it has to serve many routing process at the same time

  • Proposed solution:

    • enable each node actively in saving its residual energy capacity while the network connectivity is still be guarantied


  • Ii related work 1 mbcr

    f(i)=40

    f(i)=10

    Chosen route

    Route 1

    Source

    Destination

    Route 2

    f(i)=30

    f(i)=30

    II. Related work(1) - MBCR

    • MBCR: (Minimum battery cost routing)

      • This protocol use remaining battery capacity of each host as a metric to describe the lifetime of each mobile host.

    Over Used

    Node


    Ii related work 2 mmbcr

    Eng=2

    Eng=4

    Eng=8W

    Eng=0W

    Eng=8W

    Eng=4

    II. Related work(2) - MMBCR

    • MMBCR: Min-Max battery cost routing

      • Eliminate routing containing week node:

    f(i)=40

    f(i)=10

    Route 1

    Source

    Destination

    Waste energy in case of short time connection

    Route 2

    f(i)=30

    f(i)=30

    f(i)=20


    Iii proposed solution efa 1

    III. Proposed solution:EFA(1)

    • Overview

      • Enable each node actively in saving its residual energy capacity while the network connectivity is still be guarantied

    • Algorithm: Flooding filter

      • New RREQ header:

        • Source Addr, current seq#, Dest Addr, Dest seq# Broadcast ID

        • Require energy level:

          • Eth = (packets)*Pcs

          • Eth = (packets)*Prc


    Iii proposed solution efa 2

    III. Proposed solution:EFA(2)

    • Immediate node:

      • Calculate available energy

        • In case of serving j node at the same time

          • Eav = Nre - Erq(j)

        • Otherwise

          • Eav = Nre

      • Comparing available energy with require energy level

        • Case 1: Eav >= Eth : take part in routing process

        • Case 2: Eav < Eth : reject routing process


    Iii proposed solution efa 3

    III. Proposed solution:EFA(3)

    Flooding filter

    • Advantages of flooding filter:

      • Reduce traffic load at discovery routing phase

      • Reduce interference between nodes

      • Reduce power consumption at discovery routing phase

      • Reduce the deviation between require energy level and the energy available of each node


    Iii proposed solution efa 4

    III. Proposed solution:EFA(4)

    • Case 1:Eav >= Eth

      • Check current routing process in routing table (Check fresh route, hope count …)

      • Update/add routing table if necessary (set reserve path for new routing process:

        • source node’s IP address, seq.#

        • the number of hops to the source

        • IP address of the neighbor from which the RREQ was received

        • Energy requirement for this routing process

      • Send IACK back to the node which the RREQ was received from


    Iii proposed solution efa 5

    III. Proposed solution:EFA(5)

    • Case 2:Eav < Eth

      • Discard RREQ packet

      • If : P = {Ni | Eav ≥ Eth, Ni Є Immediate nodes} = Ø

        • After Tfck, Reduce Eth at source node automatically

        • Eth= Eth - Dst; Dst = Sre/λ (λ=10)

          • This step will repeat until P ≠ ØOr Tfck ≥ TTL

        • Re broadcast RREQ with new Eth


    Iv simulation

    IV. Simulation

    • Simulation model:

      • 50 mobile nodes

      • are generated randomly in an area of 500M*500M.

      • The moving speed of each node is 10m/s.

      • 20 connections is established during 900 seconds simulation times.

      • The energy model:

        • initial energy of each node is 20mW.

        • The energy usage for receiving and sending each packet are txPower = 0.6mW and rxPower = 0.3mW respectively.


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