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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

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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