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# An Energy-Efficient Flooding Algorithm in ad hoc network(APE) PowerPoint PPT Presentation

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

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

• Proposed solution

• Simulation (Ongoing)

### I. Introduction(1) – 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

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

### 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

• 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

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)

• Overview

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

• Algorithm: Flooding filter

• Require energy level:

• Eth = (packets)*Pcs

• Eth = (packets)*Prc

### 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)

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)

• 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)

• Case 2:Eav < Eth

• 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

• 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.