An Energy-Efficient Flooding Algorithm in ad hoc network(APE) Concrete Mathematic mid-term presentation of term project Professor: Kwangjo KimKwangjo 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 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 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 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. Source f(i)=40f(i)=10 Destination f(i)=30 Route 2 Route 1 Chosen route Over Used Node

II. Related work(2) - MMBCR MMBCR: Min-Max battery cost routing Eliminate routing containing week node: f(i)=20 Source f(i)=40f(i)=10 Destination f(i)=30 Route 2 Route 1 Eng=8W Eng=4 Eng=0W Eng=2 Eng=8W Eng=4 Waste energy in case of short time connection

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: E th = (packets)*P cs E th = (packets)*P rc

III. Proposed solution:EFA(2) Immediate node: Calculate available energy In case of serving j node at the same time E av = N re - E rq(j) Otherwise E av = N re Comparing available energy with require energy level Case 1: E av >= E th : take part in routing process Case 2: E av < E th : reject routing process

III. Proposed solution:EFA(3) 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 Flooding filter

III. Proposed solution:EFA(4) Case 1: E av >= E th 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: E av < E th Discard RREQ packet If : P = {Ni | Eav ≥ Eth, Ni Є Immediate nodes} = Ø After T fck, Reduce Eth at source node automatically E th = E th - D st ; D st = S re /λ (λ=10) This step will repeat until P ≠ Ø Or Tfck ≥ TTL Re broadcast RREQ with new E th

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.