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Routing and Scheduling for mobile ad hoc networks using an EINR approach Harshit Arora

SURE 2007. Routing and Scheduling for mobile ad hoc networks using an EINR approach Harshit Arora Advisor : Dr. Harlan Russell. Results. Simulation model. Background. Simulation Results. Routing metrics Min-hop routing: If ENR > β * η link weight = 1 otherwise 0. Disadvantage:

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Routing and Scheduling for mobile ad hoc networks using an EINR approach Harshit Arora

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  1. SURE 2007 Routing and Scheduling for mobile ad hoc networks using an EINR approach Harshit Arora Advisor : Dr. Harlan Russell Results Simulation model Background Simulation Results • Routing metrics • Min-hop routing: • If ENR > β*η link weight = 1 otherwise 0. • Disadvantage: • If β*η=3.0, for both links wt. = 1. • Although link(1,3) is far better than link(2,4) • min. hop approach shows no difference. • Distance metric approach: • If ENR > β*η link weight = • otherwise 0 • Proposed metric approach: • If ENR > β*η link weight = • otherwise 0 • Channel Access protocol • 8 time slots. • A particular time slot is selected if the • following three conditions hold: • The time slot is available to both Tx and Rx. • Rx satisfies the EINR criterion. • All other transmissions continue to maintain acceptable EINR. • Mobile ad Hoc Networks • A self-configuring network. • Does not require any infrastructure. • Can have any arbitrary • topology at a time. • Can operate in a standalone • fashion and thus can be • helpful in disaster management and • military conflicts. β=4 N=100 η=2 η=4 η=4 ENR =10 η=1.5 1 η=2 3 Weight =1 4 ENR =3.1 η=1.5 η=1 η=1 2 Weight =1 For a fixed β=4, η=2 gives the best nework performance. Assume that each node has 3 time slots. η=2 N=100 • EINR model • EINR is energy to interference + noise • ratio. • At a node: • Received energy and received • interference at the receiver are estimated • by using a propagation model . • No is the thermal energy of the noise at • the receiver. 4 • Transmit data from 1 to 4. • Transmit data from 4 to 5. • Transmit data from 5 to 3. • Transmit data from 2 to 6. β=0.01 β=4 5 3 1 6 β=1.0 β=1.0 β=0.01 2 β=4 For a fixed area a lower value of β increases the network capacity drastically but average diameter is very small. 45 • Description of Simulation model • A randomly generated network topology of • N nodes, whose location is randomly • decided, is considered in a square region. • Links are assigned weights. • The network is checked for connectivity. • A source and a destination pair is randomly • chosen. • A route between the source and the • destination is obtained. • The ‘network diameter’ is the number of • links in the longest min-hop route. • Slots are allocated to each link in the route. • If slot allotment is successful for all links, • the route is termed a success. • The total number of such successful pairs is • determined and is called ‘network • capacity’. 53 14 26 • Routing protocol • Dijkstra’s algorithm. • Links are assigned weight using the ENR (energy to noise ratio) criterion. • At any node: • Suppose link(4,8) has to be assigned weight. • Motivation behind the EINR approach • Transmission range model. • A wants to sent to B, C wants to send to D • Using transmission range model • Using the EINR model • EINR at B • EINR at D • If EINR at B and D is greater than the EINR threshold (β) then both transmisions are possible. Proposed approach Min hop approach Distance metric The proposed approach performs better than the min-hop and the distance metric approaches. • No node other than 8 is • assumed to transmit. • ENR criterion: • If ENR > threshold, • weight[4,8] =+ve otherwise 0. • If threshold = β Problem!!! • Threshold = β*η is a better choice. • η is called the interference margin. C 2 1 5 A B 6 D 7 3 • Conclusion • Analysis of different Network topologies show • that a low value of β reduces the network • dependence on interference. • The proposed routing metric protocol gives • better network performance. Tx Rx 8 4

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