KAIST

Energy-Efficient, Collision-Free Medium Access Control for Wireless Sensor Networks

Venkatesh Rajendran, Katia Obraczka, J.J. Garcia-Luna-Aceves

Wireless Networks 2006

JY Hong2008. 10. 30

Contents

Introduction

Related Works

TRAMAProtocol Overview

Neighbor Protocol

Schedule Exchange Protocol

Adaptive Election Algorithm

Simulation Results

Conclusion

TRAMA 2 / 22

Introduction

Wireless Sensor Network (WSN)

Large ensembles of interconnected nodes

Self-organize into a multi-hop wireless network

The scheduling of transmissions among nodes is major

challenge

Prolongs the battery life of each node

Self adaptive to changes in traffic, node state, connectivity

3 / 22TRAMA

Related Works - 1

Research Categories of MACContention-based

DCF 802.11b (Distributed Coordination Function)

PAMAS (Power Aware Multi Access Protocol with Signaling for ad hoc networks)

S-MAC (Sensor MAC)

Schedule-based, Contention-freeTDMA, FDMA, CDMA

NAMA (Node Activation Multiple Access)

4 / 22TRAMA

Related Works - 2

S-MAC : Basic Mechanism

5 / 22TRAMA

TRaffic Adaptive Multiple Access

TRAMA CharacteristicsEnergy-Efficient

No collision, No idle listening, No idle sender

Schedule-based

FairTransmitter-Election Algorithm

Identify of nodes one and two hop away

Traffic information

Adaptive scheduling

6 / 22TRAMA

Protocol Overview

Three components of TRAMANeighbor Protocol (NP)

Gather 2-hop neighborhood information

Schedule Exchange Protocol (SEP)Gather 1-hop traffic information for Scheduling

Adaptive Election Algorithm (AEA)Select transmitters

7 / 22TRAMA

Protocol Overview

Access modeRandom Access

Node can join the network

All nodes must be in transmit or receive state Collision

Significant role in energy consumption

Scheduled AccessCollision-free data exchange and schedule propagation

8 / 22TRAMA

Time slot Organization

NP

NPGather neighborhood information by exchanging small sig-naling packets in random access period

9 / 22TRAMA

SEP - 1

Transmission slots Collision-free data exchange and schedule propagation

SEP Traffic-based information (Schedules) with neighbors

Traffic coming from a node

The set of receiver for the traffic originating at the node

A node has to announce its schedule using SEP before starting actual transmissions

10 / 22TRAMA

SEP - 2

Schedule packet format

11 / 22TRAMA

SEP - 3

Example

12 / 22TRAMA

u7

14

2

15

Schedule packet of node u

(if winning slot are 2, 10, 20, 30, 35, 50, 58, 60)

u ’s ad-dress

100 4 8 Bitmap

1 0 0 1

2 7 14 15

0 0 0 1

2 7 14 15

1 1 1 1

2 7 14 15

2 10 20

0 0 0 0

2 7 14 15

30

Changeover Slot

1 1 1 1

2 7 14 15

60

……..

Schedule packet of node 14

(if winning slot are 5, 15, 38, 42)

14 ’s ad-dress

100 1 4 Bitmap

1

u

1 1 1

5 15 38 42

u u u

AEA - 1

Original NCR algorithmContending set

All nodes that are in two-hop neighborhood

No sleep state, not adaptive with traffic

13 / 22TRAMA

TRAMA’s AEAPossible state of a node

TX(Transmit), RX(Receive), SL(Sleep)

AEA - 2

U is a TX stateHighest priority among its contending set

U has data to send

U is a RX stateIntended receiver of the current transmitter

By consulting the schedule sent out by the selected transmit-ter

U is a SL stateNo transmitter, No intended receiver

Each node executes AEA to decide its current state

Current node priorities in two-hop neighborhood

Based on the announced schedules form one-hop neigh-bors 14 / 22TRAMA

AEA - 3

When a node becomes an Absolute Winner for a particular timeslot and has announced a non-zero bitmap for this slot, it know that no other node in its two-hop neighborhood will be transmitting in this slot

15 / 22TRAMA

Absolute Winner

Intended Receiver

AEA - 4

To avoid wasting slots when the Winner has no data to send

Possible Transmitter Set in the one-hop neighborhoodHighest priority in two-hop neighbor No collision

PTX(u)

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Absolute Winner

Simulation Parameters

Simulation platformQUALNET

500m X 500m area50 nodes are uniformly distributed6 one-hop neighbors on average17 two-hop neighbors on averageNode traffic

Statistically generated based on a exponentially distributed inter-arrival time

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Simulation Results - 1

18 / 22TRAMA

Percentage received

Simulation Results - 2

19 / 22TRAMA

Average Delay

Simulation Results - 3

20 / 22TRAMA

Percentage Sleep time

Conclusion

TRAMA achieves Energy-savings comparable to S-MAC

Delivery guarantees comparable to NAMA

TRAMA Limitations Complex election algorithm and data structure

Overhead due to explicit schedule propagation

Higher Queueing delay Long delay

TRAMA has higher delayIt Suited for

Not delay sensitive

High delivery guarantees

Energy efficiency

21 / 22WSAN : Research Challenges

Questions or Comments

22 / 22WSAN : Research Challenges

Appendix - Alternate Winner

23 / 22TRAMA

Absolute Winner

Alternate Winner