Center for WirelessCOMMUNICATIONS 04/18/23

Energy Efficient Networking

Ramesh R. Rao

University of California, San Diego

- NeXtworking’03 - Chania, Crete, Greece, June 23-25,2003

The First COST-IST(EU)-NSF(USA) Workshop on EXCHANGES & TRENDS IN NETWORKING

Center for WirelessCOMMUNICATIONS 04/18/23

Introduction

Explosion of wireless devices and applications Eg. Cellular Networks, Ad Hoc Networks, Sensor

Networks Power hungry applications and shrinking form

factor Motivates need for energy aware designs

Center for WirelessCOMMUNICATIONS 04/18/23

Three Themes

Cross-layer optimization Resource ownership Batteries

Center for WirelessCOMMUNICATIONS 04/18/23

Cross-layer Optimization

Minimum energy/hops routing unsuitable

Suppose R2 is chosen as the relay Lifetime: Relay R2 will

die prematurely Throughput: More

interference Need for joint routing and

scheduling

Center for WirelessCOMMUNICATIONS 04/18/23

The Problem is Hard

Joint optimization is an NP-hard problem Arikan (1984)

For small networks, a brute force approach works. Nuggehalli (2002)

Need for scalable and distributed algorithms which can achieve near optimal performance

Center for WirelessCOMMUNICATIONS 04/18/23

Lifetime Vs. Throughput Optimal Routes

Lifetime Optimal Routes

Lifetime=1331.6

Throughput: 1

Throughput Optimal Routes

Lifetime=839.2

Throughput=1.33

Center for WirelessCOMMUNICATIONS 04/18/23

Resource Ownership

Ownership of resources determines protocol design paradigm

Ad Hoc Network: Distributed protocols that ensure system resources are used equitably and no user gets cheated

Bandwidth Energy

Cellular Networks

System User

Ad Hoc Networks

User User

Sensor Networks

System System

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Cooperation in Ad Hoc Networks

Standard Assumption: Nodes always relay messages for other nodes!

“What’s in it for me?” No cooperation leads

to zero throughput Complete cooperation

leads to short active life.

S1

S2

S3

DR

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Cooperation in Ad Hoc Networks (Contd.)

Two Questions: How Much to relay? What strategy? (No cheating)

Answer: (Srinivasan etal Infocom 2003) Given complete information

– Each node calculates optimal level of cooperation

– Implements GTFT strategy (Nash Equilibrium)

Challenge: Learn operating point through experience with the system

Center for WirelessCOMMUNICATIONS 04/18/23

Battery Management

Maximize bits transmitted for a given battery & wireless physical interface (both have serious impairments)

Develop MAC protocols for both best battery life & throughput (Tx when channel is best)

Optimize Tx time, Rx time, Idle time, Sleep time (high power pulsed Tx time)

Coordinate power consumption with battery state (decrease average power towards end of discharge)

Operational scenario: Wireless sensor network, solar powered by day, battery powered by night, sends data intermittently

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Battery Test Set Up

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Battery Test Results

E-Tech Li-Ion Polymer Cell, 250mAh, 3.7Vdc Pulsed Discharge, 1 Second Period, 8C=2A

Center for WirelessCOMMUNICATIONS 04/18/23

Battery Tests, Summary

Li-Ion polymer secondary cell, pulsed discharge, 2x useful energy increase vs continuous discharge (charge recovery)

Lithium coin primary cell, pulsed discharge, 8x useful energy increase vs continuous discharge

Pulse constraints for charge recovery: < max on time, >min idle time, <max idle current, high pulse current levels possible, 8x to 80x manufacturer’s recommended current

Improvement scenario: Same weight, same power, much more energy or Same weight, much more power, same energy