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Energy Efficient Networking

Energy Efficient Networking. Ramesh R. Rao University of California, San Diego - Ne X tworking’03 - Chania, Crete, Greece , June 23-25,2003 The First COST -IST (EU)-NSF(USA) Workshop on EXCHANGES & TRENDS IN NETWORKING. Introduction. Explosion of wireless devices and applications

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Energy Efficient Networking

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  1. 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 INNETWORKING

  2. 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

  3. Three Themes • Cross-layer optimization • Resource ownership • Batteries

  4. 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

  5. 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

  6. Lifetime Vs. Throughput Optimal Routes Lifetime Optimal Routes Lifetime=1331.6 Throughput: 1 Throughput Optimal Routes Lifetime=839.2 Throughput=1.33

  7. 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

  8. 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 R D S2 S3

  9. 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

  10. 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

  11. Battery Test Set Up

  12. Battery Test Results • E-Tech Li-Ion Polymer Cell, 250mAh, 3.7Vdc • Pulsed Discharge, 1 Second Period, 8C=2A

  13. 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

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