Geography Informed Energy Conservation for Ad Hoc Routing

1. Geography Informed Energy Conservation for Ad Hoc Routing Vijay Raghunathan EE206A (Spring 2001)

2. Mobile and wireless systems are battery operated Extremely stringent energy (battery lifetime) budget Energy efficiency cuts across all layers of abstraction Low-power hardware components Low-power HW/SW synthesis Energy-efficient operating systems Smart applications Battery friendly network protocols Dynamic Power Management (DPM) Shutdown based DPM – Unused, idle components turned off Introduction Energy awareness is the key to long system lifetime

3. Overview • Network level, shutdown based DPM technique for ad-hoc networks • Exploits node redundancy to save energy • On-demand routing protocols (AODV, DSR) are more energy efficient than a priori protocols if idle mode energy is ignored • Energy consumed in idle listening mode is significant

4. Overview (contd.) • Ad-hoc network of wireless nodes • Nodes know their location (GPS) • Traffic nodes and transit nodes 2 4 1 3 5 Nominal Radio Range • Nodes 2, 3 and 4 are equivalent for routing packets from 1 to 5 and hence, two of them can sleep at any given time

5. Determining node equivalence Virtual grid 2 4 1 3 5 r r • Nodes determine their grid Ids using location info • Node 2 should be able to reach node 5. • r2 + (2r)2 R2 • r  R/5

6. D Active Sleeping Ta Td D Ts Discovery State Transitions D: On hearing discovery message from a higher ranked node • Active > Discovery > Sleeping • Only one active node per virtual grid • Expected Node Active Time (ENAT)

7. Main features • Eliminates node redundancy • Balances energy usage between nodes (load balancing) • Set Ta accordingly so that other nodes take over in due time • Adapts to node mobility • Reduce the sleep time Ts (random between ENAT/2 & ENAT) • Include mobility information in discovery message (Expected Node Grid Time) and choose sleep time accordingly • Independent of the routing protocol. However, depends on routing protocol to handle packet loss caused by shutdown of a currently routing node.

8. Evaluation • Data delivery ratio is maintained • Performs well as network density increases • Higher density  More redundancy  Higher energy savings • Consistent even under a more realistic propagation model • Shadowing model • Insensitive to small localization error • Localization error  Similar to mobility related error

9. Results & Discussion • Effect on network lifetime • GAF-1 results in higher lifetime than GAF-2

10. Conclusions • Inter-node (network level) DPM technique • Exploits node redundancy for energy savings • GAF extends network lifetime • Mean energy consumption per node is reduced, for the same time interval • GAF maintains high fidelity (i.e same data delivery ratio and same mean delay as unmodified AODV) at low mobility • At high mobility: • GAF-1: Higher energy savings, Lower fidelity • GAF-2: Lower energy savings, Higher fidelity • Performs well at high node density, under a realistic propagation model and is insensitive to small location errors

11. Conclusions • Choice of network parameters • Total number of nodes: 100, No. of neighbors: 42 Very high connectivity! • Even then, it translates to 2.2 nodes/grid on average  Very low redundancy! • Trade-off: Fault-tolerance vs. Energy consumption • Analysis of the effect on FT due to shutdown • Alternative: A node runs to death and wakes up another node before it dies, through a paging channel (avoids communication overhead)

12. References • T. Simunic, L. Benini, P. Glynn, and G. De Micheli, “Dynamic Power Management for Portable Systems”, Proc. MOBICOM, Aug. 2000. • M. Zorzi, and R. R. Rao, “Energy Management in Wireless Communication”, Proc. WINLAB Wkshp. On 3G Wireless Information Networks, pp. 189-201, Mar. 1997. • M. Stemm, and R. H. Katz, “Measuring and reducing energy consumption of network interfaces in hand-held interfaces”, IEICE Trans. Comm., E80-B8, pp. 1125-1131, Aug. 1997