1 ENERGY: THE ROOT OF ALL PERVASIVENESS Anthony Ephremides University of Maryland April 29, 2004

2 “PERVASIVE” NETWORKING Ability to access the network (“Anywhere,” Anytime,” “Anyone”) Focus on wireless More specifically: Ad Hoc (multihop)

3 KEY ELEMENTS Wireless Channel fading interference SINR Portable Energy Supply efficiency vs. limited –‘SOFT” – LINK GRAPHS –CROSS-LAYER COUPLING > <

4 TWO ILLUSTRATIONS 1.MAC/ROUTING with Energy Metrics 2.Processing vs. Transmission in Sensor Networks

5 MAC/ROUTING Routing algorithm flows on each link MAC assigns resources to competing flows Actual link throughput depends on MAC New link quality metric values Routing Algorithm new flows

6 MULTI-HOP AD HOC NETWORK Single channel – slotted time Separate control channel Single transceiver per node Power control - P max –regulate interference –save energy Simple attenuation model –free-space, distance based SINR < >

7 Scheduling Rules: A node can only be associated with one active link at a time. SIR requirements are satisfied. The link with the lowest metric has the top priority. SCHEDULING

8 Scheduling Algorithms: 1. Power is preset. Links are added (if SIRs are satisfied) in the order of link metric. Easy for distributed implementation. 2. With iterative power control. Links are added (if SIRs are satisfied) in the order of link metric. Difficult for distributed implementation. 3. First find maximal number of links that can coexist, then run iterative power control. Remove links until SIRs are satisfied. Difficult for distributed implementation.

9 Throughput and Delay for different scheduling algorithms. Simulation Results No rerouting.

10 JOINT SCHEDULING AND ROUTING Routing: Bellman-Ford algorithm with routing distance:

11 CONTROL OF SENSOR NETWORKS Application : Major Driver But, in all cases: Longevity (energy efficiency) Major Challenges: –MAC –Routing (map application-related objective function to link metric or MAC priority)

12 Ignore Routing Component Ignore Routing Component control node SENSOR NETWORK FOR DETECTION DETECTION

13 Simplified Model Each Node Collects Independently T independent Binary Measurements 1 2 K control center MODEL

14 MODEL (cont.) Three Operating Options - Centralized : All data transmitted to CC - Distributed : Each node decides & transmits its decision to CC - Quantized : Each node sends a quantized M-bit quantity to CC where

15 ENERGY CONSUMPTION ANALYSIS - Energy for Data Processing - based on # of comparisons - represents the energy consumed for one comparison - is the # of comparisons - Energy for Transmission - based on the distance from sensor nodes to control center and # of bits transmitted - represents the energy consumed for transmitting one bit data over a unit distance, for a fixed communication system - represents the distance from sensor nodes to control center - is the # of bits transmitted - Total Energy

16 ENERGY CONSUMPTION ANALYSIS (cont.) - Energy Consumption per Node for Three Options - Centralized Option - option 1: transmit all observations to CC - option 2: transmit # of 1 out of T observations to CC - Distributed Option - Quantized Option (suboptimal solution) where represents the expected # of comparisons needed for the suboptimal solution, which is a function of

17 Energy Consumption Analysis (cont.) - Energy Consumption vs. Accuracy fix ; vary example 1: example 2:

18 NEXT STEPS 1.Spatial/Temporal Correlation 2.Routing (map objective function to link metric) 3.Broader measurement model MORE FUNDAMENTALLY 1.Couple processing energy (dictated by the chosen SP algorithm) to the embedded system design. (memory management, signal flow graphs for software vs. hardware split, computing fabric) 2.Trade-off transmission to processing under such “INTERACTIVE” design (ultimate cross-layering)

19 CONCLUSIONS 1.Holistic cross-layer design from energy point of view 2.Application dependency/exploitation 3.“It takes courage to succeed” “It takes energy to be pervasive”