Energy-Efficient Design Some design issues in each protocol layer Design options for each layer in the protocol stack

Energy Consumption Here are some results on energy consumption of networking hardware: Device Sleep power (mW) Idle/Wakeup Power (mW) wakeup time (ms) WaveLAN Metricom / IBM IR Newton PDA N/A Magic link PDA N/A Laptop 8000

Energy Consumption WaveLAN: transmission power : reception power = 1.4 : 1 Rockwell sensors: transmission power : reception power = 4:3 (full range); 1:1 (min range) Berkeley’s motes: operate at around 10mW.

Mechanisms to reduce power at physical layer First-order approximation of the power consumption of CMOS circuitry: –P = C * V^2 * f (C: effective switch capacitance; V is the supply voltage; f is the clock frequency) Ways to reduce power: –Reduce the supply voltage V; (cons: may reduce performance at the same time, need perf. compensation) –Reduce the switching frequency f (sleep/idle mode); (cons: no energy reduction due to longer runtime) –Reduce the capacitive load C Reduce external access (output, memory, etc.) Reduce logic state transitions, routing capacitance

Reducing power at MA C and link layer Principles: –Only power on when transmitting –Increase the ratio of effective transmissions and avoid retransmissions, collisions, corruptions –regulate traffic Mechanisms to achieve it –Add idle/sleep mode in the transmission state diagram –Regularize transmissions and make them predictable, nodes can sleep when not transmitting –Avoidance contention loss, congestion loss, retransmissions, error-prone transmissions, as much as possible how to achieve ??

Reducing Power at Network Layer Principles: –Put routers that do not forward packets into sleeping mode SPAN, GAF, PEAS –Reduce signaling packets (e.g. LSP) –On-demand routing –Packet size and fragmentation –Energy-related optimality criteria –System decomposition: do not stress energy-critical nodes, load balancing –Use intermediate nodes as middleman Key issues: –How to guarantee connectivity

PEAS: Probing Environment, Adaptive Sleeping Enable long-lived system by exploiting the scale How? –Keep a subset working, turn off the others into sleeping mode –Sleeping ones replace dead ones Two issues –working nodes should be evenly distributed across the field: Probing Environment –Replace failed or energy-exhausted working nodes quickly: Adaptive Sleeping

Distribute working nodes evenly: Probing Environment Nodes are in sleeping initially –An exponential random time When waking up, a node probes within a range R_p –If there is no working node within R_p, it starts working –Otherwise, the working one should send back a reply and this one sleeps again

Peas model: why working node are evenly distributed Any topology of working nodes is equivalent to placing round peas of radius R_p/2 on a plane –The centers of two peas are at least R_p apart, when they’re tangent Assuming infinite deployment density –The densest case: each pea is tangent to 6 neighboring peas –the sparsest case: the space among any 3 adjacent peas is slightly smaller to insert another pea

Detect unpredictable failures: randomized sleeping times If wakeups are synchronized to some time points –long “gaps” if a working one fails unexpectedly Randomized sleeping times spread wakeups over time –Any unexpected failure is detected on time

How to adjust the wakeup rates A working node measures the aggregate wakeup rate from its probing neighbors and includes the information in the replies to probing neighbors Each probing neighbor adjusts its rate accordingly Ts Time K wakeups … Measure aggregate rate: _a = K / (t - t0) t0 t Each probing one adjusts: _new = ( _d / _a )

Reducing power at the transport layer Principles: –Avoid packet loss and retransmissions –Reduced-power operations during backoffs –Light-weight connection management –Design balance at the sender and the receiver Mechanisms –State estimation: Do not transmit during channel errors –Congestion avoidance: Do not overload the network –Buffering

Reducing Power in the OS (including the FS) Principles: –Predictable schedules –Caching –Turn off idle devices (e.g. displays) –CPU scheduling via dynamic voltage scaling Mechanisms: –CPU scheduler: idle state –Use application hints & semantics