University of Massachusetts, Amherst

Triage: Balancing Energy and Quality of Service in a

Microserver

Nilanjan Banerjee, Jacob Sorber, Mark Corner, Sami Rollins†, Deepak Ganesan

http://prisms.cs.umass.edu/hpm

†University of San Francisco, San Francisco

Scenario : Deploying Remote Sensor Network

Imagine you want to deploy a large scale sensor network

What do you need ?lot of sensors of course also need powerful battery-powered server nodes

These nodes are traditionally called Microservers [Girod et al.]

What do these Microservers do ?can be used for routing, query processing or storagecan act as a web server, information kioskcan be used as a router

What does the Microserver Workload look like ?

Workload is often heterogeneous and sporadicsimple requests: store data, synchronize timecomplex requests: return all images with >2 objects

Microserver

MicroserverAcoustic Sensors

Video Sensors

Vibration Sensors

Sensor Node

Wireless Link

Conflicting Goals : Performance and Energy !

Microservers have high performancehighly responsive as a conventional serverprovide performance guarantees to applicationsshould have a powerful CPUshould have lots of RAM

Remember that microservers are untethered and battery poweredthey must be highly energy-efficient for longer lifetime however, powerful platforms implies more energy consumption !

How do we design microservers which balance performance and energy !

MicroserverEnergy

Efficiency Performance

Use a single tiered powerful platformuse PSM and DVFS on the powerful platformsystem suffers from the huge idle cost of the powerful tier

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Possible Approaches

Possible Approaches

Use a dual tier system (similar to Wake on Wireless [Shih et al.])tier-0 (Mote) as low power tier, tier-1 (Stargate) as a more powerful tierkeep Stargate in power down modewake Stargate whenever a task arrives at Motesystem suffers from a huge transition cost of Stargate

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Our Approach : Triage

Combine powerful platform (Stargate) and low power sensor (Mote)Try to amortize transition costs by batching tasks at the sensorThe tasks arriving should meet soft real time deadlines

accurately profile execution time for tasks wake the Stargate platform only for long batch of tasks if possible execute simple tasks on the Mote

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OutlineDesign goals governing the Triage systemOverall Triage ArchitectureTriage components

surrogates profilerscheduler

Triage PrototypeExperimental Setup and EvaluationRelated Work and Conclusions

Design Goals

Triage architecture should be generalapplicable to microservers in wide variety of networks

Triage should be highly responsive to tasks

Triage should provide soft real time QoS guarantee

Triage should be highly energy efficientmaximize lifetime while meeting QoS guaranteesmeet lifetime constraints while providing QoS guarantees

Triage Software Architecture

Tasks arrive at tier-0 (Mote), tier-1 (Stargate) is in low power modeSurrogate services execute tasks or batch (log) them for Stargate Profiler calculates the amount of energy and time taken by a taskScheduler decides when to wake Stargate

Storage Surrogate

Query ProcessingSurrogate

Delayed Request Log/ Cache

Wakeup Control

Forwarding Surrogate

Profiler QoS Scheduler

Tier-0 Subsystem (Mote)

Network Requests

Task 2 Task 1

Hardware Power Measurement

Tier-1 Subsystem (Stargate) Task Execution

SurrogatesStorage Surrogate

enables in-network storage applicationsaccepts reads, writes, and delete requestsrequest are either served from the cache or inserted into log

Query Processing Surrogateprovides query interface for data stored on the microserver queries could be simple or complexeither queries are served from tier-0 or are inserted into log

Forwarding Surrogateefficient routing using tier-0 and tier-1 network interfacesdetermines which radio should be used to send the packetif tier-0 radio is used, packet send immediately

ProfilerMeasures the typical execution time and energy usage of tasks

measurements done through hardware assisted profilingtypical execution time : p % of the requests are likely to be satisfied

Online profiling involves two stepstask grouping – classify tasks based on the nature of taskparameter estimation

Parameter Estimation is the probability distribution of time taken by task

and are the mean and variance of the distribution applying Chebyschev’s inequality execution time of task is bounded by

)( itf

X

SchedulerUses information about tasks from the profiler

Schedules tasks to minimise the number of Stargate wakeups

We could use different scheduling algorithms under different scenarios the focus might be to meet maximum deadlines using minimum energy the aim make the batteries last for a 100 days

Triage uses two example schedulers depending on optimization criterion deadline scheduler : meets maximum deadlines at minimum energy lifetime scheduler : satisfy lifetime constraint and meet max deadlines

Example Scheduler : Deadline Scheduler

Scheduler first queries the profiler for execution time for taskAlgorithm then computes the Batch time (B )

batch time at which Stargate can be woken upall tasks and the new task meets its deadline

Let the new task be inserted at position of the sorted listFor each task , sets the latest start time

New Batch time is equal to B = B – L(Ti)

If B less than or equal to 0 tier-1 is woken up else tier-1 wakeup timer fires after time B

)( iTLiT li1

)}()(),(min{)( 1 iiii TETLTLTL

Deadline Scheduler : ExampleLet there be two batched tasks TA: deadline=60 sec execution=3 sec TB: deadline=64 sec execution=3 sec L(TA) = 57 sec L(TB) = 61 sec B = 50 secNew task TC arrives TC : deadline=62 sec execution=3 secTask is inserted between TA and TB

Pushes task TA forwardNew Batch time B = 48 sec

EB=3D=64L=61

EA=3D=60L=57

64 61 5760

W=7

50

B=50

0

EB=3D=64L=61

EA=3D=60L=55

64 61 5558

W=7 B=48

048

EC=3D=62L=58

Example Scheduler : Lifetime Scheduler

Microserver generates tokensrate of energy constraint

Calculate energy for present batch

If energy greater than tokens collecteddo not wake the Stargate

Else wake Stargate to execute batch

new new tokenstokens

Battery Capacity

?

Tasks

Batch Taken

Decide Wakeup of Tier-1

OutlineDesign goals governing the Triage systemOverall Triage ArchitectureTriage components

surrogates profilerscheduler

Triage PrototypeExperimental Setup and EvaluationRelated Work and Conclusions

Triage Prototype

StargateTelosB

Power Profiling Board

Battery

Evaluating TriageDoes Triage have power savings over other systems

single tiered system which uses PSM and DVFS (PSM-DVFS)dual tier system based on the Wake-on-Wireless (WoW*)dual tier system which used batching at tier-0 (Triage-Batch)

What benefit do tier-0 surrogates provide ?

How does the profiler perform ?

Do the scheduler algorithms meet their objective ?

What are the potential bottlenecks in the Triage system ?

Experimental Setup : Camera Sensor Network

CLIENT

BASE STATION

MICROSERVER

SENSOR CAMERA

802.15.4 Link

802.11b Link

PRINT

HELP

ALPHA

SHIFT

ENTERRUN

DG ER FI

AJ BK CL

7M 8N 9O

DG DG DG

DG T 3U

0V .WX Y Z

TAB

% UTILIZATION

HUB/MAU NIC

2BNC4Mb/s

NI-PCI 6251 DAQ

TelosB motes act as sensor camerasTelosB and laptop acts as client generating image requests for the microserver

Power measurements taken using a NI-PCI 6251 DAQClient equipped with both 802.11b and 802.15.4 radios

Profiler Performance

Triage consumes slightly more energy than a batching system

Images arrive at constant rateQueries arrive at a regular rate

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Average Latency Constraint (sec)

Ave

rage

Pow

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TriageTriage-Batch

Profiler Performance

Triage system meets more than 90% of all the deadlinesTriage-Batch meets less than 75% of the deadlines

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Triage

Triage-Batch

Lifetime Scheduler Performance

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Lifetime ConstraintTriageWoW*PSM-DVFS

Triage meets the lifetime constraint WoW* and PSM-DVFS batteries die long before the

deadline

Initial battery capacity = 100 mAh , lifetime constraint = 1hr First 30 mins : tasks with long deadlines, 30-60 mins : tasks with short deadlines

System Bottlenecks

The USB transfer energy is a huge bottleneck on Triage !

Triage leads to 300% improvement in battery lifetime

Triage WoW* PSM-DVFS0

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1200A

vera

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ower

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W)

TelosBSuspendTransitionUSB-TransferWifi+computeStargate-idle

Related WorkWake-On-Wireless [Shih et al.]

low-power radio receives wakeup messagesrequires in-network supportfocus on when to wake up

Wireless optimizations [Anand et al.]Disk Spindown [Helmbold et al.]Multiple radios [Pering et al.]Multiple processor cores [Mayo & Ranganathan]

none provide orders-of-magnitude scaling of powerm-Platform [MSR06-142], LEAP [IPSN06] and LEAP2

heterogenous stack-based sensor network platformno intelligent profiling or scheduling to decide high power tier wakeups

Microserver platforms throwboxes [infocom 07]

Conclusions

We presented Triage : a highly capable, energy efficient microserver

Triage uses Hierarchical Power Managementintegrate multiple independent platformspass control between tierssuspend unneeded tiers

Triage leads to 300% improvement in battery lifetimeTriage meets all lifetime goals and provides probabilistic QoSTriage used for building highly energy efficient microservers

application in sensor deployment, mobile computing

University of Massachusetts, Amherst

Triage: Balancing Energy and Quality of Service in a

Microserver

Nilanjan Banerjee, Jacob Sorber, Mark Corner, Sami Rollins†, Deepak Ganesan

http://prisms.cs.umass.edu/hpm

University of San Francisco, San Francisco