Real- Time Wireless Sensor- Actuator Networks
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1 Real- Time Wireless Sensor- Actuator Networks Abusayeed Saifullah Department of Computer Science
2 Roadmap Ø Real- time transmission scheduling theory for WSAN Dynamic priority Fixed priority - - End- to- end delay analysis Priority assignment Ø Scheduling- control co- design for WSAN Ø CapNet: real- time WSAN for data center power capping Ø WSAN over TV White Spaces 2
3 Wireless Data Center Power Management Power infrastructure in an enterprise data center costs hundreds of millions USD. 42% [Courtesy: J Hamilton, Amazon] Power Other Server 53% Power capping: regulate the power consumption of a cluster of servers. 5% 3
4 Wireless Data Center Power Management Power infrastructure in an enterprise data center costs hundreds of millions USD. 42% [Courtesy: J Hamilton, Amazon] Power Other Server 53% Power capping: regulate the power consumption of a cluster of servers. 5% Management using low- cost wireless Reduced cost: for 100,000 servers, only 5.4%- 8% of the wire solution cost Simple, Ulexible, easily manageable 4
5 Power Capping Ø Cap: circuit breaker s capacity for a cluster of servers Ø Using nameplate power rating à less servers per cluster Power Nameplate rating Servers rarely operate at peak Circuit allocation Actual power consumption 1 week Time Oversubscription: put more servers on a circuit Aggregate power rarely exceeds the cap Power capping: brings the aggregate power consumption back to cap 5
6 Power Capping Real- Time Requirement Long-delay Conventional Tripping Ø Trip time: allowed time duration above the cap Short Circuit Tripped Ø If oversubscription duration > trip time à circuit breaker trips Server shutdowns Power outage Not Tripped Power capping must be done within trip time (deadline) 6
7 Designing Wireless Capping Protocol Ø A naive protocol will repeatedly Collect power consumption data from each server Determine aggregate consumption; do capping if it exceeds cap 7
8 Designing Wireless Capping Protocol Ø A naive protocol will repeatedly Collect power consumption data from each server Determine aggregate consumption; do capping if it exceeds cap Power Power capping is a rare event! Time Interferes with wireless in other clusters/applications! Ø We design a distributed event- driven protocol 1 week Global cap to local cap à local detectionà servers generate alarms Aggregation is done only upon detection of a potential event 8
9 CapNet Design and Implementation Ø CapNet: Wireless Sensor Network for Power Capping Employs conulict- free, event driven protocol Ø Operates in 3 phases Local detection à alarm Aggregation upon k alarms: increase k to suppress false alarms Triggers capping, if the alarms are true start CPU frequency modulation yes Event detection phase Aggregation phase Control phase max. num. of iterations done? no 9
10 CapNet Design and Implementation Ø CapNet: Wireless Sensor Network for Power Capping Employs conulict- free, event driven protocol Ø Operates in 3 phases Local detection à alarm Aggregation upon k alarms: increase k to suppress false alarms Triggers capping, if the alarm is true start Event detection phase Aggregation phase CPU frequency modulation Control phase yes max. num. of iterations done? no Implemented in TinyOS on TelosB platform. 10
11 Power Consumption in a Data Center Rack16 Cluster 2 Rack13 Cluster 1 Rack8 Cluster Rack8 Cluster 1 Rack13 Cluster 1 Rack16 Cluster servers (2880 readings per server) Ø Strong synchrony among the servers in the same cluster Cluster exceeds cap à many servers exceed local capà fast alarm CapNet beneuits from correlation à a practical approach! matrix [i,j]: correlation between i- th and j- th server Microso' Data Center clusters running Web- Search, , Map- Reduce, cloud apps 11
12 Experiment Deployed in Microsoft data center experimental facility TelosB to Server through serial 12
13 Real- Time Performance (480 servers) CDF Capping latency= Network latency { + OS latency ms + Hardware latency Slack= Trip time- capping latency iterations 8 iterations 0 16 iterations Slack considering lower trip times (ms) x 10 6 Not Tripped Long-delay Conventional Tripping Short Circuit Tripped CapNet meets the real- time requirements in capping. 94% transmission suppression compared to the naive protocol! 13
14 Roadmap Ø Real- time transmission scheduling theory for WSAN Dynamic priority Fixed priority - - End- to- end delay analysis Priority assignment Ø Scheduling- control co- design for WSAN Ø CapNet: real- time WSAN for data center power capping Ø WSAN over TV White Spaces 14
15 WSAN over TV White Space Ø WSAN scalability challenge Smart city à hundreds of thousands of nodes Clinical monitoring in large medical systems Ø Approach: WSAN over white spaces 15
16 Sensor Networking over White Space White Spaces: unused UHF/VHF band between MHz Advantage Challenge Long transmission range Wall penetration Energy, real- time requirements Exploit bandwidth and data rate [courtesy: Spectrum Bridge] Spectrum inside a data center 16
17 Sensor Networking over White Space White Spaces: unused UHF/VHF band between MHz Advantage Challenge Long transmission range Wall penetration Energy, real- time requirements Exploit bandwidth and data rate [courtesy: Spectrum Bridge] More than 60% spectra are white spaces < - 85dBm 17
18 Sensor Networking over White Space White Spaces: unused UHF/VHF band between MHz Advantage Challenge Long transmission range Wall penetration Energy, real- time requirements Exploit bandwidth and data rate Availability (counties) Courtesy: SpectrumBridge Fixed (4 W), Portable/mobile (100 mw) Portable/mobile (40 mw) Channel [courtesy: Spectrum Bridge] Spectrum availability based on counties in USA 18
19 Sensor Networking over White Space White Spaces: unused UHF/VHF band between MHz Advantage Challenge Long transmission range Wall penetration Energy, real- time requirements Exploit bandwidth and data rate For sensor network applications that involve [courtesy: Spectrum Bridge] Wide- area sensing: Large civil infrastructure, oil Uield Wall/obstacle penetration: Hospital, industry sensor network 19
20 Conclusion Ø Real- time wireless sensor- actuator network is a reality. Enables cyber- physical systems in industry, home, hospital Ø Our contributions and research impacts Real- time wireless scheduling theory for WSAN Scheduling- control co- design for wireless control CapNet: the Uirst real- time WSAN for data center power capping Ø Vision: large- scale wireless cyber- physical systems Scalable real- time network architecture and protocols Wide- area sensor networking over White Spaces 20
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