Energy-efficient Capture of Stochastic Events by Global- and Local-periodic Network Coverage David...
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Energy-efficient Capture of Stochastic Events by Global- and Local-periodic Network Coverage
Energy-efficient Capture of Stochastic Events by Global- and Local-periodic Network Coverage
David K. Y. YauDavid K. Y. Yau
SensorNet: Plume Detection by In-situ Sensor Network
MotivationsMotivations
Unattended operation of many low-cost and small form factor sensors Dense static network Uncontrolled (random) placement Significant overlap in sensing regions
Possibility to duty-cycle sensors to save energy Eliminate redundant coverage Load balance between sensors for maximum network
lifetime
Unattended operation of many low-cost and small form factor sensors Dense static network Uncontrolled (random) placement Significant overlap in sensing regions
Possibility to duty-cycle sensors to save energy Eliminate redundant coverage Load balance between sensors for maximum network
lifetime
Motivations (cont’d)Motivations (cont’d)
Exploitation of real-world event properties and dynamics Events may stay and hence can be captured with delay
by (q,p)-periodic sensor When events stay, “quality of monitoring” may be
much higher than q/p high energy saving potential If p small enough, arbitrarily high fraction of events can be
captured no matter how small q/p (q,p) schedule can be optimized for maximum
event/information capture given event dynamics
Exploitation of real-world event properties and dynamics Events may stay and hence can be captured with delay
by (q,p)-periodic sensor When events stay, “quality of monitoring” may be
much higher than q/p high energy saving potential If p small enough, arbitrarily high fraction of events can be
captured no matter how small q/p (q,p) schedule can be optimized for maximum
event/information capture given event dynamics
BasicsBasics
Stochastic event arrivals/departures at each PoI Distribution of event staying times X Distribution of event absent times Y X and Y for same event may be dependent; but different events are
i.i.d.
Capture of events by sensor of range r (binary perfect-disk model) Anisotropic sensing is possible without affecting main conclusions
Many sensors placed according to Poisson Point Process of intensity ; may communicate within given wireless range
Stochastic event arrivals/departures at each PoI Distribution of event staying times X Distribution of event absent times Y X and Y for same event may be dependent; but different events are
i.i.d.
Capture of events by sensor of range r (binary perfect-disk model) Anisotropic sensing is possible without affecting main conclusions
Many sensors placed according to Poisson Point Process of intensity ; may communicate within given wireless range
Basics (cont’d)Basics (cont’d)
Sensors can be turned on/off (as a whole) Energy model: energy rate of k1 when on, k2 when off;
constant energy c to switch between on/off In principle, sensing/communication/computation can
be independently controlled Performance metrics (Step utility function)
Probability of instantaneous event capture Pin (over all events that could be captured only)
Probability of event capture (with or without delay) Pc Other types of events (utility functions) can be analyzed
Sensors can be turned on/off (as a whole) Energy model: energy rate of k1 when on, k2 when off;
constant energy c to switch between on/off In principle, sensing/communication/computation can
be independently controlled Performance metrics (Step utility function)
Probability of instantaneous event capture Pin (over all events that could be captured only)
Probability of event capture (with or without delay) Pc Other types of events (utility functions) can be analyzed
Energy Efficiency TechniquesEnergy Efficiency Techniques
(q,p)-periodic sensor schedule to exploit event dynamics (mainly, staying times)
Coordinated sleep between sensors to eliminate redundant coverage Sensor x is redundant if its sensing region is completely
covered by those of its active neighbors (conservative condition)
Sensors exchange their location, active schedule, remaining energy, etc (Hello protocol)
Safe to turn off x without affecting performance Different neighbors can go to sleep at different times;
permission to sleep renegotiated for energy balance
(q,p)-periodic sensor schedule to exploit event dynamics (mainly, staying times)
Coordinated sleep between sensors to eliminate redundant coverage Sensor x is redundant if its sensing region is completely
covered by those of its active neighbors (conservative condition)
Sensors exchange their location, active schedule, remaining energy, etc (Hello protocol)
Safe to turn off x without affecting performance Different neighbors can go to sleep at different times;
permission to sleep renegotiated for energy balance
Coordinated Sleep ProtocolCoordinated Sleep Protocol
Sensor roles Regular, supporting, redundant
Regular sensors identify their support sets regularly; a sensor ranks support set by Minimum residual energy (energy balance) Overlap of active time between itself and
support members (maximally productive sleep; in particular, a > 2 c / (k1 - k2))
Sensor roles Regular, supporting, redundant
Regular sensors identify their support sets regularly; a sensor ranks support set by Minimum residual energy (energy balance) Overlap of active time between itself and
support members (maximally productive sleep; in particular, a > 2 c / (k1 - k2))
Example Support SetExample Support Set
J
B
C
A
IH
G
D
EF
A’s support sets:
C, D, H, I
D, F, H, I
Hello message
Negotiation of Permission to SleepNegotiation of Permission to Sleep
J
B
C
A
IH
G
D
E
F
Request to sleep (RTS)
Clear to sleep (CTS)
Confirm (CNF)Supporting
Redundant
If two neighbors both want to go to sleep, they defer sending CTSby random delay (probabilistically longer if less remaining energy)
Syncrhonous and Asynchronous Periodic Network
Syncrhonous and Asynchronous Periodic Network
Synchronous periodic network All sensors start their (q,p) schedule at the same time (global-periodic) Network of sensors behave as one big periodic sensor Maximum coordinated sleep opportunities Leverage lightweight time synchronization protocols
Asynchronous periodic network Each sensor starts (q,p) schedule at an independent random point in
time (local-periodic) Spread-out on periods for better event capture Reduced coordinated sleep opportunities (less temporal redundancy) Zero coordination for periodic operation
Synchronous periodic network All sensors start their (q,p) schedule at the same time (global-periodic) Network of sensors behave as one big periodic sensor Maximum coordinated sleep opportunities Leverage lightweight time synchronization protocols
Asynchronous periodic network Each sensor starts (q,p) schedule at an independent random point in
time (local-periodic) Spread-out on periods for better event capture Reduced coordinated sleep opportunities (less temporal redundancy) Zero coordination for periodic operation
Coordinated Sleep OpportunitiesCoordinated Sleep Opportunities
Spatial redundancy Deployment density
Temporal redundancy Overlapping q active time for synchronous
periodic scheduling Opportunistic overlapping time for
asynchronous periodic scheduling Higher q higher overlap probability
Spatial redundancy Deployment density
Temporal redundancy Overlapping q active time for synchronous
periodic scheduling Opportunistic overlapping time for
asynchronous periodic scheduling Higher q higher overlap probability
Design PointsDesign Points
Periodic scheduling can be used together and orthogonally with coordinated sleep
Four design points Synchronous network with/without coordinated
sleep Asynchronous network with/without
coordinated sleep
Periodic scheduling can be used together and orthogonally with coordinated sleep
Four design points Synchronous network with/without coordinated
sleep Asynchronous network with/without
coordinated sleep
Energy-aware Optimization of Synchronous Network
Energy-aware Optimization of Synchronous Network
Required Pin specified by user
Pc of single sensor given by [CoNext 2008]
Required Pin specified by user
Pc of single sensor given by [CoNext 2008]
Pc as function of pPc as function of p
For Step utility,Pc monotonically decreasing in p(full information captured instantaneously no need to remain on)
Information Capture under Limited Energy
Information Capture under Limited Energy
When energy also considered, extremely fine q/p wastes energy to turn on/off the sensor frequently optimal event capture per unit of energy occurs at intermediate p
Energy model: k1 q + k2 (p - q) + 2c
Standard techniques apply for single dimension optimization of continuous function
Analysis of Capture DelayAnalysis of Capture Delay
Capture Delay for Exponential Staying times
Capture Delay for Exponential Staying times
Illustration of Capture DelayIllustration of Capture Delay
Event Capture of Asynchronous Network
Event Capture of Asynchronous Network
Events not captured by one sensor may be captured by another sensor All sensors within distance r of event are
“within range” Consideration for all in-range sensors needed By Poisson Point Process, probability of k such
sensors given by
Events not captured by one sensor may be captured by another sensor All sensors within distance r of event are
“within range” Consideration for all in-range sensors needed By Poisson Point Process, probability of k such
sensors given by
Non-capture Probability by One SensorNon-capture Probability by One Sensor
For Pin, simply 1 - q/p
For Pc, given by
Hence, we have …
For Pin, simply 1 - q/p
For Pc, given by
Hence, we have …
Probability of Instantaneous Capture (Asynchronous Network)
Probability of Instantaneous Capture (Asynchronous Network)
Probability of Capture(Asynchronous Network)
Probability of Capture(Asynchronous Network)
Optimization of Asynchronous NetworkOptimization of Asynchronous Network
User-specified Pin q/p (Theorem 3)
Pin increases linearly with q/p for synchronous network, but
Increase is exponential for asynchronous network
Optimization of p given q/p (Theorem 4)
User-specified Pin q/p (Theorem 3)
Pin increases linearly with q/p for synchronous network, but
Increase is exponential for asynchronous network
Optimization of p given q/p (Theorem 4)
Pin as Function of q/p (Asynchronous Network)
Pin as Function of q/p (Asynchronous Network)
Optimization of QE as Function of p (Asynchronous)
Optimization of QE as Function of p (Asynchronous)
Network SimulationsNetwork Simulations
Synchronous network With coordinated sleep (S-CSP) Without coordinated sleep (S-nc)
Asynchronous network With coordinated sleep (A-CSP) Without coordinated sleep (A-nc)
Role-alternating, Coverage-preserving protocol (RACP) [Hsin & Liu, IPSN 2004]
Synchronous network With coordinated sleep (S-CSP) Without coordinated sleep (S-nc)
Asynchronous network With coordinated sleep (A-CSP) Without coordinated sleep (A-nc)
Role-alternating, Coverage-preserving protocol (RACP) [Hsin & Liu, IPSN 2004]
A-nc vs. RACPA-nc vs. RACP
=4, required Pin = 0.99+ q/p=0.4
A-nc has 75% longer network lifetime, w/ little loss in Pin
A-nc requires no zero synchronization between sensors
A-nc achieves perfect load balancing (trivially)
A-CSP vs. RACPA-CSP vs. RACPA-CSP starts to die at about same time as A-nc, but …
Death is much more gradual
A-CSP has less good load balancing as RACP, because shifted on periods reduce chance for coordinated sleep
S-CSP vs. RACP (Probability of Instantaneous Capture)
S-CSP vs. RACP (Probability of Instantaneous Capture)
Pin = 0.4 q/p = 0.4
S-CSP achieves required Pin
S-CSP lasts twice as long as RACP tradeoff between performance and energy efficiency
S-CSP vs. RACP(Probability of Capture)
S-CSP vs. RACP(Probability of Capture)
S-CSP closes perfomance gap significantly in terms of event capture (0.8 vs. 0.4), because …
S-CSP is designed to take advantage of event staying time to work less hard and capture events at a delay
S-CSP vs. A-CSP(Probability of Capture)S-CSP vs. A-CSP
(Probability of Capture)S-CSP starts to die later because aligned on periods provide maximum sleep opportunities, but …
A-CSP achieves better event capture almost all the time, in spite of its degraded performance earlier
S-CSP vs. S-ncS-CSP vs. S-nc
Coordinated sleep prolongs network lifetime by about 1/3
Coordinated sleep achieves pretty good load balancing (complete network death happens rather quickly, cf. asynchronous network)
Summary of ResultsSummary of Results
Synchronous network provides performance/energy tradeoff by exploiting event staying time to capture events at a delay If user is willing to relax requirement on Pin (so we can use
smaller q/p) Performance gap closes significantly in terms of Pc
At low/moderate density, asynchronous network provides similar tradeoff, but tradeoff becomes more attractive Pin increases exponentially w/ q/p (cf. linear increase for
synchronous network)
Synchronous network provides performance/energy tradeoff by exploiting event staying time to capture events at a delay If user is willing to relax requirement on Pin (so we can use
smaller q/p) Performance gap closes significantly in terms of Pc
At low/moderate density, asynchronous network provides similar tradeoff, but tradeoff becomes more attractive Pin increases exponentially w/ q/p (cf. linear increase for
synchronous network)
Summary of Results (cont’d)Summary of Results (cont’d)
For high-density asynchronous network, tradeoff becomes mostly not necessary Loss of Pin is very small Gain in network lifetime is quite large
Asynchronous network provides better performance than synchronous network, but …
Asynchronous network provides less chance for coordinated sleep (load balancing also less effective)
For high-density asynchronous network, tradeoff becomes mostly not necessary Loss of Pin is very small Gain in network lifetime is quite large
Asynchronous network provides better performance than synchronous network, but …
Asynchronous network provides less chance for coordinated sleep (load balancing also less effective)
Related WorkRelated Work
Offline computation of subsets of k-cover sensors [Slijepcevic & Potkonjak 01] Not adaptive to dynamic networks
Online coordinated sleep protocols [Hsin & Liu 0; Yan, He & Stankovic 03; Tan & Georganas 02] Don’t consider event dynamics and optimization of periodic
networks
Network optimization for dynamic events [Bisnik, Abouzeid & Isler 06; Yau et al. 08] Sparse mobile sensor networks; no on-line sensor coordination
Offline computation of subsets of k-cover sensors [Slijepcevic & Potkonjak 01] Not adaptive to dynamic networks
Online coordinated sleep protocols [Hsin & Liu 0; Yan, He & Stankovic 03; Tan & Georganas 02] Don’t consider event dynamics and optimization of periodic
networks
Network optimization for dynamic events [Bisnik, Abouzeid & Isler 06; Yau et al. 08] Sparse mobile sensor networks; no on-line sensor coordination