CS 851 Presentation: Differentiated Surveillance for Sensor Network Presented by Liqian Luo Reference: 1. T. Yan, T. He, and J. A. Stankovic, “Differentiated.

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Presentation transcript:

CS 851 Presentation: Differentiated Surveillance for Sensor Network Presented by Liqian Luo Reference: 1. T. Yan, T. He, and J. A. Stankovic, “Differentiated Surveillance for Sensor networks”, First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003), Los Angeles, CA 2003

Assessment of the Paper Pros  The first algorithm to guarantee different degrees of coverage for different requirements  Good performance in power conservation and balancing Cons  Pessimistic degree of coverage estimation  Lack of flexibility Require clock synchronization; Do not support mobility; work/sleep schedule never changes after decided; Expensive fault tolerance

Outline Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Problem statement How to provide sensing coverage for a sensor network in a power-efficient way?

Problem statement – Sensing Coverage

Problem statement – Degree of Sensing Coverage Current solutions regard the sensing coverage to a certain geographic area as a binary. This paper argues that higher degree of sensing coverage is desired to obtain high detection confidence since individual nodes are not reliable F T T

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Differentiated surveillance solution – Introduction Degree of coverage (DOC) Differentiated surveillance  Providing different degrees of sensing coverage for a sensor network according to different requirements 0 1 2

Differentiated surveillance solution – Introduction DOC = 1DOC = 2

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Differentiated surveillance solution – Design Goals Provide energy efficient sensing coverage for a geographic area covered by sensor nodes  extend system life Reduce total energy consumption Reduce energy consumption variation among nodes  provide differentiated surveillance

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

r Differentiated surveillance solution – Assumptions Each node knows its own location and nodes are not moving. Neighboring nodes are roughly time synchronized. The sensing area of a node is a circle with radius r centered at the location of this node. Radio radius is larger than 2r < 2r

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Basic design without differentiation – Goal Goal: find a work-sleep schedule for each node which achieves 100% Sensing coverage guarantee. Ideally we should consider each point in the area when do scheduling, but it is impossible because the number of points is infinite. What can we do? For EACH POINT p in a certain geographic area, Guarantee that at ANY TIME, p is covered by at least one node’s sensing range.

Basic design without differentiation – 100% sensing coverage Solution – 100% Grid point sensing coverage  Divide whole network into grids  For each grid point x, guarantee that x is covered by at least one node’s sensing range at ANY time r

Basic design without differentiation – 100% sensing coverage 100% Grid point sensing coverage = 100% sensing coverage guarantee? No. r r r r

Basic design without differentiation – 100% sensing coverage Solution – Conservative sensing radius (Rc)  Rc = r – d/  For each grid point x, guarantee that x is covered by at least one node’s conservative sensing range at ANY time. d Rc Rc Rc Rc r

Basic design without differentiation - decide working schedule A schedule example If we want to provide sensing coverage for point x, we can have either A or B or C awaken. B A C Point x Node A Node B Node C WakingSleeping time A scheduling example of A, B and C

Basic design without differentiation – decide working schedule Challenge: For each node, how to coordinate with other nodes and decide its own schedule?  Solution - Random Reference Point Scheduling Algorithm

Basic design without differentiation – decide working schedule Concepts  Initialization Phase In this phase, nodes find their own positions, synchronize time with neighboring nodes and decide their own working schedule.  Sensing Phase Nodes enter this phase after initialization phase and choose to sense or sleep according to their schedules.  Sensing Round - T Sensing phase is divided into sensing rounds with equal duration T. A node has the same schedule for each round. Decide working schedule for sensing round T

Basic design without differentiation – decide working schedule Concepts  A node’s working schedule is determined by Four parameter tuple – (T, Ref, Tfront, Tend) Ref: a random time reference point chosen by a node within [0, T) Tfront: the duration of time prior to Ref Tend: the duration of time after Ref. By this tuple, A node’s working period is determined as follows:  [T*j + Ref – Tfront, T*j + Ref + Tend) And all the other time the node is sleeping.

Basic design without differentiation – decide working schedule Solution – Random Reference Point Scheduling Algorithm 1) Each node N chooses a “Reference Point (Ref)” randomly from [0, T) and broadcasts its Ref and position. e.g. T = 100, RefA = 40, RefB= 90, RefC = 20 2) For each grid point P in its own sensing area, N sorts all the Refs from nodes (including N) which can also sense P in ascending order. For A according to point P1, we have: Ref(1) = RefC = 20, Ref(2) = RefA = 40, Ref(3) = RefB = 90 B A C Point P1 0 refCrefA refB

Basic design without differentiation – decide working schedule 3) Assuming RefN is the (i)th Ref, N’s four parameter tuple is computed as follows: TfronN = (Ref(i)- Ref(i-1))/2,1<i<M TendN = (Ref(i+1)-Ref(i))/2,1<i<M TfrontA = (Ref(2)-Ref(1))/2 = (40-20)/2 = 10 TendA = (Ref(3)-Ref(2))/2 = (90-40)/2 = 25 (T, RefA, TfrontA, TendA) = (100, 40, 10, 25) 4) N’s working period for point P (TwN(P)) is decided by: [T*j + RefN – TfrontN, T*j + RefN + TendN), j = 0, 1, 2, … TwA(P1) = [100*j+40–10, 100*j+40+25) = [100*j+30, 100*j+65) 0 refCrefArefBrefC t t

Basic design without differentiation – decide working schedule 5) Calculate the union of TwN(Px) for all grid points within N’s sensing area, choose this union as the final working period of N (TwN). TwA(P1) TwA(P2) TwA(P3) TwA(Pn) TwA …

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Enhanced design with differentiation Provide different DOC according to different requirements DoC = 3 DoC = 2 DoC = 1

Enhanced design with differentiation Goal  provide sensing coverage with DOC = a Solution  Extend 4-parameter tuple to 5-parameter tuple (T, Ref, Tfront, Tend, a)  Determine a node’s working period as follows: [T*j + Ref – Tfront*a, T*j + Ref + Tend*a)

Enhanced design with differentiation – An example Schedule for Grid Point P1 (a=1) B A C Point P1 (T, RefA, TfrontA, TendA) = (100, 40, 10, 25) (T, RefB, TfrontB, TendB) = (100, 90, 25, 15) (T, RefC, TfrontC, TendC) = (100, 20, 15, 10) TwA = [T*j + Ref – Tfront, T*j + Ref + Tend) = [100*j + 30, 100*j + 65) TwB = [100*j + 65, 100*j + 105) TwC = [100*j + 5, 100*j + 30) A refCrefArefB C B

Enhanced design with differentiation – An example Schedule for Grid Point P1 (a=2) (T, RefA, TfrontA, TendA, a) = (100, 40, 10, 25, 2) (T, RefB, TfrontB, TendB, a) = (100, 90, 25, 15, 2) (T, RefC, TfrontC, TendC, a) = (100, 20, 15, 10, 2) TwA = [T*j + Ref – Tfront*2,T*j + Ref + Tend*2) = [100*j + 20, 100*j + 90) TwB = [100*j + 40, 100*j + 120) TwC = [100*j -10, 100*j + 40) A refCrefArefB C B Question - Can the algorithm guarantee 100% DOC>=2 sensing coverage by setting a=2? Answer - Yes

Enhanced design with differentiation – An example Schedule for Grid Point P1 (a=3) (T, RefA, TfrontA, TendA, a) = (100, 40, 10, 25, 3) (T, RefB, TfrontB, TendB, a) = (100, 90, 25, 15, 3) (T, RefC, TfrontC, TendC, a) = (100, 20, 15, 10, 3) TwA = [T*j + Ref – Tfront*3,T*j + Ref + Tend*3) = [100*j + 10, 100*j + 115) = T TwB = [100*j + 15, 100*j + 135) = T TwC = [100*j -25, 100*j + 50) A refCrefArefB C B Question - Can the algorithm guarantee 100% DOC>=3 sensing coverage by setting a=3? Answer - No

Enhanced design with differentiation – An extension to guarantee 100% DOC>=a A refCrefArefB C B My Extension to guarantee 100% DOC>=a sensing coverage  Separate the time line into segments by using Refs and the middle points between Refs  Instead of expanding Tw by its own Tfront or Tend, expand one segment on both sides when a is increased by 1.

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Optimizations and Extensions – Second Pass Optimization Existing Problem  Taking the union of Tw for all grid points within sensing range as final Tw will be more than efficient to provide coverage guarantee Solution  make a second pass optimization to reduce the redundancy B A 1 2 TwA(1) TwA TwB(1) TwB(2) TwB

Optimizations and Extensions – Second Pass Optimization Second Pass Optimization 1)After getting the final Tw, each node sends it to neighbors within the distance of 2r 2)Within 2r neighbors that have not recalculated their Tw, the one with the longest Tw recalculates its Tw and sends it to 2r neighbors 3) Repeat 2) until everyone has recalculated its Tw. Why not the one with the shortest Tw? B A 1 2 TwA(1) TwA TwB(1) TwB(2) TwB

Optimizations and Extensions – Multi- Round Extension for Energy Balance Existing Problem  Reference points are selected randomly instead of uniformly, which results in big variation in Tw among nodes and big variation in power consumption. Solution  Multi-Round Extension TwA TwC TwB refCrefBrefA

Optimizations and Extensions – Multi- Round Extension for Energy Balance Multi-Round Extension  Instead of calculating a single schedule, calculate M schedules according to M independently selected random Refs for each node.  At each round T in sensing phase, the nodes choose one schedule consecutively. TwA1 TwA2TwA3TwA2TwA3

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Related Work – Communication Coverage SPAN, ASCENT: providing a communication coverage within an energy conservation context

Related Work – Sensing Coverage 1 Energy Efficient Robust Sensing Coverage: a probing-based mechanism  After a sleeping node wakes up, use a probing message to see whether there is another node working within its sensing area. If no, it takes the responsibility of sensing until it dies. Drawbacks  Overestimate neighbor’s contribution, so no guarantee on sensing coverage a b

Related Work – Sensing Coverage 2 A Node Scheduling Scheme for Energy Conservation: sponsored coverage scheme  At the beginning of each round, each node advertises its position to neighbors  After receiving neighbors’ position advertises, each node calculates its eligibility for going to sleep. Here, a back-off scheme is used to avoid simultaneous actions of multiple nodes.

Related Work – Sensing Coverage 2 Drawbacks  Require broadcasting at the beginning of each round  Underestimate the area that the neighbor nodes can cover

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Evaluation - Introduction Nodes are distributed with a uniform random distribution in a 160 X 160 rectangle Guarantee sensing coverage in the inner 140 X 140 rectangle to eliminate the edge effect sensing radius = 10, communication radius =

Evaluation 1 – Energy Conservation Total Energy Consumption per Unit of Time Sponsored Coverage Basic Design 2 nd Pass Optimization

Evaluation 1 – Energy Conservation Single Node Energy Consumption: Standard Deviation Sponsored Coverage Basic Design Multiple Round Extension ?

Evaluation 1 – Energy Conservation Half-life of the network Sponsored Coverage Basic Design 2nd Pass Optimization

Evaluation 2 – Sensing Coverage Actual Degree of Coverage for Differentiated Surveillance

Roadmap Problem Statement Differentiated Surveillance solution  Introduction  Design goals  Assumptions  Basic design without differentiation  Enhanced design with differentiation Extensions and Optimizations Related Work Evaluation Conclusion and Discussion

Conclusion  Novelty - guarantee not only full sensing coverage to a certain geographic area, but also sensing coverage with specific degree of coverage.  Scalability - localized distributed algorithm  Power management - Good job in energy conservation and balancing  Robustness - fixed schedule throughout the life time, expensive fault tolerant extension, can not work without clock synchronization, can not support mobility ?

Conclusion and Discussion Discussion 1  This solution can not guarantee certain degree of coverage more than 2. Discussion 2  Each node chooses its Ref randomly. What if multiple neighbors have the same Refs?  A simple solution is to order the same Refs by node ID.

Conclusion and Discussion Discussion 3  In initialization phase, each node should send out Ref broadcast and should receive all Refs from 2r neighbors. It is very hard in high density sensor network. So there must be some nodes which are ignored and have not attended the scheduling algorithm in initialization phase.  An extension, which allows these nodes to attend the scheduling later, is necessary.

Conclusion and Discussion Discussion 4  Each node decides its working schedule only based on sensing coverage. Some other layer protocols or applications may need a different working schedule. How to integrate with other working schedule will be a big problem.

Conclusion and Discussion Discussion 5  The baseline - Sponsored coverage scheme can provide fault-tolerance and support certain mobility since it updates neighbor hood information every round  DS without the expensive fault tolerance scheme can not provide fault-tolerance at all  So it is unfair to compare the power consumption between DS without fault-tolerance and the baseline with fault-tolerance.

Thanks!