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DEAR: Delay-bounded Energy-constrained Adaptive Routing in Wireless Sensor Networks
Shi Bai, Weiyi Zhang, Guoliang Xue, Jian Tang, and Chonggang WangUniversity of Minnesota, AT&T Lab, Arizona State University,
Syracuse University, NEC Lab2012 IEEE INFOCOM
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1. Introduction 2. Algorithm
◦ 2.1 Definition◦ 2.2 Problem statement◦ 2.3 DEAR Algorithm
3. Experiment 4. Conclusion
Outline
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Wireless Sensor Networks◦ Key Issue: Energy Consumption
Delay-bounded Energy-constrained Adaptive Routing (DEAR) Problem◦ Adaptive reliability
Splitting the traffic over multiple paths◦ Differential delay
Increased memory and buffer overflow◦ Deliverable energy constraints
Energy consumption of transmitting packet
Introduction
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Def 1. Packet Allocation◦ P is a set of s-BS paths.◦ The aggregated packet of link e is the sum of the
packet allocations on link e of the paths in P: q(e) = ƩL(p)
Def 2. Differential delay◦ dh => the highest path delay
◦ dl => the lowest path delay
◦ => Dp= dh – dl
Definition (1)
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Def 3. Energy Consumption◦ Transmitting energy consumption
E = w*q q => packet size transmitted on link w => Energy consumption of transmitting 1 bit
W=[C*(2^b-1)+F]*(1/b) C => the quality of transmission and noise power F => the power consumption of electronic circuitry
Def 4. Latency/Delay◦ Queuing delay
The time waiting at output link for transmission◦ Transmission delay
The amount of time required to push all of the packet bits into the transmission media
◦ Propagation delay The time takes for the head of the signal to travel from the sender to the
receiver
Definition (2)
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Transmission delay ◦ Ignored transmission and queuing delay◦ Without considering the transmission delay
Allocate of packets have no impact on delivery of packets
Path:p1=(A,B,BS), p2=(A,C,BS), p3=(A,BS) Path delay: d(p1)=2, d(p2)=3, d(p3)=2
Ex a) packet split => p1=10, p3 = 2 Ex b) packet split => p1= 6, p3 = 6
Path delay are the same Differential delay
d(p1)-d(p3) = 2 – 2 = 0
Transmission delay(1)
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◦ Considering the transmission delay Allocations of packets on multiple paths will have
impact on path delays Path delay
d(p1) = Ʃd(e) + ƩƬ(v) Ex a) d(p1) = 2 + (10 pk/(2 pk/s) + 10/2) = 12, d(p3) =
2 + (2/4) = 2.5 Ex b) d(p1) = 2 +(6/2 + 6/2) = 8, d(p3) = 2 + (6/4) =
3.5 Path delay are different
Ex a) Differential delay is 9.5=(12 - 2.5) Ex b) Differential delay is 4.5
Transmission delay(2)
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DEAR(Delay-bounded Energy constrained Adaptive Routing)◦ Seek set of paths P that can provide the following
Delay bounded Energy constrained Adaptive reliability
Graph G=(V, E, b, d, w, β)◦ V represents the set of sensor nodes and BS.◦ E represents the set of links.◦ b represents bandwidth◦ d represents the delay of the path p◦ w represents transmission energy consumption◦ β represents the residual energy of sensor v
Problem Statement
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Delay Bounded◦ Any path p in P must satisfy the differential delay
constraint: dmin ≤ d(p) ≤ dmax
Energy Constrained◦ The energy consumption of transmitting packet for
each sensor i cannot exceed its residual energy level β(i)
Adaptive reliability◦ The size of aggregated packet of all paths in P is no
less than Q : q(P) ≥ Q◦ Route the data such that any single link failure does
no affect more than x% of the total packets
DEAR problem(1)
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Feasible and infeasible solution by Adaptive reliability and delay constraint◦ Ex c) 2,2,8
In case 8 packet drop => 67%◦ Ex d) 6,4,2
In case delay is 8 over between 4 and 5 ◦ Ex e) 2,10
In case 10 packet drop => over 70%
DEAR problem(2)
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IDEAR
Algorithm 1
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Linear Program solution
Restricted Maximum Flow scheme
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ODEAR problem◦ Optimization problem
SPDEAR problem◦ (1+α) approximation algorithm
Algorithm 1
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Graph Transformation(1)
◦ Each u[t] means that node u can transmit packet at time t.
◦ This bandwidth ensures that the packets sent by u at time i can not exceed b(e).
◦ This ensures that only the packet, which arrive at BS no earlier than dmin and no later than dmax.
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Requirement Condition◦ Packet Demand: 12 Packet◦ Reliability requirement x% = 70%◦ Delay requirement: dmin = 2 and dmax = 5
Maximum flow by IDEAR◦ P1=(A[0],B[2],BS[4],BS[5])◦ P2=(A[0],C[3],BS[5])◦ P3=(A[0],BS[3],BS[4],BS[5])◦ P4=(A[0],A[1],BS[4],BS[5])
Graph Transformation(2)
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Fully Polynomial Time Approximation Scheme for SPDEAR◦ Scaling and rounding technique◦ dΘ= ⌊d(e)*Θ⌋ + 1
Algorithm 2
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Approximation algorithm for ODEAR◦ dmin ≥ 0
Algorithm 3
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Efficient Heuristic for DEAR◦ Round the propagation delay of each link◦ dmin and dmax
Algorithm 4
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Network topologies in an 100 * 100 sq The power of Sensor node was randomly
distributed in [16, 20] Bandwidth, propagation delay and
transmission energy consumption of each communication link was randomly distributed in [6,10], [1,5], [1,3]
Result (1)
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Performance of different number of nodes
Results (2)
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Performance of different reliability requirements
Results (3)
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Performance of different packet sizes
Results (4)
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Transmission delay in multipath routing◦ The previous work ignored
Delay-bounded Energy-constrained Adaptive Routing (DEAR)◦ Adaptive multipath routing◦ Energy constraint◦ Differential delay
Conclusion
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Thank you.
Q&A
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