how to make a sensor network live longer?
DESCRIPTION
How to make a sensor network live longer?. Presentator: Yibo Sun Course prof.: Kyoung-Don Kang. Agenda. The definition of Lifetime of sensor networks To make the whole network live longer -- Energy balancing strategy To make an application live longer - PowerPoint PPT PresentationTRANSCRIPT
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How to make a sensor network live longer?Presentator: Yibo SunCourse prof.: Kyoung-Don Kang
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Agenda
The definition of Lifetime of sensor networks
To make the whole network live longer -- Energy balancing strategy To make an application live longer -- Energy optimization for target area
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What is the lifetime?
The time till all nodes die out? The average of nodes’ lifetime? The time for the system to work
properly? The time for an application to work
properly?
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Some definition of Lifetime
[Blough,et al. 02], defines the Lifetime of the sensor network as
min {t1,t2,t3} t1 is the time it takes for the cardinality of the larges
t connected components to drop below c1*n(t), where n(t) is the number of alive nodes at time t
t2 is the time it takes for n(t) to drop below c2*n(0) t3 is the time it takes for the area covered to drop be
low c3*L^d 0 <= c1 ,c2, c3 <= 1
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setting c1 =0 and c2 = 1 corresponds to defining lifetime as the time it takes for the first node to die
setting c1 =1 and c2 =0 corresponds to defining lifetime as the time to network disconnection.
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E.GNode#1 is the only sinkNode#6’s lifetime = The Lifetime
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Definition by coverage ratio
By setting c1=c2=0, and c3=q, then we obtain the definition of network lifetime given in [Zhang,et al. 04] , which defines lifetime as:
the entire interval in which at least q portion of the region R is covered by at least one sensor node. (q =1 indicates full coverage)
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Definition by target node/area [Duarte-Melo, et al. 02] defines the lifetime of a sens
or network as the expected lifetime of any given sensor in the network. In a densely deployed sensor network this definition is extend to be the time until a certain percentage of the sensors died.
In [Ye, et al. 02] The lifetime is defined as the time it takes for the coverage (defined as the ratio of the area covered by working nodes to the total area) to drop below, and never exceed again, a pre-determined threshold.
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“The Lifetime”
Hence, different application has different lifetime definition
“The Lifetime” here is defined by how long the target function unit works properly.
i.e. The lifetime of a subgraph G’(V) in whole graph G(V)
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Target Function Unit The nodes near the event together
with the notes on the route (red line)
The target nodes’ lifetime = The lifetime
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How to make a whole network live longer? Main ideas:
Reduce the total power consumptionEfficiently transmit the data packetsSynchronously consuming all nodes’ ene
rgy [Joongseok, et al, 2005] Maximum lifet
ime is NP-hard!
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Minimum Energy vs. Maximum Lifetime
Lifetime under minimum energy routing is 67% of that under maximum lifetime routing
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Some assumptions
Energy consumption model: consider packet sending and receiving
only Simplified Radio Model:
Radio transceiver, Micro Controller, Energy Source
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In fixed transmit radio power level, energy used to send/receive one bit is
Transmiting a k-bit packet a distance d costs
Receive a k-bit packet costs
In real propagation model, E = k*dc, 2<c<4
bitnJEelec /502//100 mbitpJamp
2) *),()(,( dkkEdkEkEdkE electxamptxelectx
kEkEkE elecrxelecrx *)(( )
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An experiment on lifetime of routing protocols of different category Direct communication protocol Minimum-transmission-energy
routing protocol Clustering
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Direct communication can be generated to protocols based on
multiple base stations or anchor nodes Energy used on sending one k-bit message
is: 2) *),()(,( dkkEdkEkEdkE electxamptxelectx
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MTE Shortest path GPSR Energy used on sending one k-bit message is:
Each node consumes:)'(**))',()((*',( 2
) dEkndkEkEndkE elechopstxamptxelechopstx
)'*(*)',()(',( 2) dEkdkEkEdkE electxamptxelectx
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Clustering Energy consumed when sending a k-bit
message:
Each node consumes:
)*(**)),()((*,(2''''
)'' dEkmdkEkEmdkE elecsclusterhoptxamptxelecsclusterhoptx
)*(*),()(,(2''''
)'' dEkdkEkEdkE electxamptxelectx
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The application dies long before the last node dies!
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How about energy awaring routing? Minimum Total Transmission Power Routing
(MTPR) Attempts to reduce the total transmission power per
packet. Prefers routes with more hops with short transmission
ranges than few hops with longer transmission rage.
Problem: cost more extra energy , delay, not scalable Min-Max Battery Cost Routing (MMBCR)
Consider the remaining battery power of nodes as metric. Nodes with high residual capacity participate in routing
more often. And prefers to choose a path whose weakest node has the maximum remaining power.
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Conditional MMBCR
Set a parameter as threshold, if no node in the chosen route with MMBCR algorithm, whose battery capacity is lower than , MMBCR applied, else, use MTPR.
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Seems end-to-end optimization is not practical.
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Hop-to-Hop Optimization
Take energy consumption in routing metric
NADV [Seungjoon et al, MobiHoc’05] Select neighbors with optimal trade-off be
tween proximity and link cost
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Advance: advantage by greedy option
Normalized Advance: Cost(n) = fraction of successful data tra
nsmission to neighbor n
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GEAR (Geographically and Energy Aware Routing) Each node maintains a neighbor table
Energy levels and locations of each neighbor
Cost to transmit to each neighbor Packet is forwarded to neighbor with s
mallest cost
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Why not balance the energy? Make clusters to be balanced in member
Balanced k-clustering [Soheil, et,al.Sensors 2002]
Make every node to be key nodeLow-Energy Adaptive Clustering Hierarchy
(LEACH) Combine direct communication and MTE
[Martin Haegnni, ISCAS '03 ]
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Balanced K-clustering
Minimum cost flow question, O((n+k)3)
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LEACH
Using randomization to distribute the energy load evenly
Break up operation into rounds Set-up phase
Cluster-head Advertisement Cluster Set-Up Transmission schedule creation
Steady-state phase Data transmission to cluster head Signal prosessing (Data fusion) Data transmission to the base station
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Combine direct communication and MTE Node i transmits locally generated pac
ket to next neighbor with probability ai
,and directly to the sink with bi = 1 - ai .
Incoming packet always forward to the neighbor
Goal: choose ai to achieve energy balancing
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Assume distance between node is the same
By solving
In 5 nodes: b1…b5 are 0.0301,0.0438,0.0694,0.1250,0
In 10 nodes: 14% lifetime increased with an extra energy consumption: 60%~80%
To make all the nodes live same shorter???
1
11
)1)1(()1(i
iki
i
kkii bbiNiabiNE
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How to make an application live longer? Here, “an application” implies it car
es more about a set of nodes instead of allTurn off the redundant nodes down or ma
ke them to sleep…can be a choiceSet priority to different nodes and conside
r as a factor in routing. Thus to divide a subgraph from the graph.
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An application-oriented GPSR version Set a VIP-rate p (0<=p<=1) to every node,
initially 0 Set a threshold h (not carefully
considered!) When event arises, nodes near the spot
are set their priority to a higher value, say 0.8And it send a VIP-awareness packet to its
neighbor
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When an intermediate node want forward a packet
if there exists a greedy option, it compares the VIP-ratesIf higher, then do greedy forwardIf lower, then do primeter forward
If no greedy option, follow right hand rule
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Maintenance all nodes maintain a single-hop neighbor table
At source: mode = greedy
Intermediate node: if (mode == greedy) {
greedy forwarding;if (no_greedy_option||greedy_option_VIPrate - this.VIPrat
e>h) mode = perimeter;
}if (mode == perimeter) {
if (have left local maxima && local maxima’s VIPrate - this.VIPrate<h) mode = greedy;
else (right-hand rule);}
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Original Networks
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Earthquake happen0.8
0.8
What we need is to optimize lifetime of this
subgraph
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Spread the VIPrate or not?0.8
0.8
This node still suffers from large traffic
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Earthquake moves…0.8
0.8
0.8
0.8
What we need is to optimize lifetime of this
subgraph
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After optimization0.8
0.8
0.8
0.8
Work in lower cycle
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A analysis by hand Before
optimization
23
1
7
5
1
1
5
9
1 3 21
1
7
1
3
3
Send 1 packet
Receive 1 packetForward 1 packet
Send 1 pakcet
Energy consume: 55
Whole energy: 92
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After optimization
23
11
7
5
1
1
3
13
1 21
3
11
1
1
7
Energy consume: 49
Whole energy: 100Save for subgraph:
6Extra energy: 8
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11
11
17
15
1
11
3
9
1
7
1
5
3 9
3
Energy consume: 32Whole energy: 98
Save for subgraph: 24Extra energy: 6
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Thanks