PROGETTO PATTERN Attività di Ricerca del gruppo di Catania nel I Anno Energy efficient solutions...
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Transcript of PROGETTO PATTERN Attività di Ricerca del gruppo di Catania nel I Anno Energy efficient solutions...
PROGETTO PATTERN
Attività di Ricerca del gruppo di Catania nel I Anno
Energy efficient solutions for connectivity and data delivery in self-organizing networks
University of CataniaDipartimento di Ingegneria Informatica e delle Telecomunicazioni
© Laura Galluccio 04
Progetto PATTERN Firenze 12/10/04 2
Outline
Energy efficiency and Timeliness of Neighbor Discovery in Self-Organizing Networks
Integrated MAC/Routing protocol for Geographical Forwarding in Self-Organizing Networks
Progetto PATTERN Firenze 12/10/04 3
Energy efficiency and Timeliness of Neighbor
Discovery in Self-Organizing Networks
Progetto PATTERN Firenze 12/10/04 4
The ProblemAd hoc and sensor networks: nodes mobility and
failures lead to very dynamic topology
If nodes are able to discover very rapidly…..
……Self-organization can be achieved…..
….but Higher responsiveness is paid in terms of energy consumption!
Progetto PATTERN Firenze 12/10/04 5
Scenario
N2
N1
1Nv
R
dN1,N2
2Nv
Progetto PATTERN Firenze 12/10/04 6
Scenario
N1
N2
Progetto PATTERN Firenze 12/10/04 7
Scenario
• A and B enter each others coverage range they become neighbors
N1
N2t=0
Progetto PATTERN Firenze 12/10/04 8
Scenario
• A and B exit each others coverage range they are no longer neighbors
N1
N2
t=
Progetto PATTERN Firenze 12/10/04 9
Scenario
N1
N2
Progetto PATTERN Firenze 12/10/04 10
Neighborhood Time
Neighborhood time (): time interval during which a pair of nodes are neighbors.
Discovery time (T): time interval necessary for the discovery between two nodes.
Transmit time (TT): time interval necessary for the exchange of the data required by the application.
In case of correct functioning: TT ≤ -T Probability of discovery success (PDS):
probability that the above relationship holds
Progetto PATTERN Firenze 12/10/04 11
The Approach
A Trade-off is needed between increasing the PDS and decreasing the energy cost associated to this process.
We derived a Markov analytical framework for evaluating the energy cost of the hunting process which is the process of searching for other nodes in the proximity.
This framework allows the developer to design the hunting process so as to meet the requirements in terms of the energy consumption
Progetto PATTERN Firenze 12/10/04 12
211' NNN vvv
cos2'21211
22NNNNN vvvvv
If remains constant in direction and magnitude for a sufficient amount of time:
and
1'Nv
11'/'/2 NNy vSvP
44
1)(
4
1)(
22
22
sR
s
Rsf
sRR
RsF SS
Progetto PATTERN Firenze 12/10/04 13
The Hunting Process
DSSIIHFtHS .....,2,1.....,2,1
)()()(
)(HQ
)(H
)(HF
To discover neighbors, a node periodically runs a set of procedures which we call hunting process. The states of this process could be:
• Inquiry: a beacon message is transmitted (I)• Inquiry Scan: a node listens for beacon messages (S)• Doze: no inquiry or scan procedures are executed (D)
If M channels are used for discovery, the hunting process can be described as:
state space state of the hunting process
transition rate matrix steady state array
Progetto PATTERN Firenze 12/10/04 14
Neighbor Discovery Process (NDP) Suppose that in t the two nodes N1 and N2 become
neighbors. NDP is the result of the interactions between the 2 hunting processes
)()2(
),()1(
)()(
tH
StH
StP
S )()()( HFx
HF
PF
tPQe
Pt
P )()0(
)()(
)( )2()1(
)0()( H
xHP
otherwise0
)''2σ,''1(σ)'
2σ,'1(σif
)'2
σ,'1
(σ(P)F)2
σ1,
(σ )]2
σ,1
(σ),'2
σ,'1
[(σ
](P)[Q
''1σ'
1σif]''
2σ,'2[σ
])2(H
[Q
''2σ'
2σif]''1σ,'1[σ
])1(H
[Q
)]''2,''1(),'
2,'1[(])([
PQ
Progetto PATTERN Firenze 12/10/04 15
Conditions for Discovery
mH
mHH
tItSStSS
)()()(lim )2()1()1(
mHH
tm
H ItSSStS
)()(lim)( )2()2()1(
mHH
tm
H StSSItS
)()(lim)( )2()2()1(
mH
mHH
tStSItSS
)()()(lim )2()1()1(
1.
2.
3.
4.
Progetto PATTERN Firenze 12/10/04 16
Probability of discovery and array of discovery rate
MmIandSiftQ
MmSandIiftQ
MmIandSiftQ
MmSandIiftQ
tttP
mmmSH
mmmIH
mmmSH
mmmIH
DISC
,][
,][
,][
,][
),(
21],1[)1(
21],1[)1(
12],2[)2(
12],2[)2(
)()2,1(
MmIandSifQ
MmSandIifQ
MmIandSifQ
MmSandIifQ
mmmSH
mmmIH
mmmSH
mmmIH
DISC
,][
,][
,][
,][
][
21],1[)1(
21],1[)1(
12],2[)2(
12],2[)2(
)]2,1[()(
*)()( )()( DISCP tt overall discovery rate at t
Progetto PATTERN Firenze 12/10/04 17
Evolution of the process when nodes do not succeed in discovery
tTtSPt PDISCtT |),()()]([ 21
)()2,1(
)'(
The probability that the state of the pair of neighbors is given that the 2 nodes have not discovered
We derived matrix which is the state transition rate matrix of the process, given that the mobile nodes have not discovered each other. This matrix can be related to Consequently:
),( 21
)(PNODISCQ
)(PQ
tPNODISCQPP
tT e)(
)()( )0(
*)()( )()( DISCPtTtT tt
Progetto PATTERN Firenze 12/10/04 18
QoS Parameters
Energy Cost
][)(
1][
)( ][][[ mSH
SCAN
M
mmI
HINQ PWPWc
Pdf of the discovery time T )(1)( tAT ektF
M
mmSmI
PmImS
Pk1
),()(
),()( ][][1
*)(
1
11)(
0
....,1
.,.........1
)0()()( DISC
RL
tRLdtdP
t
tT ttd
e
d
ediagdtA
id eigenvalues of )(PNODISCQ eigenvectors of which is the )(P
NODISCQ
matrix of the transition rates, given that the mobile nodes do not discover each other
Progetto PATTERN Firenze 12/10/04 19
PDS in data transfer
TTvs
T
R
SS dsddffsfP)('/
0
2
0 0
)()()(
Progetto PATTERN Firenze 12/10/04 20
Cycle Time
The cycle time can be related to the scan, inquiry and doze probabilities.It can be demonstrated that, once the probabilities are set, does not depend on or or .
SP
CycleTv TT
DozeScanInqCycle TTTT
Progetto PATTERN Firenze 12/10/04 21
Cycle Time 5. vTwithTvsP CycleCycleS
0Cycle
T
T
T
5Cycle
T
T
T
Progetto PATTERN Firenze 12/10/04 22
Case Study
SP
Cycle
T
T
T
We applied the proposed methodology to a relevant case study:
•A single channel system
We derived some design implications on neighbor discovery algorithms and verified that increases as the cost constraint increases and the ratio decreases.
Progetto PATTERN Firenze 12/10/04 23
Case Study0,1.
Cycle
TCycleScanS T
TvTwithPvsP
C*=0.3
C*=0.7
Progetto PATTERN Firenze 12/10/04 24
Case Study0,1
Cycle
TCycle T
TvT
1vTCycle
Progetto PATTERN Firenze 12/10/04 25
Case Study
1vTCycle
Progetto PATTERN Firenze 12/10/04 26
Conclusions 1
1. Nodes in self-organizing ad hoc and sensor networks execute the hunting process procedures
2. These procedures imply high energy consumption if a timely discovery occurs
3. A trade-off is needed4. An analytical framework for evaluation of the maximum probability
of discovery success, given some energy constraints, was introduced5. This framework can be used for designing appropriately the
discovery process in a mobile network so as to satisfy the application requirements
Progetto PATTERN Firenze 12/10/04 27
Integrated MAC/Routing protocol for Geographical
Forwarding in Self-Organizing Networks
Progetto PATTERN Firenze 12/10/04 28
The Problem
In commercial sensor devices different TX power levels are available
This feature can be exploited for reducing energy consumption
We propose a MAC/ROuting protocol which uses this capability
This protocol works with a cross-layer approach, is simple and does not require any location information knowledge
Uses competition to select the most efficient next relay
Progetto PATTERN Firenze 12/10/04 29
Prerequisites
P
DRdDRdG RR
),''(),'('','
)'()....'()'(....... 2121 RSRSRSPPP MM
Weighted progress factor (WPF)
Set of power levels and coverage range
R’’
R’ D
)'(1 RS
Progetto PATTERN Firenze 12/10/04 30
Protocol FunctioningRouting functionalities
P
DRdDRdG RR
),''(),'('','
)'()....'()'(....... 2121 RSRSRSPPP MM
Weighted progress factor (WPF)
Set of power levels and coverage range
R’’
R’ D
)'(1 RS
1. To select the next relay node R’ triggers a competition
2. Be R’’ the winner of the competition in the set S1(R’) and GR’R1’’ its WPF
3. If R’ estimates that a higher WPF can be obtained increasing P, a new competition is triggered in the set S2(R’).
4. The procedure is repeated until no better relay nodes can be found
5. When the best relay is identified the information is transmitted
Progetto PATTERN Firenze 12/10/04 31
Protocol FunctioningMAC functionalities
P
DRdDRdG RR
),''(),'('','
)'()....'()'(....... 2121 RSRSRSPPP MM
Weighted progress factor (WPF)
Set of power levels and coverage range
1. Nodes periodically switch ON and OFF to reduce energy consumption
2. Synchronization is not needed
3. A wake up phase is requires for R’ identifying the best relay node in Si(R’)
4. To this purpose R’ transmits several short WAKE-UP messages for a TCycle
5. Then R’ sends a Go MESSAGE which triggers competition among nodes in Si(R’)
6. A node in Si(R’) hearing the WAKE_UP messages calculates its WPF and stays awake waiting for the GO MESSAGE
7. Then upon hearing the GO MESSAGE a node sends randomly back to R’ its WPF so that R’ performs the choice of the best relay in Si(R’)
CycleT
ONT
TXWUON
InWU TTT 2
Progetto PATTERN Firenze 12/10/04 32
Questions Analytical Framework
What is the probability that outside the coverage area obtained using , exists at least one node whose WPF is higher than , provided that
Once the probability is known, when it is worth enlarging the coverage area?
If we stop the competition at time t, what is the probability to choose not the best available relay node in the considered coverage area?
?)(i
Mi GG
g
iP
Progetto PATTERN Firenze 12/10/04 33
Answer to Question 1
)|()()(1 1}|Pr{ iGga
iM
iM
i eGGgG
)|( iGgaWhere is the nodes’ density and is the area where a node B must be located in order to belong to and have a WPF higher than g.
)'(1 RSi
gP
R
i
i 1
gP
R
i
i 1
Progetto PATTERN Firenze 12/10/04 34
Answer to Question 2
11
1)()(
1
/
/ |
)()(1 )|(}|{
ii
iiiM
iM
i
PR
PPG iGGiM
iM
i dgGgfgGGGE
Where is the probability density function which can be evaluated using the previous results as
)|()()(1 | iGG
Ggf Mi
Mi
)|()|( )|(
| )()(1
iGga
iGGGga
dg
deGgf i
Mi
Mi
Progetto PATTERN Firenze 12/10/04 35
Answer to Question 3
iPiR
iG MiGARAAiARi dggfgGttGGRSA /
)(,','1 )(}|Pr{1},:)'(Pr{
This represents the probability that a node having a WPF higher than the best available one exists out of and its CONTROL ACK message arrives later than other nodes’ messages.
)'(RSi
gkt
ARA egGt
1}|Pr{ ,'
}Pr{ )()( gG
dg
df M
iMiG
Progetto PATTERN Firenze 12/10/04 36
Performance evaluationPolicy for the TX power level choice
Policy 1: TX power levels increase linearlyPolicy 2: TX power levels give a linear increase inPolicy 3: TX power levels give a linear increase in
)'(RSi
iR
Progetto PATTERN Firenze 12/10/04 37
Performance evaluationPolicy for the TX power level choice
Average TX power
Average power consumption
Average range
Progetto PATTERN Firenze 12/10/04 38
Performance evaluationComparison with other protocols
Average power consumption
Average number of hops
Progetto PATTERN Firenze 12/10/04 40
Performance evaluationNumber of packets delivered at destination
Progetto PATTERN Firenze 12/10/04 41
Conclusions 2
1. MACRO is an integrated MAC/Routing geocast protocol 2. Convenient in case of strict requirements in terms of energy
efficiency 3. The increase in end-to-end delay can turn into an
advantage in terms of data aggregation4. MACRO greately extends node’s lifetime
Progetto PATTERN Firenze 12/10/04 42
Publications
L. Galluccio, A. Leonardi, G. Morabito, S. Palazzo: Tradeoff between Energy-Efficiency and Timeliness of Neighbor Discovery in Self-Organizing Ad Hoc and Sensor Networks. Proc. of HICSS 2005, Big Island, Hawaii, January 2005.
L. Galluccio, A. Leonardi, S. Palazzo: Design Guidelines for Geocast Protocols in Ad Hoc and Sensor Networks. Proc. of Med-Hoc Net 2004, Bodrum, Turkey, June 2004.
L. Galluccio, S. Palazzo: A Taxonomy of Location Management Schemes in Mobile Ad Hoc Networks. To appear in Journal of Communications and Networks.
D. Ferrara, L. Galluccio, A. Leonardi, G. Morabito, S. Palazzo: MACRO: An Integrated MAC/Routing Protocol for Geographical Forwarding in Wireless Sensor Networks. Submitted for Publication.