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Performance Evaluation of a Multi-Radio
Energy Conservation Scheme for Disruption
Tolerant Networks
Iyad Tumar
Birzeit University
MOBIWAC 2010, Bodrum, Turkey
October 18, 2010
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks1
Disruption Tolerant Networks (DTNs)
Developing network communication when connectivity isintermittent and prone to disruptions
DTNs differ from traditional networks due to specialcharacteristics
Frequent partitions, no end-to-end connectionIntermittent connectivityMessage delivery delayLimited resources
Efficient energy conservation schemes are necessary toprolong the network life time
: message transmission
R2S
R1
message
D
(a) From node S to R1
R1 R2
D
S
S : source node
(b) From node R1 to R2
DR2
R1
S
D: destination node
(c) From node R2 to D
Figure 1: An example scenario of message forwarding in a DTN as time passes
nodes provides a routing path from a source toward a destination. This route can be com-
pletely predictable if nodes move on fixed schedules, while it can be completely unpre-
dictable (i.e., opportunistic) if nodes move in an arbitrary manner. Many studies have
identified the characteristics of a set of DTNs and proposed routing protocols on them.
Such routing protocols can be classified into three categories: knowledge-based mechanisms,
designated delivery mechanisms, and opportunistic mechanisms. First, knowledge-basedmech-
anisms utilize available knowledge about network dynamics and apply Dijkstra’s algo-
rithm to find the shortest path in terms of expected delay [30, 18]. Second, designated
delivery mechanisms designate special mobile nodes to deliver messages among other
nodes as in Message Ferrying [78, 79, 80] and Data Mule [62]. Finally, opportunistic mech-
anisms forward one or more copy of messages to other nodes without any knowledge
about network dynamics and hope for eventual delivery [72, 69, 73, 31].
Another major issue in DTNs is energy conservation. In the class of DTNs, there are
important applications with energy constraints. For example, nodes deployed in a remote
or hazardous area may have limited access to energy sources, yet the need for long net-
work lifetime. Even if some nodes have abundant energy, a heterogeneous network may
include key devices with limited energy. Thus, efficient power management mechanisms
are necessary to allow these networks to remain operational over a long period of time.
However, mobile devices exhibit a tension between saving energy and providing connec-
tivity. In order to pass messages, the device must discover other nodes, typically using the
3
Figure 1.1: An example scenario of message forwarding in a DTN as time passes [14].
delivery services within DTN environments. DTNs can be applied to wireless networks withno end-to-end connectivity, satellite networks with long delays, wireless sensor networks withintermittent connectivity, and underwater acoustic networks with frequent interruptions.
Another major issue in DTNs is energy conservation. In general, DTNs are applicable inremote and hazardous areas where the energy sources are often constrained. DTNs are alsooften assumed to operate over a long period of time. Therefore, several research efforts havebeen devoted to developing power management schemes for DTNs to allow these networks toremain operational over a long period of time.
The wireless interface is one of the largest consumers of energy in energy limited devices [19]and it can work in four different modes: listening, transmitting, receiving, and sleeping. Wire-less interfaces consume a significant amount of energy even in the idle listening mode. Mea-surements have shown that transmitting a single bit of information requires the same amountof energy as that needed for processing a thousand operations in a sensor node [20]. Studiesalso show that energy consumption of some radios in idle mode is almost as high as in receiv-ing mode [21, 22]. Therefore, a significant amount of energy can be saved by allowing nodesto put their wireless interfaces into sleep mode.
In DTNs, nodes need to discover neighbors to establish communication. Searching for neigh-bors in sparse DTNs can consume a large amount of power compared to the power consumedby infrequent data transfers. Therefore, novel power management schemes are needed toaddress this problem and to save energy. Designing such power management schemes ischallenging, because nodes need to know when to sleep, to save power, and when to wake upto search for neighbors. Ideally, power management schemes should not reduce network con-nectivity opportunities, which would negatively affect the overall performance of the network.
1.1.1 Disruption Tolerant Networks Characteristics
DTNs are supposed to operate over a long period of time, and they differ from traditionalnetworks because of their characteristics. In this section we briefly review some importantproperties of DTNs [15, 23, 24]:
Latency: Due to frequent and random mobility of the nodes in DTNs, any two nodes maynever meet each other for a long time. Therefore, the transmission rate may be considerablysmall and largely asymmetric with long latency of data delivery.
2
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks2
Disruption Tolerant Networks (DTNs)
Developing network communication when connectivity isintermittent and prone to disruptions
DTNs differ from traditional networks due to specialcharacteristics
Frequent partitions, no end-to-end connectionIntermittent connectivityMessage delivery delayLimited resources
Efficient energy conservation schemes are necessary toprolong the network life time
: message transmission
R2S
R1
message
D
(a) From node S to R1
R1 R2
D
S
S : source node
(b) From node R1 to R2
DR2
R1
S
D: destination node
(c) From node R2 to D
Figure 1: An example scenario of message forwarding in a DTN as time passes
nodes provides a routing path from a source toward a destination. This route can be com-
pletely predictable if nodes move on fixed schedules, while it can be completely unpre-
dictable (i.e., opportunistic) if nodes move in an arbitrary manner. Many studies have
identified the characteristics of a set of DTNs and proposed routing protocols on them.
Such routing protocols can be classified into three categories: knowledge-based mechanisms,
designated delivery mechanisms, and opportunistic mechanisms. First, knowledge-basedmech-
anisms utilize available knowledge about network dynamics and apply Dijkstra’s algo-
rithm to find the shortest path in terms of expected delay [30, 18]. Second, designated
delivery mechanisms designate special mobile nodes to deliver messages among other
nodes as in Message Ferrying [78, 79, 80] and Data Mule [62]. Finally, opportunistic mech-
anisms forward one or more copy of messages to other nodes without any knowledge
about network dynamics and hope for eventual delivery [72, 69, 73, 31].
Another major issue in DTNs is energy conservation. In the class of DTNs, there are
important applications with energy constraints. For example, nodes deployed in a remote
or hazardous area may have limited access to energy sources, yet the need for long net-
work lifetime. Even if some nodes have abundant energy, a heterogeneous network may
include key devices with limited energy. Thus, efficient power management mechanisms
are necessary to allow these networks to remain operational over a long period of time.
However, mobile devices exhibit a tension between saving energy and providing connec-
tivity. In order to pass messages, the device must discover other nodes, typically using the
3
Figure 1.1: An example scenario of message forwarding in a DTN as time passes [14].
delivery services within DTN environments. DTNs can be applied to wireless networks withno end-to-end connectivity, satellite networks with long delays, wireless sensor networks withintermittent connectivity, and underwater acoustic networks with frequent interruptions.
Another major issue in DTNs is energy conservation. In general, DTNs are applicable inremote and hazardous areas where the energy sources are often constrained. DTNs are alsooften assumed to operate over a long period of time. Therefore, several research efforts havebeen devoted to developing power management schemes for DTNs to allow these networks toremain operational over a long period of time.
The wireless interface is one of the largest consumers of energy in energy limited devices [19]and it can work in four different modes: listening, transmitting, receiving, and sleeping. Wire-less interfaces consume a significant amount of energy even in the idle listening mode. Mea-surements have shown that transmitting a single bit of information requires the same amountof energy as that needed for processing a thousand operations in a sensor node [20]. Studiesalso show that energy consumption of some radios in idle mode is almost as high as in receiv-ing mode [21, 22]. Therefore, a significant amount of energy can be saved by allowing nodesto put their wireless interfaces into sleep mode.
In DTNs, nodes need to discover neighbors to establish communication. Searching for neigh-bors in sparse DTNs can consume a large amount of power compared to the power consumedby infrequent data transfers. Therefore, novel power management schemes are needed toaddress this problem and to save energy. Designing such power management schemes ischallenging, because nodes need to know when to sleep, to save power, and when to wake upto search for neighbors. Ideally, power management schemes should not reduce network con-nectivity opportunities, which would negatively affect the overall performance of the network.
1.1.1 Disruption Tolerant Networks Characteristics
DTNs are supposed to operate over a long period of time, and they differ from traditionalnetworks because of their characteristics. In this section we briefly review some importantproperties of DTNs [15, 23, 24]:
Latency: Due to frequent and random mobility of the nodes in DTNs, any two nodes maynever meet each other for a long time. Therefore, the transmission rate may be considerablysmall and largely asymmetric with long latency of data delivery.
2
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks2
Disruption Tolerant Networks (DTNs)
Developing network communication when connectivity isintermittent and prone to disruptions
DTNs differ from traditional networks due to specialcharacteristics
Frequent partitions, no end-to-end connectionIntermittent connectivityMessage delivery delayLimited resources
Efficient energy conservation schemes are necessary toprolong the network life time
: message transmission
R2S
R1
message
D
(a) From node S to R1
R1 R2
D
S
S : source node
(b) From node R1 to R2
DR2
R1
S
D: destination node
(c) From node R2 to D
Figure 1: An example scenario of message forwarding in a DTN as time passes
nodes provides a routing path from a source toward a destination. This route can be com-
pletely predictable if nodes move on fixed schedules, while it can be completely unpre-
dictable (i.e., opportunistic) if nodes move in an arbitrary manner. Many studies have
identified the characteristics of a set of DTNs and proposed routing protocols on them.
Such routing protocols can be classified into three categories: knowledge-based mechanisms,
designated delivery mechanisms, and opportunistic mechanisms. First, knowledge-basedmech-
anisms utilize available knowledge about network dynamics and apply Dijkstra’s algo-
rithm to find the shortest path in terms of expected delay [30, 18]. Second, designated
delivery mechanisms designate special mobile nodes to deliver messages among other
nodes as in Message Ferrying [78, 79, 80] and Data Mule [62]. Finally, opportunistic mech-
anisms forward one or more copy of messages to other nodes without any knowledge
about network dynamics and hope for eventual delivery [72, 69, 73, 31].
Another major issue in DTNs is energy conservation. In the class of DTNs, there are
important applications with energy constraints. For example, nodes deployed in a remote
or hazardous area may have limited access to energy sources, yet the need for long net-
work lifetime. Even if some nodes have abundant energy, a heterogeneous network may
include key devices with limited energy. Thus, efficient power management mechanisms
are necessary to allow these networks to remain operational over a long period of time.
However, mobile devices exhibit a tension between saving energy and providing connec-
tivity. In order to pass messages, the device must discover other nodes, typically using the
3
Figure 1.1: An example scenario of message forwarding in a DTN as time passes [14].
delivery services within DTN environments. DTNs can be applied to wireless networks withno end-to-end connectivity, satellite networks with long delays, wireless sensor networks withintermittent connectivity, and underwater acoustic networks with frequent interruptions.
Another major issue in DTNs is energy conservation. In general, DTNs are applicable inremote and hazardous areas where the energy sources are often constrained. DTNs are alsooften assumed to operate over a long period of time. Therefore, several research efforts havebeen devoted to developing power management schemes for DTNs to allow these networks toremain operational over a long period of time.
The wireless interface is one of the largest consumers of energy in energy limited devices [19]and it can work in four different modes: listening, transmitting, receiving, and sleeping. Wire-less interfaces consume a significant amount of energy even in the idle listening mode. Mea-surements have shown that transmitting a single bit of information requires the same amountof energy as that needed for processing a thousand operations in a sensor node [20]. Studiesalso show that energy consumption of some radios in idle mode is almost as high as in receiv-ing mode [21, 22]. Therefore, a significant amount of energy can be saved by allowing nodesto put their wireless interfaces into sleep mode.
In DTNs, nodes need to discover neighbors to establish communication. Searching for neigh-bors in sparse DTNs can consume a large amount of power compared to the power consumedby infrequent data transfers. Therefore, novel power management schemes are needed toaddress this problem and to save energy. Designing such power management schemes ischallenging, because nodes need to know when to sleep, to save power, and when to wake upto search for neighbors. Ideally, power management schemes should not reduce network con-nectivity opportunities, which would negatively affect the overall performance of the network.
1.1.1 Disruption Tolerant Networks Characteristics
DTNs are supposed to operate over a long period of time, and they differ from traditionalnetworks because of their characteristics. In this section we briefly review some importantproperties of DTNs [15, 23, 24]:
Latency: Due to frequent and random mobility of the nodes in DTNs, any two nodes maynever meet each other for a long time. Therefore, the transmission rate may be considerablysmall and largely asymmetric with long latency of data delivery.
2
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks2
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Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks3
Contribution
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
4. PERFORMANCE EVALUATION?$( 2&,,&.+%6 8(5*+#0 "*( 10(' 2&* )(*2&*8"%#( (>",1":
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Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks4
Outline
1 BackgroundMobility ModelsPower Management of Disruption Tolerant Networks
2 Multi-Radio Power Management Scheme for DTNsPerformance Evaluation of the MR Power managementSchemeImpact of Different Mobility Models on the MR Powermanagement Scheme
3 Summary, Conclusions and Future Directions
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks5
Outline
1 BackgroundMobility ModelsPower Management of Disruption Tolerant Networks
2 Multi-Radio Power Management Scheme for DTNsPerformance Evaluation of the MR Power managementSchemeImpact of Different Mobility Models on the MR Powermanagement Scheme
3 Summary, Conclusions and Future Directions
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks6
Mobility Models
Random Waypoint (RWP)
The most common model used to evaluate routingprotocols such as DSR and AODV
Each node chooses some destination randomly and movesthere in different speed
Message Ferry Mobility Model (MF)
Regular nodes (often static nodes)
Ferries which move around the deployed area in a deterministic path
Collect messages from the regular nodesDeliver messages to their destinations or to other ferries
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks7
Mobility Models
Manhattan Mobility Model
It uses a grid road topology for the movement in urbanareas
Nodes move in horizontal or vertical streets
ZebraNet Mobility Model
Zebra Mobility models are based on zebra’s movementhabit
Human (Orlando) Mobility Model
The Orlando mobility model is based on actual datagathered from human mobility
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks8
Power Management of DTNs
Oracles and Knowledge-Based Mechanisms
These power management mechanisms based on knowledge offuture contacts
Assume that nodes have synchronized clocks
Save 50% of the energy compared to the case when no powermanagement apply
Hierarchical Power Management
It is based on the previous mechanisms and assumessynchronization among nodes
Use additional low-power radio to discover contacts and to awakethe high-power radio to exchange data
Saves 73% of the energy compared to the case when no powermanagement apply
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks9
Power Management of DTNs
The Context Aware power Management Scheme (CAPM)
Asynchronous mechanism (each node works on its own wake-upschedule)
The CAPM scheme has a fixed duty cycle
Each node wakes up for a fixed or adaptive period and sleeps forthe remaining time
The CAPM achieves 80% energy saving while PSM in Hierarchicalpower management scheme saves 40%
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks10
Outline
1 BackgroundMobility ModelsPower Management of Disruption Tolerant Networks
2 Multi-Radio Power Management Scheme for DTNsPerformance Evaluation of the MR Power managementSchemeImpact of Different Mobility Models on the MR Powermanagement Scheme
3 Summary, Conclusions and Future Directions
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks11
Multi-Radio Power Management Scheme for DTNs
Multi-Radio combines concepts of on-demand andasynchronous schemes by using
Low-power radio (LPR) interface to search for neighbors
High-power radio (HPR) interface that is wokenon-demand to exchange data
Power usage of low and high power radios (in Watt)
Radio Tx Rx Idle Sleep Bit RateWaveLan 1.3272 0.9670 0.8437 0.0664 2 Mbps
XTend 1 0.36 0.36 0.01 115.2 Kbps
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks12
Neighbor Discovery and Data Delivery
Each node periodically wakes up for a period W in a fixedduty cycle of length C
it broadcasts a beacon with a piggybacked delivery send a delivery acceptance message to node 2 when it hears
a b
c d
Multiple possible neighbor discovery scenarios
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks13
Simulation Setup
Simulation Scenarios
Each scenario is set up with 40 nodes, distributed over
1000 x 1000 m2 1150 x 1150 m2
1400 x 1400 m2 2000 x 2000 m2
3000 x 3000 m2
Traffic Model
We use constant bit rate traffic with 10 CBR flows and apacket size of 512 bytes.
The traffic generation for each flow varied from 0.25pkts/s to 3 pkts/s.
Only a maximum of 10 connections are allowed duringeach run.
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks14
Evaluation Metrics
1 Normalized Energy Consumption (NEC):
The ratio of the energy consumption when multi-radio scheme isapplied divided by the energy consumption in the absence of energyconservation
2 Delivery Ratio:
The ratio of the number of the successfully received data packetsdivided by the number of the data packets sent
3 Average End-to-End Delay:
The average delay it takes to deliver a data packet from the sourceto the destination
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks15
Evaluation Metrics
1 Normalized Energy Consumption (NEC):
The ratio of the energy consumption when multi-radio scheme isapplied divided by the energy consumption in the absence of energyconservation
2 Delivery Ratio:
The ratio of the number of the successfully received data packetsdivided by the number of the data packets sent
3 Average End-to-End Delay:
The average delay it takes to deliver a data packet from the sourceto the destination
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks15
Evaluation Metrics
1 Normalized Energy Consumption (NEC):
The ratio of the energy consumption when multi-radio scheme isapplied divided by the energy consumption in the absence of energyconservation
2 Delivery Ratio:
The ratio of the number of the successfully received data packetsdivided by the number of the data packets sent
3 Average End-to-End Delay:
The average delay it takes to deliver a data packet from the sourceto the destination
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks15
Impact of Node Density on Delivery Ratio of the
MR using RWP
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10−5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Node Density
Deliv
ery
Ratio
SR−3pkts/sMR−3pkts/sSR−0.25pkts/sMR−0.25pkts/s
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks16
Impact of Node Density on Average Delay using
RWP
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10−5
0
20
40
60
80
100
120
140
160
180
Node Density
Aver
age
Dela
y (s
)
SR−3pkts/sMR−3pkts/sSR−0.25pkts/sMR−0.25pkts/s
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks17
Impact of Node Density on Normalized Energy
Consumption using RWP
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5x 10−5
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Node Density
Norm
alize
d En
ergy
Con
sum
ptio
n
SR−3pkts/sMR−3pkts/sSR−0.25pkts/sMR−0.25pkts/s
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks18
Impact of Varying Node Density and Traffic Load
on the Delivery Ratio for Different Mobility Models
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10!5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Node Density
Delivery
Rati
o
SR!3pkts/s
MR!3pkts/s
SR!0.25pkts/s
MR!0.25pkts/s
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10!5
0.1
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0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Node Density
Delivery
Rati
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SR!3pkts/s
MR!3pkts/s
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MR!0.25pkts/s
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Rati
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2.1 Neighbor Discovery!"#$ %&'( )(*+&'+#",,- ."/(0 1) 2&* " )(*+&'! +% " 34('
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Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks19
Impact of Varying Node Density and Traffic Load
on the Average Delay for Different Mobility Models
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10!5
0
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200
250
300
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Avera
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3. SIMULATION SETUP=% &*'(* 5& (>",1"5( 5$( 81,5+:*"'+& 0#$(8(9 5$( E"%'&8
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
4. PERFORMANCE EVALUATION?$( 2&,,&.+%6 8(5*+#0 "*( 10(' 2&* )(*2&*8"%#( (>",1":
5+&%\ !"#$%&'()* +,)#-. /",01$23'",4 ?$( *"5+& &25$( (%(*6- #&%018)5+&% .$(% 81,5+:*"'+& 0#$(8( +0 ")),+(''+>+'(' ;- 5$( (%(*6- #&%018)5+&% +% 5$( ";0(%#( &2 (%(*6-#&%0(*>"5+&%7 5)&'6)#. 7%3'"4 ?$( *"5+& &2 5$( %18;(* &25$( 01##(0021,,- *(#(+>(' '"5" )"#/(50 '+>+'(' ;- 5$( %18:;(* &2 5$( '"5" )"#/(50 0(%57 86)#%-) +,*93"9+,* 5)&%.4?$( ">(*"6( '(,"- +5 5"/(0 5& '(,+>(* " '"5" )"#/(5 2*&8 5$(0&1*#( 5& 5$( '(05+%"5+&%7
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks20
Impact of Varying Node Density and Traffic Load
on the NEC for Different Mobility Models
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10!5
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Node Density
No
rma
lize
d E
ne
rgy
Co
ns
um
pti
on
SR!3pkts/s
MR!3pkts/s
SR!0.25pkts/s
MR!0.25pkts/s
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10!5
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Node Density
No
rma
lize
d E
ne
rgy
Co
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um
pti
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SR!3pkts/s
MR!3pkts/s
SR!0.25pkts/s
MR!0.25pkts/s
!"#$%&' !()'
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10!5
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Node Density
No
rma
lize
d E
ne
rgy
Co
ns
um
pti
on
SR!3pkts/s
MR!3pkts/s
SR!0.25pkts/s
MR!0.25pkts/s
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 10!5
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Node Density
No
rma
lize
d E
ne
rgy
Co
ns
um
pti
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SR!3pkts/s
MR!3pkts/s
SR!0.25pkts/s
MR!0.25pkts/s
!(&*+&,,&*' !-%.&*/0'
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2.1 Neighbor Discovery!"#$ %&'( )(*+&'+#",,- ."/(0 1) 2&* " )(*+&'! +% " 34('
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2.2 Data DeliveryA$(% 5$(*( +0 '"5" 5& ;( '(,+>(*('9 " %&'( )+66-;"#/0 "
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3. SIMULATION SETUP=% &*'(* 5& (>",1"5( 5$( 81,5+:*"'+& 0#$(8(9 5$( E"%'&8
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
4. PERFORMANCE EVALUATION?$( 2&,,&.+%6 8(5*+#0 "*( 10(' 2&* )(*2&*8"%#( (>",1":
5+&%\ !"#$%&'()* +,)#-. /",01$23'",4 ?$( *"5+& &25$( (%(*6- #&%018)5+&% .$(% 81,5+:*"'+& 0#$(8( +0 ")),+(''+>+'(' ;- 5$( (%(*6- #&%018)5+&% +% 5$( ";0(%#( &2 (%(*6-#&%0(*>"5+&%7 5)&'6)#. 7%3'"4 ?$( *"5+& &2 5$( %18;(* &25$( 01##(0021,,- *(#(+>(' '"5" )"#/(50 '+>+'(' ;- 5$( %18:;(* &2 5$( '"5" )"#/(50 0(%57 86)#%-) +,*93"9+,* 5)&%.4?$( ">(*"6( '(,"- +5 5"/(0 5& '(,+>(* " '"5" )"#/(5 2*&8 5$(0&1*#( 5& 5$( '(05+%"5+&%7
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks21
Summary I
Energy saving of different mobility models at low data rate(0.25 pkt/s)
Mobility Model SR Eng. Saving MR Eng. Saving Delta
RWP 85% 90% 5%MF 86% 93% 7%
Zebra 85% 91% 6%Manhattan 84% 89% 5%
Orlando 77% 87% 10%
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks22
Summary II
Energy saving of different mobility models at high data rate(3 pkt/s)
Mobility Model SR Eng. Saving MR Eng. Saving Delta
RWP 73% 88% 15%MF 76% 90% 14%
Zebra 73% 89% 16%Manhattan 72% 86% 14%
Orlando 67% 84% 17%
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks23
Outline
1 BackgroundMobility ModelsPower Management of Disruption Tolerant Networks
2 Multi-Radio Power Management Scheme for DTNsPerformance Evaluation of the MR Power managementSchemeImpact of Different Mobility Models on the MR Powermanagement Scheme
3 Summary, Conclusions and Future Directions
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks24
Summary and Conclusion
Summary
We designed a MR power management scheme for DTNs
The MR uses two complementary radios: a low-power radiofor neighbor discovery and a high-power radio to undertakethe data transmission
We evaluated the MR scheme with different mobility modelsand we compared it with a single radio scheme (CAPM)
Conclusion
The MR scheme is adaptive to different mobility models
The MR scheme can achieve almost the same delivery ratiocompared to the single radio power management scheme
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks25
Summary and Conclusion
Summary
We designed a MR power management scheme for DTNs
The MR uses two complementary radios: a low-power radiofor neighbor discovery and a high-power radio to undertakethe data transmission
We evaluated the MR scheme with different mobility modelsand we compared it with a single radio scheme (CAPM)
Conclusion
The MR scheme is adaptive to different mobility models
The MR scheme can achieve almost the same delivery ratiocompared to the single radio power management scheme
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks25
Future Directions
Routing Protocols
It would be interesting to study the behavior of the MRscheme with other routing protocols such as MaxProp
Traffic Models
It would be interesting to evaluate the MR powermanagement scheme with different traffic models
Adaptive Radios
To explore adaptive radios for energy saving techniques indisruption tolerant networks
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks26
Future Directions
Routing Protocols
It would be interesting to study the behavior of the MRscheme with other routing protocols such as MaxProp
Traffic Models
It would be interesting to evaluate the MR powermanagement scheme with different traffic models
Adaptive Radios
To explore adaptive radios for energy saving techniques indisruption tolerant networks
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks26
Future Directions
Routing Protocols
It would be interesting to study the behavior of the MRscheme with other routing protocols such as MaxProp
Traffic Models
It would be interesting to evaluate the MR powermanagement scheme with different traffic models
Adaptive Radios
To explore adaptive radios for energy saving techniques indisruption tolerant networks
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks26
THANK YOU
Questions???
Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks27