interference-aware routing and scheduling in wimax ... speci es a mac protocol but leaves scheduling...
TRANSCRIPT
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Interference-aware Routing and Schedulingin WiMAX Backhaul Networks
with Smart Antennas
CS 440 — Computer Networks
Montana State University
Fall 2008
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionWiMAX
Worldwide Interoperability for Microwave Access, isdescribed by the WiMAX forum as “a standards-basedtechnology enabling the delivery of last mile wirelessbroadband access as an alternative to cable and DSL”.
IEEE 802.16 standards
Base Station vs Subscriber Station
Point-to-Multipoint (PMP) mode vs Mesh mode
Time Division Multiple Access (TDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionWiMAX
Worldwide Interoperability for Microwave Access, isdescribed by the WiMAX forum as “a standards-basedtechnology enabling the delivery of last mile wirelessbroadband access as an alternative to cable and DSL”.
IEEE 802.16 standards
Base Station vs Subscriber Station
Point-to-Multipoint (PMP) mode vs Mesh mode
Time Division Multiple Access (TDMA)
3 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionWiMAX
Worldwide Interoperability for Microwave Access, isdescribed by the WiMAX forum as “a standards-basedtechnology enabling the delivery of last mile wirelessbroadband access as an alternative to cable and DSL”.
IEEE 802.16 standards
Base Station vs Subscriber Station
Point-to-Multipoint (PMP) mode vs Mesh mode
Time Division Multiple Access (TDMA)
4 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionWiMAX
Worldwide Interoperability for Microwave Access, isdescribed by the WiMAX forum as “a standards-basedtechnology enabling the delivery of last mile wirelessbroadband access as an alternative to cable and DSL”.
IEEE 802.16 standards
Base Station vs Subscriber Station
Point-to-Multipoint (PMP) mode vs Mesh mode
Time Division Multiple Access (TDMA)
5 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionWiMAX
Worldwide Interoperability for Microwave Access, isdescribed by the WiMAX forum as “a standards-basedtechnology enabling the delivery of last mile wirelessbroadband access as an alternative to cable and DSL”.
IEEE 802.16 standards
Base Station vs Subscriber Station
Point-to-Multipoint (PMP) mode vs Mesh mode
Time Division Multiple Access (TDMA)
6 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionWiMAX
Worldwide Interoperability for Microwave Access, isdescribed by the WiMAX forum as “a standards-basedtechnology enabling the delivery of last mile wirelessbroadband access as an alternative to cable and DSL”.
IEEE 802.16 standards
Base Station vs Subscriber Station
Point-to-Multipoint (PMP) mode vs Mesh mode
Time Division Multiple Access (TDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionWiMAX vs WiFi
WiMAX WiFi
802.16 802.11Licensed/unlicensed spectrum Unlicensed spectrum
WMAN WLANLonger range Shorter range
Higher throughput Lower throughtputRequest/Grant (TDMA) Contention based (CSMA/CA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionAn example WiMAX backhaul network
Internet
SS
SSSS
SS
SS
BS
SS
SS
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Introductionsmart antenna
Adapt to the environment.
Longer transmission range.
Lower power consumption.
Digital Adaptive Array (DAA) antennas
Multiple antenna elements (a.k.a, Degree Of Freedom,DOF)
Beam forming
Spatial Division Multiple Access (SDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Introductionsmart antenna
Adapt to the environment.
Longer transmission range.
Lower power consumption.
Digital Adaptive Array (DAA) antennas
Multiple antenna elements (a.k.a, Degree Of Freedom,DOF)
Beam forming
Spatial Division Multiple Access (SDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Introductionsmart antenna
Adapt to the environment.
Longer transmission range.
Lower power consumption.
Digital Adaptive Array (DAA) antennas
Multiple antenna elements (a.k.a, Degree Of Freedom,DOF)
Beam forming
Spatial Division Multiple Access (SDMA)
12 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Introductionsmart antenna
Adapt to the environment.
Longer transmission range.
Lower power consumption.
Digital Adaptive Array (DAA) antennas
Multiple antenna elements (a.k.a, Degree Of Freedom,DOF)
Beam forming
Spatial Division Multiple Access (SDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Introductionsmart antenna
Adapt to the environment.
Longer transmission range.
Lower power consumption.
Digital Adaptive Array (DAA) antennas
Multiple antenna elements (a.k.a, Degree Of Freedom,DOF)
Beam forming
Spatial Division Multiple Access (SDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Introductionsmart antenna
Adapt to the environment.
Longer transmission range.
Lower power consumption.
Digital Adaptive Array (DAA) antennas
Multiple antenna elements (a.k.a, Degree Of Freedom,DOF)
Beam forming
Spatial Division Multiple Access (SDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Introductionsmart antenna
Adapt to the environment.
Longer transmission range.
Lower power consumption.
Digital Adaptive Array (DAA) antennas
Multiple antenna elements (a.k.a, Degree Of Freedom,DOF)
Beam forming
Spatial Division Multiple Access (SDMA)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionAn example of smart antenna beam pattern (from www.wtec.org)
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionOur problem
We consider routing and scheduling in WiMAX backhaulnetworks with smart antennas.
802.16 specifies a MAC protocol but leaves schedulingalgorithm to implementation.
The trivial solution mentioned in WiMAX standardperforms very poorly.
Schedule with smart antennas and spatial reuse is quitedifferent from traditional link scheduling withomni-directional antennas.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionOur problem
We consider routing and scheduling in WiMAX backhaulnetworks with smart antennas.
802.16 specifies a MAC protocol but leaves schedulingalgorithm to implementation.
The trivial solution mentioned in WiMAX standardperforms very poorly.
Schedule with smart antennas and spatial reuse is quitedifferent from traditional link scheduling withomni-directional antennas.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionOur problem
We consider routing and scheduling in WiMAX backhaulnetworks with smart antennas.
802.16 specifies a MAC protocol but leaves schedulingalgorithm to implementation.
The trivial solution mentioned in WiMAX standardperforms very poorly.
Schedule with smart antennas and spatial reuse is quitedifferent from traditional link scheduling withomni-directional antennas.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
IntroductionOur problem
We consider routing and scheduling in WiMAX backhaulnetworks with smart antennas.
802.16 specifies a MAC protocol but leaves schedulingalgorithm to implementation.
The trivial solution mentioned in WiMAX standardperforms very poorly.
Schedule with smart antennas and spatial reuse is quitedifferent from traditional link scheduling withomni-directional antennas.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelAntenna Model
Each node has an antenna with K DOFs. (K is usually aconstant. But we do not make this assumption in ourwork.)
Each antenna can tune its K DOFs to point at arbitrarydirections dynamically.
In order to activate a link, one DOF needs to be assignedfor communication at each end of the link.
In order to cancel interference from one node to another,only one DOF needs to be assigned to form a null at eithernode.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelAntenna Model
Each node has an antenna with K DOFs. (K is usually aconstant. But we do not make this assumption in ourwork.)
Each antenna can tune its K DOFs to point at arbitrarydirections dynamically.
In order to activate a link, one DOF needs to be assignedfor communication at each end of the link.
In order to cancel interference from one node to another,only one DOF needs to be assigned to form a null at eithernode.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelAntenna Model
Each node has an antenna with K DOFs. (K is usually aconstant. But we do not make this assumption in ourwork.)
Each antenna can tune its K DOFs to point at arbitrarydirections dynamically.
In order to activate a link, one DOF needs to be assignedfor communication at each end of the link.
In order to cancel interference from one node to another,only one DOF needs to be assigned to form a null at eithernode.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelAntenna Model
Each node has an antenna with K DOFs. (K is usually aconstant. But we do not make this assumption in ourwork.)
Each antenna can tune its K DOFs to point at arbitrarydirections dynamically.
In order to activate a link, one DOF needs to be assignedfor communication at each end of the link.
In order to cancel interference from one node to another,only one DOF needs to be assigned to form a null at eithernode.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelScheduling Model
BS schedules the entire frame in a centralized manner,and broadcast the schedule to all SSs.
Bandwidth requests do not change within a schedulingperiod.
How to split downlink subframe and uplink subframe isout of the scope of our discussion.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelScheduling Model
BS schedules the entire frame in a centralized manner,and broadcast the schedule to all SSs.
Bandwidth requests do not change within a schedulingperiod.
How to split downlink subframe and uplink subframe isout of the scope of our discussion.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelScheduling Model
BS schedules the entire frame in a centralized manner,and broadcast the schedule to all SSs.
Bandwidth requests do not change within a schedulingperiod.
How to split downlink subframe and uplink subframe isout of the scope of our discussion.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelNetwork Model
A static, single channel, multi-hop WiMAX backhaulnetwork.
All traffic demands are unicast and between BS and SS.No traffic from SS to another SS.
Radios are homogeneous, half-duplex, and equipped withDAA antennas.
Protocol interference model
Primary interferenceSecondary interference
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelNetwork Model
A static, single channel, multi-hop WiMAX backhaulnetwork.
All traffic demands are unicast and between BS and SS.No traffic from SS to another SS.
Radios are homogeneous, half-duplex, and equipped withDAA antennas.
Protocol interference model
Primary interferenceSecondary interference
30 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelNetwork Model
A static, single channel, multi-hop WiMAX backhaulnetwork.
All traffic demands are unicast and between BS and SS.No traffic from SS to another SS.
Radios are homogeneous, half-duplex, and equipped withDAA antennas.
Protocol interference model
Primary interferenceSecondary interference
31 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelNetwork Model
A static, single channel, multi-hop WiMAX backhaulnetwork.
All traffic demands are unicast and between BS and SS.No traffic from SS to another SS.
Radios are homogeneous, half-duplex, and equipped withDAA antennas.
Protocol interference model
Primary interferenceSecondary interference
32 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelNetwork Model
A static, single channel, multi-hop WiMAX backhaulnetwork.
All traffic demands are unicast and between BS and SS.No traffic from SS to another SS.
Radios are homogeneous, half-duplex, and equipped withDAA antennas.
Protocol interference model
Primary interferenceSecondary interference
33 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
System ModelNetwork Model
A static, single channel, multi-hop WiMAX backhaulnetwork.
All traffic demands are unicast and between BS and SS.No traffic from SS to another SS.
Radios are homogeneous, half-duplex, and equipped withDAA antennas.
Protocol interference model
Primary interferenceSecondary interference
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionRouting (Tree Construction) Problem
If an SS can directly connect to the BS or another SS, norelay needed.
Thus, the communication graph G can firstly be layered.
Then the routing problem becomes to pick a node in layerh− 1 as the parent node for each node in layer h.
We want the routing tree be balanced and have lowinterference.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionRouting (Tree Construction) Problem
If an SS can directly connect to the BS or another SS, norelay needed.
Thus, the communication graph G can firstly be layered.
Then the routing problem becomes to pick a node in layerh− 1 as the parent node for each node in layer h.
We want the routing tree be balanced and have lowinterference.
36 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionRouting (Tree Construction) Problem
If an SS can directly connect to the BS or another SS, norelay needed.
Thus, the communication graph G can firstly be layered.
Then the routing problem becomes to pick a node in layerh− 1 as the parent node for each node in layer h.
We want the routing tree be balanced and have lowinterference.
37 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionRouting (Tree Construction) Problem
If an SS can directly connect to the BS or another SS, norelay needed.
Thus, the communication graph G can firstly be layered.
Then the routing problem becomes to pick a node in layerh− 1 as the parent node for each node in layer h.
We want the routing tree be balanced and have lowinterference.
38 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionInterference aware Tree Construction Problem (ITCP)
Define the secondary interference value of vi asIs(vi) = |Ni| − 1, where |Ni| is the set of nodes that canpotentially interfere with vi.
Define the secondary interference value of link e = (vi, vj)as Is(e) = max{Is(vi), Is(vj)}.
Definition
ITCP seeks a spanning tree rooted at the BS, such that in eachlayer h > 1, the maximum node degree of layer h− 1 isminimized subject to the constraint that the maximumsecondary interference value of all links picked between layerh− 1 and layer h is minimized (or less than K), withoutcausing disconnection of the two layers.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionInterference aware Tree Construction Problem (ITCP)
Define the secondary interference value of vi asIs(vi) = |Ni| − 1, where |Ni| is the set of nodes that canpotentially interfere with vi.
Define the secondary interference value of link e = (vi, vj)as Is(e) = max{Is(vi), Is(vj)}.
Definition
ITCP seeks a spanning tree rooted at the BS, such that in eachlayer h > 1, the maximum node degree of layer h− 1 isminimized subject to the constraint that the maximumsecondary interference value of all links picked between layerh− 1 and layer h is minimized (or less than K), withoutcausing disconnection of the two layers.
40 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionInterference aware Tree Construction Problem (ITCP)
Define the secondary interference value of vi asIs(vi) = |Ni| − 1, where |Ni| is the set of nodes that canpotentially interfere with vi.
Define the secondary interference value of link e = (vi, vj)as Is(e) = max{Is(vi), Is(vj)}.
Definition
ITCP seeks a spanning tree rooted at the BS, such that in eachlayer h > 1, the maximum node degree of layer h− 1 isminimized subject to the constraint that the maximumsecondary interference value of all links picked between layerh− 1 and layer h is minimized (or less than K), withoutcausing disconnection of the two layers.
41 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionScheduling Problem
A schedule is composed of both transmission schedulingand DOF assignment.
The spanning tree is given as input, together with thebandwidth demands of each SS.
Nodes need to transmit not only their own demands, butalso the aggregated demands from their descendants inthe spanning tree.
We want to promote the throughput of all nodes whilemaintaining fairness.
We only discuss uplink scheduling. Downlink is symmetric.
42 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionScheduling Problem
A schedule is composed of both transmission schedulingand DOF assignment.
The spanning tree is given as input, together with thebandwidth demands of each SS.
Nodes need to transmit not only their own demands, butalso the aggregated demands from their descendants inthe spanning tree.
We want to promote the throughput of all nodes whilemaintaining fairness.
We only discuss uplink scheduling. Downlink is symmetric.
43 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionScheduling Problem
A schedule is composed of both transmission schedulingand DOF assignment.
The spanning tree is given as input, together with thebandwidth demands of each SS.
Nodes need to transmit not only their own demands, butalso the aggregated demands from their descendants inthe spanning tree.
We want to promote the throughput of all nodes whilemaintaining fairness.
We only discuss uplink scheduling. Downlink is symmetric.
44 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionScheduling Problem
A schedule is composed of both transmission schedulingand DOF assignment.
The spanning tree is given as input, together with thebandwidth demands of each SS.
Nodes need to transmit not only their own demands, butalso the aggregated demands from their descendants inthe spanning tree.
We want to promote the throughput of all nodes whilemaintaining fairness.
We only discuss uplink scheduling. Downlink is symmetric.
45 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionScheduling Problem
A schedule is composed of both transmission schedulingand DOF assignment.
The spanning tree is given as input, together with thebandwidth demands of each SS.
Nodes need to transmit not only their own demands, butalso the aggregated demands from their descendants inthe spanning tree.
We want to promote the throughput of all nodes whilemaintaining fairness.
We only discuss uplink scheduling. Downlink is symmetric.
46 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionUplink Scheduling Problem (USP)
A schedule and DOF assignment is feasible if:
1 For each link scheduled, DOFs have been assigned at bothend for communication.
2 There does not exist primary or secondary interference inevery minislot.
3 Each node assigns at most K DOFs.
Definition
USP seeks a feasible uplink schedule and DOF assignment suchthat the bandwidth demand satisfaction ratio of the leastsatisfied node is maximized.
47 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionUplink Scheduling Problem (USP)
A schedule and DOF assignment is feasible if:
1 For each link scheduled, DOFs have been assigned at bothend for communication.
2 There does not exist primary or secondary interference inevery minislot.
3 Each node assigns at most K DOFs.
Definition
USP seeks a feasible uplink schedule and DOF assignment suchthat the bandwidth demand satisfaction ratio of the leastsatisfied node is maximized.
48 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionUplink Scheduling Problem (USP)
A schedule and DOF assignment is feasible if:
1 For each link scheduled, DOFs have been assigned at bothend for communication.
2 There does not exist primary or secondary interference inevery minislot.
3 Each node assigns at most K DOFs.
Definition
USP seeks a feasible uplink schedule and DOF assignment suchthat the bandwidth demand satisfaction ratio of the leastsatisfied node is maximized.
49 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionUplink Scheduling Problem (USP)
A schedule and DOF assignment is feasible if:
1 For each link scheduled, DOFs have been assigned at bothend for communication.
2 There does not exist primary or secondary interference inevery minislot.
3 Each node assigns at most K DOFs.
Definition
USP seeks a feasible uplink schedule and DOF assignment suchthat the bandwidth demand satisfaction ratio of the leastsatisfied node is maximized.
50 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Problem DefinitionUplink Scheduling Problem (USP)
A schedule and DOF assignment is feasible if:
1 For each link scheduled, DOFs have been assigned at bothend for communication.
2 There does not exist primary or secondary interference inevery minislot.
3 Each node assigns at most K DOFs.
Definition
USP seeks a feasible uplink schedule and DOF assignment suchthat the bandwidth demand satisfaction ratio of the leastsatisfied node is maximized.
51 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for ITCPIdeas
Construct auxiliary graph and use Ford-Fulkersonalgorithm to check whether it is possible to bound thenode degree of layer h− 1 while keep layer h and h− 1connected.
Use binary search to find the minimum satisfying nodedegree.
The algorithm has been proved to optimally solve ITCP inO(mnhmax log δmax) time.
52 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for ITCPIdeas
Construct auxiliary graph and use Ford-Fulkersonalgorithm to check whether it is possible to bound thenode degree of layer h− 1 while keep layer h and h− 1connected.
Use binary search to find the minimum satisfying nodedegree.
The algorithm has been proved to optimally solve ITCP inO(mnhmax log δmax) time.
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Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for ITCPIdeas
Construct auxiliary graph and use Ford-Fulkersonalgorithm to check whether it is possible to bound thenode degree of layer h− 1 while keep layer h and h− 1connected.
Use binary search to find the minimum satisfying nodedegree.
The algorithm has been proved to optimally solve ITCP inO(mnhmax log δmax) time.
54 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for ITCPExample Auxiliary Graph
C D E F
A B Layer h-1
Layer h
s
t
11
1 1 1 11
mid
mid
1
1
55 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for a specialcase of USPIdeas
Link scheduling problems in a multihop wireless networkhave been shown to be NP-hard.
A special case: when every node has enough DOFs toeiminate all potential secondary interferece.
Find the bottleneck node in the routing tree.
Schedule for the bottleneck node and its descendants, thenremove them and their demands from the routing tree.
Repeat until the tree becomes empty, and all nodesscheduled.
Our algorithm is polynomial in the number of nodes,irrelevant to the number of minislots.
56 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for a specialcase of USPIdeas
Link scheduling problems in a multihop wireless networkhave been shown to be NP-hard.
A special case: when every node has enough DOFs toeiminate all potential secondary interferece.
Find the bottleneck node in the routing tree.
Schedule for the bottleneck node and its descendants, thenremove them and their demands from the routing tree.
Repeat until the tree becomes empty, and all nodesscheduled.
Our algorithm is polynomial in the number of nodes,irrelevant to the number of minislots.
57 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for a specialcase of USPIdeas
Link scheduling problems in a multihop wireless networkhave been shown to be NP-hard.
A special case: when every node has enough DOFs toeiminate all potential secondary interferece.
Find the bottleneck node in the routing tree.
Schedule for the bottleneck node and its descendants, thenremove them and their demands from the routing tree.
Repeat until the tree becomes empty, and all nodesscheduled.
Our algorithm is polynomial in the number of nodes,irrelevant to the number of minislots.
58 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for a specialcase of USPIdeas
Link scheduling problems in a multihop wireless networkhave been shown to be NP-hard.
A special case: when every node has enough DOFs toeiminate all potential secondary interferece.
Find the bottleneck node in the routing tree.
Schedule for the bottleneck node and its descendants, thenremove them and their demands from the routing tree.
Repeat until the tree becomes empty, and all nodesscheduled.
Our algorithm is polynomial in the number of nodes,irrelevant to the number of minislots.
59 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for a specialcase of USPIdeas
Link scheduling problems in a multihop wireless networkhave been shown to be NP-hard.
A special case: when every node has enough DOFs toeiminate all potential secondary interferece.
Find the bottleneck node in the routing tree.
Schedule for the bottleneck node and its descendants, thenremove them and their demands from the routing tree.
Repeat until the tree becomes empty, and all nodesscheduled.
Our algorithm is polynomial in the number of nodes,irrelevant to the number of minislots.
60 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A polynomial time optimal algorithm for a specialcase of USPIdeas
Link scheduling problems in a multihop wireless networkhave been shown to be NP-hard.
A special case: when every node has enough DOFs toeiminate all potential secondary interferece.
Find the bottleneck node in the routing tree.
Schedule for the bottleneck node and its descendants, thenremove them and their demands from the routing tree.
Repeat until the tree becomes empty, and all nodesscheduled.
Our algorithm is polynomial in the number of nodes,irrelevant to the number of minislots.
61 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A heuristic algorithm for USP in the general caseIdeas
Slot-by-slot scheduling.
Greedily tries to pack as many links as possible in aminislot, consider the least satisfied link first.
Use auxiliary graph to decide whether a set of links can beactive concurrently and compute a feasible DOFassignment.
62 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A heuristic algorithm for USP in the general caseIdeas
Slot-by-slot scheduling.
Greedily tries to pack as many links as possible in aminislot, consider the least satisfied link first.
Use auxiliary graph to decide whether a set of links can beactive concurrently and compute a feasible DOFassignment.
63 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
A heuristic algorithm for USP in the general caseIdeas
Slot-by-slot scheduling.
Greedily tries to pack as many links as possible in aminislot, consider the least satisfied link first.
Use auxiliary graph to decide whether a set of links can beactive concurrently and compute a feasible DOFassignment.
64 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Simulation ScenariosScenario Parameters
Parameter SettingScenario Area 4× 8km2
Transmission Range 1kmInterference Range 3km
Number of DOFs per Node 3BS Placement Top-left cornerSS Placement Uniform within the area
Number of SSs [25, 50, 75, 100, 125, 150]Minislots per Frame 1024
Uplink demand of each SS Discrete uniform in [5, 10]Downlink demand of each SS Discrete uniform in [10, 20]
65 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Tree Construction AlgorithmsExample Trees
BFS ITCP MST
66 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Tree Construction + SchedulingEnd-to-end throughput
25 50 75 100 125 1500
50
100
150
200
250
300
350E
nd to
End
Thr
ough
put
Network Size
USP + ITCPFirst−Fit + BFSFirst−Fit + MST
67 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Tree Construction + SchedulingMinimum satisfaction ratio
25 50 75 100 125 1500
0.2
0.4
0.6
0.8
1M
inim
um S
atis
fact
ion
Rat
io
Network Size
USP + ITCPFirst−Fit + BFSFirst−Fit + MST
68 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Tree Construction + SchedulingFairness index
25 50 75 100 125 1500
0.2
0.4
0.6
0.8
1F
airn
ess
Inde
x
Network Size
USP + ITCPFirst−Fit + BFSFirst−Fit + MST
69 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Conclusions
We define the Interference-aware Tree ConstructionProblem for routing and present a polynomial-timeoptimal algorithm to solve it.
The trees constructed by our algorithm outperform MSTand BFS trees.
We present a polynomial-time optimal algorithm for aspecial case of the scheduling problem and an effectiveheuristicd algorithm for the general case.
Compared with other solutions, our routing and schedulingscheme can greatly improve the throughput and fairness.
70 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Conclusions
We define the Interference-aware Tree ConstructionProblem for routing and present a polynomial-timeoptimal algorithm to solve it.
The trees constructed by our algorithm outperform MSTand BFS trees.
We present a polynomial-time optimal algorithm for aspecial case of the scheduling problem and an effectiveheuristicd algorithm for the general case.
Compared with other solutions, our routing and schedulingscheme can greatly improve the throughput and fairness.
71 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Conclusions
We define the Interference-aware Tree ConstructionProblem for routing and present a polynomial-timeoptimal algorithm to solve it.
The trees constructed by our algorithm outperform MSTand BFS trees.
We present a polynomial-time optimal algorithm for aspecial case of the scheduling problem and an effectiveheuristicd algorithm for the general case.
Compared with other solutions, our routing and schedulingscheme can greatly improve the throughput and fairness.
72 / 74
Interference-aware Routing
andSchedulingin WiMAXBackhaulNetworks
with SmartAntennas
CS 440 —ComputerNetworks
Introduction
System Model
ProblemDefinition
Algorithms
Scenarios
Results
Conclusions
Conclusions
We define the Interference-aware Tree ConstructionProblem for routing and present a polynomial-timeoptimal algorithm to solve it.
The trees constructed by our algorithm outperform MSTand BFS trees.
We present a polynomial-time optimal algorithm for aspecial case of the scheduling problem and an effectiveheuristicd algorithm for the general case.
Compared with other solutions, our routing and schedulingscheme can greatly improve the throughput and fairness.
73 / 74