SlideShare a Scribd company logo
1 of 18
Adaptive Video Streaming for
Device-to-Device Mobile Platforms
ACM MobiCom-2013 (Demo)

Students (USC):
Joongheon Kim, Feiyu Meng, Peiyao Chen, Hilmi E. Egilmez, Dilip Bethanabhotla
Professors (USC):
Dr. Andreas F. Molisch, Dr. Giuseppe Caire, Dr. Michael J. Neely, Dr. Antonio Ortega
1
System Model
u1

u2

u1

u2

Helpers (Wireless/Mobile Video Servers)
• Maintain Multiple Queues for Individual Users

h1

u1

h2

u2

Users (Smartphone Users)
• Operation: Admission Control
 Determining quality mode of each chunk based on
DPP algorithm for network utility maximization
• Download chunks from Helpers

[Reference] D. Bethanabhotla, G. Caire, and M. J. Neely, "Joint Transmission Scheduling and Congestion Control for Adaptive Streaming in Wireless
Device-to-Device Networks,” Proc. Asilomar 2012. (Journal Version: http://arxiv.org/abs/1304.8083)

2
Operational Example
[Example-Based Explanation]
• User requests desired video to two helpers.

Helper 2
WiFi-AP

Helper 1
WiFi-AP

5

User
WiFi-Station
Operational Example
[Example-Based Explanation]

Helper 2
WiFi-AP

Helper 1
WiFi-AP

0

6

User
WiFi-Station

0

• User requests desired video to two helpers.
• Both helpers will reply zero (which is current backlog size).
Operational Example
[Example-Based Explanation]

s13

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s12
s11

7

User
WiFi-Station

• User requests desired video to two helpers.
• Both helpers will reply zero (which is current backlog size).
• User does the random selection (helper 1 is selected).
And the user lets helper 1 know that it should place
the sub-chunks of chunk 1 (i.e., s11, s12, s13).
Operational Example
[Example-Based Explanation]

s13

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s12
s11

8

User
WiFi-Station

• User requests desired video to two helpers.
• Both helpers will reply zero (which is current backlog size).
• User does the random selection (helper 1 is selected).
And the user lets helper 1 know that it should place
the sub-chunks of chunk 1 (i.e., s11, s12, s13).
• User requests next chunks (i.e., c2) to two helpers.
Operational Example
[Example-Based Explanation]

s13

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s12
s11

3

9

User
WiFi-Station

0

• User requests desired video to two helpers.
• Both helpers will reply zero (which is current backlog size).
• User does the random selection (helper 1 is selected).
And the user lets helper 1 know that it should place
the sub-chunks of chunk 1 (i.e., s11, s12, s13).
• User requests next chunks (i.e., c2) to two helpers.
• Helper 1 will reply 3 and helper 2 will reply 0.
Operational Example
[Example-Based Explanation]

s13

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s23

s12

s22

s11

s21

10

User
WiFi-Station

• User requests desired video to two helpers.
• Both helpers will reply zero (which is current backlog size).
• User does the random selection (helper 1 is selected).
And the user lets helper 1 know that it should place
the sub-chunks of chunk 1 (i.e., s11, s12, s13).
• User requests next chunks (i.e., c2) to two helpers.
• Helper 1 will reply 3 and helper 2 will reply 0.
• User selects the one which has the smallest queue backlog
size. Thus, helper 2 is selected. And the user lets helper 2
know that it should place the sub-chunks of chunk 2.
Operational Example
[Example-Based Explanation]

s13

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s23

s12

s22

s11

s21

• Now, instead of doing transmission scheduling,
User selects helper 1 because user needs s11
in terms of playback order and user knows that helper 1
has the one (Greedy Pull for Minimum Delay).

I need
s11

11

• User requests desired video to two helpers.
• Both helpers will reply zero (which is current backlog size).
• User does the random selection (helper 1 is selected).
And the user lets helper 1 know that it should place
the sub-chunks of chunk 1 (i.e., s11, s12, s13).
• User requests next chunks (i.e., c2) to two helpers.
• Helper 1 will reply 3 and helper 2 will reply 0.
• User selects the one which has the smallest queue backlog
size. Thus, helper 2 is selected. And the user lets helper 2
know that it should place the sub-chunks of chunk 2.

User
WiFi-Station
Operational Example
[Example-Based Explanation]

Helper 2
WiFi-AP

Helper 1
WiFi-AP

• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is bad, so, helper 1 can transmit only one, i.e., s11.

s23

s13

s22

s12

s21
s11

s11

12

User
WiFi-Station
Operational Example
[Example-Based Explanation]

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s23

s13

s22

s12

s21

s11

13

User
WiFi-Station

• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is bad, so, helper 1 can transmit only one, i.e., s11.
• User requests next chunk (i.e., c3) to two helpers.
Operational Example
[Example-Based Explanation]

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s23

s13

s22

s12

s21

2

3

s11

14

User
WiFi-Station

• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is bad, so, helper 1 can transmit only one, i.e., s11.
• User requests next chunk (i.e., c3) to two helpers.
• Helper 1 will reply 2 and helper 2 will reply 3.
Operational Example
[Example-Based Explanation]

s33
s32
s31

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s23

s13

s22

s12

s21

s11

15

User
WiFi-Station

• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is bad, so, helper 1 can transmit only one, i.e., s11.
• User requests next chunk (i.e., c3) to two helpers.
• Helper 1 will reply 2 and helper 2 will reply 3.
• User selects the one which has the smallest queue backlog
size. Thus, helper 1 is selected. And the user lets helper 1
know that it should place the sub-chunks of chunk 3.
Operational Example
[Example-Based Explanation]

s33
s32
s31

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s23

s13

s22

s12

s21

• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is bad, so, helper 1 can transmit only one, i.e., s11.
• User requests next chunk (i.e., c3) to two helpers.
• Helper 1 will reply 2 and helper 2 will reply 3.
• User selects the one which has the smallest queue backlog
size. Thus, helper 1 is selected. And the user lets helper 1
know that it should place the sub-chunks of chunk 3.
• Now, instead of doing transmission scheduling,
User selects helper 1 again because user needs s12
in terms of playback order and user knows that helper 1
has the one (Greedy Pull for Minimum Delay).

s11

I need
s12

16

User
WiFi-Station
Operational Example
[Example-Based Explanation]

s33
s32

Helper 2
WiFi-AP

Helper 1
WiFi-AP

• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is bad, so, helper 1 can transmit only one, i.e., s12.

s23

s31

s22

s13

s21
s12

s11
s12

17

User
WiFi-Station
Operational Example
[Example-Based Explanation]

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s23
s22

s33

s21
s13
s31
s32

s11
s12

I need
s13

18

s13
User
WiFi-Station

s31
s32

• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is bad, so, helper 1 can transmit only one, i.e., s12.
• (User doesn’t request chunks because c3 was the last one)
• Now, instead of doing transmission scheduling,
User selects helper 1 again because user needs s13
in terms of playback order and user knows that helper 1
has the one (Greedy Pull for Minimum Delay).
• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is good, so, helper 1 can transmit three.
Operational Example
[Example-Based Explanation]

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s33

• Now, instead of doing transmission scheduling,
User selects helper 2 because user needs s21
in terms of playback order and user knows that helper 2
has the one (Greedy Pull for Minimum Delay).
• Helper 2 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is good, so, helper 1 can transmit three.

s23
s22
s21

s11
s12

19

User
WiFi-Station

s22

s13

I need
s21

s23
s21

s31
s32
Operational Example
[Example-Based Explanation]
• Now, instead of doing transmission scheduling,
User selects helper 2 because user needs s33
in terms of playback order and user knows that helper 1
has the one (Greedy Pull for Minimum Delay).
• Helper 1 transmits sub-chunks for the given time. If RSSI
is good, then it can transmit more. Now, suppose that the
channel is good, so, helper 1 can transmit the all of
remaining sub-chunks.

Helper 2
WiFi-AP

Helper 1
WiFi-AP

s33

s11
s12

20

User
WiFi-Station

s22

s13

I need
s33

s23
s21

s31

s33

s32

More Related Content

What's hot

Delays in packet switch network
Delays in packet switch networkDelays in packet switch network
Delays in packet switch networkShanza Sohail
 
Multiple Access Methods
Multiple Access MethodsMultiple Access Methods
Multiple Access MethodsPrateek Soni
 
Comparison of TCP congestion control mechanisms Tahoe, Newreno and Vegas
Comparison of TCP congestion control mechanisms Tahoe, Newreno and VegasComparison of TCP congestion control mechanisms Tahoe, Newreno and Vegas
Comparison of TCP congestion control mechanisms Tahoe, Newreno and VegasIOSR Journals
 
Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...
Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...
Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...CA Technologies
 
Data linkcontrol
Data linkcontrolData linkcontrol
Data linkcontrolBablu Shofi
 
A Data Transmission Technique Based On RSSI in an Ad-Hoc Network
A Data Transmission Technique Based On RSSI in an Ad-Hoc NetworkA Data Transmission Technique Based On RSSI in an Ad-Hoc Network
A Data Transmission Technique Based On RSSI in an Ad-Hoc NetworkIOSR Journals
 
Protocol implementation on NS2
Protocol implementation on NS2Protocol implementation on NS2
Protocol implementation on NS2amreshrai02
 
Example problems
Example problemsExample problems
Example problemsdeepakps22
 
Mediumaccesscontrol
MediumaccesscontrolMediumaccesscontrol
MediumaccesscontrolVk Sreedhar
 
A preamble-based approach for Providing QOS support in Wireless Sensor Network
A preamble-based approach for Providing QOS support in Wireless Sensor NetworkA preamble-based approach for Providing QOS support in Wireless Sensor Network
A preamble-based approach for Providing QOS support in Wireless Sensor Networkdiala wedyan
 
Multiple Access Techniques
Multiple Access TechniquesMultiple Access Techniques
Multiple Access Techniquesinayat khan
 
Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...
Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...
Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...Seung-gyu Byeon
 

What's hot (18)

Delays in packet switch network
Delays in packet switch networkDelays in packet switch network
Delays in packet switch network
 
Multiple Access Methods
Multiple Access MethodsMultiple Access Methods
Multiple Access Methods
 
Comparison of TCP congestion control mechanisms Tahoe, Newreno and Vegas
Comparison of TCP congestion control mechanisms Tahoe, Newreno and VegasComparison of TCP congestion control mechanisms Tahoe, Newreno and Vegas
Comparison of TCP congestion control mechanisms Tahoe, Newreno and Vegas
 
Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...
Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...
Pre-Con Education: Recognizing Your Network's Key Performance Indicators Th...
 
Data linkcontrol
Data linkcontrolData linkcontrol
Data linkcontrol
 
Advanced networking - scheduling and QoS part 1
Advanced networking - scheduling and QoS part 1Advanced networking - scheduling and QoS part 1
Advanced networking - scheduling and QoS part 1
 
Multiple access protocol
Multiple access protocolMultiple access protocol
Multiple access protocol
 
A Data Transmission Technique Based On RSSI in an Ad-Hoc Network
A Data Transmission Technique Based On RSSI in an Ad-Hoc NetworkA Data Transmission Technique Based On RSSI in an Ad-Hoc Network
A Data Transmission Technique Based On RSSI in an Ad-Hoc Network
 
Mac sub layer
Mac sub layerMac sub layer
Mac sub layer
 
Protocol implementation on NS2
Protocol implementation on NS2Protocol implementation on NS2
Protocol implementation on NS2
 
Rumor riding
Rumor ridingRumor riding
Rumor riding
 
Example problems
Example problemsExample problems
Example problems
 
Mediumaccesscontrol
MediumaccesscontrolMediumaccesscontrol
Mediumaccesscontrol
 
Ns2
Ns2Ns2
Ns2
 
A preamble-based approach for Providing QOS support in Wireless Sensor Network
A preamble-based approach for Providing QOS support in Wireless Sensor NetworkA preamble-based approach for Providing QOS support in Wireless Sensor Network
A preamble-based approach for Providing QOS support in Wireless Sensor Network
 
Multiple Access Techniques
Multiple Access TechniquesMultiple Access Techniques
Multiple Access Techniques
 
Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...
Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...
Mncs 16-08-3주-변승규-opportunistic flooding in low-duty-cycle wireless sensor ne...
 
Message passing in Distributed Computing Systems
Message passing in Distributed Computing SystemsMessage passing in Distributed Computing Systems
Message passing in Distributed Computing Systems
 

Viewers also liked

Marco nunes correia aves
Marco nunes correia   avesMarco nunes correia   aves
Marco nunes correia avesJosé Palma
 
Margaret mee 100 anos de vida e obra
Margaret mee 100 anos de vida e obraMargaret mee 100 anos de vida e obra
Margaret mee 100 anos de vida e obraJosé Palma
 
Pierre joseph redouté (1759 – 1840)
Pierre joseph redouté (1759 – 1840)Pierre joseph redouté (1759 – 1840)
Pierre joseph redouté (1759 – 1840)José Palma
 
Файлы и файловые структуры
Файлы и файловые структурыФайлы и файловые структуры
Файлы и файловые структурыkvlar
 
Complex Systems Approach to Emotionally-aware Learning Environments
Complex Systems Approach to Emotionally-aware Learning EnvironmentsComplex Systems Approach to Emotionally-aware Learning Environments
Complex Systems Approach to Emotionally-aware Learning EnvironmentsAladdin Ayesh
 
Proposal P2P regulation for belgium
Proposal P2P regulation for belgiumProposal P2P regulation for belgium
Proposal P2P regulation for belgiumAngelo Meuleman
 
книготерапия
книготерапиякниготерапия
книготерапияliudsege
 
JBM Global, Top Boarding School in Noida
JBM Global, Top Boarding School in NoidaJBM Global, Top Boarding School in Noida
JBM Global, Top Boarding School in NoidaJBM Global School
 
Atrapasueños atrapasoños
Atrapasueños atrapasoñosAtrapasueños atrapasoños
Atrapasueños atrapasoñosisabelvillar
 
Rosas de pj redouté
Rosas de pj redoutéRosas de pj redouté
Rosas de pj redoutéJosé Palma
 

Viewers also liked (18)

Replacing Laptop Harddrive
Replacing Laptop HarddriveReplacing Laptop Harddrive
Replacing Laptop Harddrive
 
Marco nunes correia aves
Marco nunes correia   avesMarco nunes correia   aves
Marco nunes correia aves
 
Margaret mee 100 anos de vida e obra
Margaret mee 100 anos de vida e obraMargaret mee 100 anos de vida e obra
Margaret mee 100 anos de vida e obra
 
Pierre joseph redouté (1759 – 1840)
Pierre joseph redouté (1759 – 1840)Pierre joseph redouté (1759 – 1840)
Pierre joseph redouté (1759 – 1840)
 
Файлы и файловые структуры
Файлы и файловые структурыФайлы и файловые структуры
Файлы и файловые структуры
 
PRADEEP MORYA
PRADEEP MORYAPRADEEP MORYA
PRADEEP MORYA
 
Complex Systems Approach to Emotionally-aware Learning Environments
Complex Systems Approach to Emotionally-aware Learning EnvironmentsComplex Systems Approach to Emotionally-aware Learning Environments
Complex Systems Approach to Emotionally-aware Learning Environments
 
ICT SSE class 1
ICT SSE class 1ICT SSE class 1
ICT SSE class 1
 
Proposal P2P regulation for belgium
Proposal P2P regulation for belgiumProposal P2P regulation for belgium
Proposal P2P regulation for belgium
 
RESUME pinaki1
RESUME pinaki1RESUME pinaki1
RESUME pinaki1
 
книготерапия
книготерапиякниготерапия
книготерапия
 
Ithink
IthinkIthink
Ithink
 
JBM Global, Top Boarding School in Noida
JBM Global, Top Boarding School in NoidaJBM Global, Top Boarding School in Noida
JBM Global, Top Boarding School in Noida
 
Bender taller
Bender tallerBender taller
Bender taller
 
Tema 10 - La diversidad de los paisajes agrarios españoles.
Tema 10 - La diversidad de los paisajes agrarios españoles.Tema 10 - La diversidad de los paisajes agrarios españoles.
Tema 10 - La diversidad de los paisajes agrarios españoles.
 
Atrapasueños atrapasoños
Atrapasueños atrapasoñosAtrapasueños atrapasoños
Atrapasueños atrapasoños
 
Devolucion
DevolucionDevolucion
Devolucion
 
Rosas de pj redouté
Rosas de pj redoutéRosas de pj redouté
Rosas de pj redouté
 

Similar to Mobicom2013 demo

Integrated Active Filters using low gain modules
Integrated Active Filters using low gain modulesIntegrated Active Filters using low gain modules
Integrated Active Filters using low gain modulesIDES Editor
 
VTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION) SOLVED PAPERS
VTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION)  SOLVED PAPERSVTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION)  SOLVED PAPERS
VTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION) SOLVED PAPERSvtunotesbysree
 
Domain model example
Domain model exampleDomain model example
Domain model exampleHeba Fathy
 
11-23-0034-01-0uhr-non-primary-channel-utilization.pptx
11-23-0034-01-0uhr-non-primary-channel-utilization.pptx11-23-0034-01-0uhr-non-primary-channel-utilization.pptx
11-23-0034-01-0uhr-non-primary-channel-utilization.pptxSlideshare986556
 
Importance of sliding window protocol
Importance of sliding window protocolImportance of sliding window protocol
Importance of sliding window protocoleSAT Journals
 
Importance of sliding window protocol
Importance of sliding window protocolImportance of sliding window protocol
Importance of sliding window protocoleSAT Publishing House
 
Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...eSAT Journals
 
Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...eSAT Publishing House
 
Unit 2 data link control
Unit 2 data link controlUnit 2 data link control
Unit 2 data link controlVishal kakade
 
Data Link Control Protocols
Data Link Control ProtocolsData Link Control Protocols
Data Link Control ProtocolsTechiNerd
 
Enhancement of Throughput & Spectrum Sensing of Cognitive Radio Networks
Enhancement of Throughput & Spectrum Sensing of Cognitive Radio NetworksEnhancement of Throughput & Spectrum Sensing of Cognitive Radio Networks
Enhancement of Throughput & Spectrum Sensing of Cognitive Radio NetworksIRJET Journal
 
Client Side Secure De-Duplication Scheme in Cloud Storage Environment
Client Side Secure De-Duplication Scheme in Cloud Storage EnvironmentClient Side Secure De-Duplication Scheme in Cloud Storage Environment
Client Side Secure De-Duplication Scheme in Cloud Storage EnvironmentIRJET Journal
 
Design of a Microstrip Ultrawide Band Bandpass Filter using Short Stub Loaded
Design of a Microstrip Ultrawide Band Bandpass Filter using Short Stub LoadedDesign of a Microstrip Ultrawide Band Bandpass Filter using Short Stub Loaded
Design of a Microstrip Ultrawide Band Bandpass Filter using Short Stub LoadedIRJET Journal
 
DUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTER
DUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTERDUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTER
DUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTERjmicro
 
Effect of Varying Segment Size on DASH Streaming Quality for Mobile User
Effect of Varying Segment Size on DASH Streaming Quality for Mobile UserEffect of Varying Segment Size on DASH Streaming Quality for Mobile User
Effect of Varying Segment Size on DASH Streaming Quality for Mobile UserYomna Mahmoud Ibrahim Hassan
 

Similar to Mobicom2013 demo (20)

Integrated Active Filters using low gain modules
Integrated Active Filters using low gain modulesIntegrated Active Filters using low gain modules
Integrated Active Filters using low gain modules
 
VTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION) SOLVED PAPERS
VTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION)  SOLVED PAPERSVTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION)  SOLVED PAPERS
VTU 5TH SEM CSE COMPUTER NETWORKS-1 (DATA COMMUNICATION) SOLVED PAPERS
 
Domain model example
Domain model exampleDomain model example
Domain model example
 
11-23-0034-01-0uhr-non-primary-channel-utilization.pptx
11-23-0034-01-0uhr-non-primary-channel-utilization.pptx11-23-0034-01-0uhr-non-primary-channel-utilization.pptx
11-23-0034-01-0uhr-non-primary-channel-utilization.pptx
 
The medium access sublayer
 The medium  access sublayer The medium  access sublayer
The medium access sublayer
 
Importance of sliding window protocol
Importance of sliding window protocolImportance of sliding window protocol
Importance of sliding window protocol
 
Importance of sliding window protocol
Importance of sliding window protocolImportance of sliding window protocol
Importance of sliding window protocol
 
Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...
 
Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...Performance evaluation of broadcast mac and aloha mac protocol for underwater...
Performance evaluation of broadcast mac and aloha mac protocol for underwater...
 
Ab4103161168
Ab4103161168Ab4103161168
Ab4103161168
 
R1 050888
R1 050888R1 050888
R1 050888
 
Channel quality
Channel qualityChannel quality
Channel quality
 
Unit 2 data link control
Unit 2 data link controlUnit 2 data link control
Unit 2 data link control
 
Data Link Control Protocols
Data Link Control ProtocolsData Link Control Protocols
Data Link Control Protocols
 
Enhancement of Throughput & Spectrum Sensing of Cognitive Radio Networks
Enhancement of Throughput & Spectrum Sensing of Cognitive Radio NetworksEnhancement of Throughput & Spectrum Sensing of Cognitive Radio Networks
Enhancement of Throughput & Spectrum Sensing of Cognitive Radio Networks
 
Client Side Secure De-Duplication Scheme in Cloud Storage Environment
Client Side Secure De-Duplication Scheme in Cloud Storage EnvironmentClient Side Secure De-Duplication Scheme in Cloud Storage Environment
Client Side Secure De-Duplication Scheme in Cloud Storage Environment
 
Design of a Microstrip Ultrawide Band Bandpass Filter using Short Stub Loaded
Design of a Microstrip Ultrawide Band Bandpass Filter using Short Stub LoadedDesign of a Microstrip Ultrawide Band Bandpass Filter using Short Stub Loaded
Design of a Microstrip Ultrawide Band Bandpass Filter using Short Stub Loaded
 
DUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTER
DUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTERDUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTER
DUAL PORT COGNITIVE RADIO ANTENNA USING TUNABLE BAND PASS FILTER
 
CN.pptx
CN.pptxCN.pptx
CN.pptx
 
Effect of Varying Segment Size on DASH Streaming Quality for Mobile User
Effect of Varying Segment Size on DASH Streaming Quality for Mobile UserEffect of Varying Segment Size on DASH Streaming Quality for Mobile User
Effect of Varying Segment Size on DASH Streaming Quality for Mobile User
 

Recently uploaded

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
Google AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAGGoogle AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAGSujit Pal
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...gurkirankumar98700
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...HostedbyConfluent
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 

Recently uploaded (20)

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
Google AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAGGoogle AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAG
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 

Mobicom2013 demo

  • 1. Adaptive Video Streaming for Device-to-Device Mobile Platforms ACM MobiCom-2013 (Demo) Students (USC): Joongheon Kim, Feiyu Meng, Peiyao Chen, Hilmi E. Egilmez, Dilip Bethanabhotla Professors (USC): Dr. Andreas F. Molisch, Dr. Giuseppe Caire, Dr. Michael J. Neely, Dr. Antonio Ortega 1
  • 2. System Model u1 u2 u1 u2 Helpers (Wireless/Mobile Video Servers) • Maintain Multiple Queues for Individual Users h1 u1 h2 u2 Users (Smartphone Users) • Operation: Admission Control  Determining quality mode of each chunk based on DPP algorithm for network utility maximization • Download chunks from Helpers [Reference] D. Bethanabhotla, G. Caire, and M. J. Neely, "Joint Transmission Scheduling and Congestion Control for Adaptive Streaming in Wireless Device-to-Device Networks,” Proc. Asilomar 2012. (Journal Version: http://arxiv.org/abs/1304.8083) 2
  • 3. Operational Example [Example-Based Explanation] • User requests desired video to two helpers. Helper 2 WiFi-AP Helper 1 WiFi-AP 5 User WiFi-Station
  • 4. Operational Example [Example-Based Explanation] Helper 2 WiFi-AP Helper 1 WiFi-AP 0 6 User WiFi-Station 0 • User requests desired video to two helpers. • Both helpers will reply zero (which is current backlog size).
  • 5. Operational Example [Example-Based Explanation] s13 Helper 2 WiFi-AP Helper 1 WiFi-AP s12 s11 7 User WiFi-Station • User requests desired video to two helpers. • Both helpers will reply zero (which is current backlog size). • User does the random selection (helper 1 is selected). And the user lets helper 1 know that it should place the sub-chunks of chunk 1 (i.e., s11, s12, s13).
  • 6. Operational Example [Example-Based Explanation] s13 Helper 2 WiFi-AP Helper 1 WiFi-AP s12 s11 8 User WiFi-Station • User requests desired video to two helpers. • Both helpers will reply zero (which is current backlog size). • User does the random selection (helper 1 is selected). And the user lets helper 1 know that it should place the sub-chunks of chunk 1 (i.e., s11, s12, s13). • User requests next chunks (i.e., c2) to two helpers.
  • 7. Operational Example [Example-Based Explanation] s13 Helper 2 WiFi-AP Helper 1 WiFi-AP s12 s11 3 9 User WiFi-Station 0 • User requests desired video to two helpers. • Both helpers will reply zero (which is current backlog size). • User does the random selection (helper 1 is selected). And the user lets helper 1 know that it should place the sub-chunks of chunk 1 (i.e., s11, s12, s13). • User requests next chunks (i.e., c2) to two helpers. • Helper 1 will reply 3 and helper 2 will reply 0.
  • 8. Operational Example [Example-Based Explanation] s13 Helper 2 WiFi-AP Helper 1 WiFi-AP s23 s12 s22 s11 s21 10 User WiFi-Station • User requests desired video to two helpers. • Both helpers will reply zero (which is current backlog size). • User does the random selection (helper 1 is selected). And the user lets helper 1 know that it should place the sub-chunks of chunk 1 (i.e., s11, s12, s13). • User requests next chunks (i.e., c2) to two helpers. • Helper 1 will reply 3 and helper 2 will reply 0. • User selects the one which has the smallest queue backlog size. Thus, helper 2 is selected. And the user lets helper 2 know that it should place the sub-chunks of chunk 2.
  • 9. Operational Example [Example-Based Explanation] s13 Helper 2 WiFi-AP Helper 1 WiFi-AP s23 s12 s22 s11 s21 • Now, instead of doing transmission scheduling, User selects helper 1 because user needs s11 in terms of playback order and user knows that helper 1 has the one (Greedy Pull for Minimum Delay). I need s11 11 • User requests desired video to two helpers. • Both helpers will reply zero (which is current backlog size). • User does the random selection (helper 1 is selected). And the user lets helper 1 know that it should place the sub-chunks of chunk 1 (i.e., s11, s12, s13). • User requests next chunks (i.e., c2) to two helpers. • Helper 1 will reply 3 and helper 2 will reply 0. • User selects the one which has the smallest queue backlog size. Thus, helper 2 is selected. And the user lets helper 2 know that it should place the sub-chunks of chunk 2. User WiFi-Station
  • 10. Operational Example [Example-Based Explanation] Helper 2 WiFi-AP Helper 1 WiFi-AP • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is bad, so, helper 1 can transmit only one, i.e., s11. s23 s13 s22 s12 s21 s11 s11 12 User WiFi-Station
  • 11. Operational Example [Example-Based Explanation] Helper 2 WiFi-AP Helper 1 WiFi-AP s23 s13 s22 s12 s21 s11 13 User WiFi-Station • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is bad, so, helper 1 can transmit only one, i.e., s11. • User requests next chunk (i.e., c3) to two helpers.
  • 12. Operational Example [Example-Based Explanation] Helper 2 WiFi-AP Helper 1 WiFi-AP s23 s13 s22 s12 s21 2 3 s11 14 User WiFi-Station • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is bad, so, helper 1 can transmit only one, i.e., s11. • User requests next chunk (i.e., c3) to two helpers. • Helper 1 will reply 2 and helper 2 will reply 3.
  • 13. Operational Example [Example-Based Explanation] s33 s32 s31 Helper 2 WiFi-AP Helper 1 WiFi-AP s23 s13 s22 s12 s21 s11 15 User WiFi-Station • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is bad, so, helper 1 can transmit only one, i.e., s11. • User requests next chunk (i.e., c3) to two helpers. • Helper 1 will reply 2 and helper 2 will reply 3. • User selects the one which has the smallest queue backlog size. Thus, helper 1 is selected. And the user lets helper 1 know that it should place the sub-chunks of chunk 3.
  • 14. Operational Example [Example-Based Explanation] s33 s32 s31 Helper 2 WiFi-AP Helper 1 WiFi-AP s23 s13 s22 s12 s21 • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is bad, so, helper 1 can transmit only one, i.e., s11. • User requests next chunk (i.e., c3) to two helpers. • Helper 1 will reply 2 and helper 2 will reply 3. • User selects the one which has the smallest queue backlog size. Thus, helper 1 is selected. And the user lets helper 1 know that it should place the sub-chunks of chunk 3. • Now, instead of doing transmission scheduling, User selects helper 1 again because user needs s12 in terms of playback order and user knows that helper 1 has the one (Greedy Pull for Minimum Delay). s11 I need s12 16 User WiFi-Station
  • 15. Operational Example [Example-Based Explanation] s33 s32 Helper 2 WiFi-AP Helper 1 WiFi-AP • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is bad, so, helper 1 can transmit only one, i.e., s12. s23 s31 s22 s13 s21 s12 s11 s12 17 User WiFi-Station
  • 16. Operational Example [Example-Based Explanation] Helper 2 WiFi-AP Helper 1 WiFi-AP s23 s22 s33 s21 s13 s31 s32 s11 s12 I need s13 18 s13 User WiFi-Station s31 s32 • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is bad, so, helper 1 can transmit only one, i.e., s12. • (User doesn’t request chunks because c3 was the last one) • Now, instead of doing transmission scheduling, User selects helper 1 again because user needs s13 in terms of playback order and user knows that helper 1 has the one (Greedy Pull for Minimum Delay). • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is good, so, helper 1 can transmit three.
  • 17. Operational Example [Example-Based Explanation] Helper 2 WiFi-AP Helper 1 WiFi-AP s33 • Now, instead of doing transmission scheduling, User selects helper 2 because user needs s21 in terms of playback order and user knows that helper 2 has the one (Greedy Pull for Minimum Delay). • Helper 2 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is good, so, helper 1 can transmit three. s23 s22 s21 s11 s12 19 User WiFi-Station s22 s13 I need s21 s23 s21 s31 s32
  • 18. Operational Example [Example-Based Explanation] • Now, instead of doing transmission scheduling, User selects helper 2 because user needs s33 in terms of playback order and user knows that helper 1 has the one (Greedy Pull for Minimum Delay). • Helper 1 transmits sub-chunks for the given time. If RSSI is good, then it can transmit more. Now, suppose that the channel is good, so, helper 1 can transmit the all of remaining sub-chunks. Helper 2 WiFi-AP Helper 1 WiFi-AP s33 s11 s12 20 User WiFi-Station s22 s13 I need s33 s23 s21 s31 s33 s32