SlideShare a Scribd company logo
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
A downlink scheduler supporting
real time services in LTE cellular
networks
Emmanouil Skondras1, Angelos Michalas2,
Aggeliki Sgora1, Dimitrios D. Vergados1
1Department of Informatics, University of Piraeus, Piraeus, Greece
2Department of Informatics Engineering, Technological Education Institute of
Western Macedonia
1
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Outline
• Introduction
• Resource Allocation Schemes & Algorithms
• The FLSA scheduler
• Simulation Results
– Simulation Setting
– Simulation Results
• Conclusions
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Introduction
• Proposition of a QoS aware scheduler meeting
the requirements of modern services in an LTE
networks.
• A three level scheduler - FLS-Advanced (FLSA).
• FLSA aims at QoS aware resource allocation.
– In order to satisfy the requirements of strict real
times services.
3
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
LTE frame
• The LTE frame length is 10 ms
– It contains 10 subframes with
length equal to 1 ms
– Each subfrace is consisted of 3
slots with 0.5 ms length
• 7 OFDM symbols per slot
• Bandwidth is distributed into
sub-channels with 180 Khz length
– 12 sub-carriers with length 15
KHz per sub-channel
4
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Scheduling Strategies for LTE
• Several downlink packet schedulers have been
proposed in the current literature.
• They can be classified into two groups:
– Non-QoS aware
– QoS aware
• A non-QoS aware scheduler does not take into
account parameters that affect the service quality.
• A QoS aware distributes resources considering the
specific constraints of each service.
5
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Non-QoS aware schedulers
• Maximum Throughput (MT)
• Proportional Fair (PF)
• Throughput to Average (TTA)
• Blind Equal Throughput (BET)
 di
k(t): Available throughput in the kth RB of the ithuser.
 𝑅i(t-1): Past average throughput.
 di(t): Available throughput in the ithuser. 6
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
QoS aware schedulers
• Modified Largest Weighted Delay First (M-LWDF)
• Exponential/PF (EXP/PF)
 DHOL,i: Head of line delay.
 δi: Target packet loss ratio.
 τi: Delay constraint.
 Nrt: The number of active real time flows. 7
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
QoS aware schedulers
• LOG RULE
• EXP RULE
 DHOL,i: Head of line delay.
 Nrt: The number of active real time flows.
 Γi
k: Spectral efficiency for the ith user on the kth subchannel.
 bi and c: Configurable parameters.
8
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
QoS aware schedulers
• Frame Level Scheduler (FLS)
– Two level QoS aware strategy.
– Upper level
• Estimates the ui(k) quota of
data that the ith real time
flow must transmit at the kth
frame to succeed its QoS
constraints.
• Coefficients are used in
order to guarantee the
required delay constraints
for real time flows.
 qi(k): Queue length in the kth frame.
 Mi: the number of coefficients used.
 ci(n): The nth coefficient value.
 τi: The target delay.
9
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
QoS aware schedulers
• Frame Level Scheduler (FLS)
– Lower level
• Uses the PF metric to allocate network resources to real
time flows for transmitting their quota of data.
• Whereas, the remaining resources are allocated to best
effort flows.
10
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
The Proposed Scheduler - FLSA
• It has been built on three distinct levels.
• The three levels cooperate each other.
– For dynamically assigning radio resources to users
in each TTI.
• Real time flows receive higher priority than
the best effort ones.
– Because of their strict service constraints that
must be fulfilled.
11
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
The Proposed Scheduler
12
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
The Upper Level of the Scheduler
• Uses the formula of FLS
– To estimate the quota ui(k) of data that the ith real
time flow should transmit in each kth TTI, to
succeed its QoS constraints.
• ui(k) quota is estimated in each kth TTI of a
frame.
– Whereas in FLS it is estimated once at the
beginning of each kth frame.
13
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
The Upper Level of the Scheduler
• Performance improvement has been observed.
– Due to the fact that:
• In FLS, when a real time flow transmits its ui(k) quota of
data, it loses the opportunity to continue the
transmission until the beginning of the next frame.
– By recalculating the formula in each TTI (instead of
estimating it only at the beginning of each frame):
• The FLSA provides more resources to real time flows that
have remaining data for transmission.
14
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
The Middle Level of the Scheduler
• The use of the QoS aware M-LWDF scheduler:
– Realizes improved resource distribution among the
real time flows.
• In comparison with the FLS scheduler which at the
second level uses the non-QoS aware PF algorithm.
16
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
The Lower Level of the Scheduler
• Allocates the remaining RBs of each TTI to both real
time and best effort flows using the M-LWDF algorithm.
• RBs are allocated to:
– Real time flows
• For transmitting their qi-ui(t) data.
• qi denotes the queue length for the flow i,
– Best effort flows
• Considering the fact they have no specific service constraints.
17
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Performance Evaluation
• The performance of the FLSA was evaluated
against the schedulers:
– PF
– M-LWDF
– EXP/PF
– FLS
– EXP-RULE
– LOG-RULE
• Using the open source simulator LTE-Sim.
19
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Performance Evaluation
• The parameters considered in each scheduler:
20
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Performance Evaluation
• The simulation parameters:
21
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Performance Evaluation
• The simulated topology:
22
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
VoIP packet loss ratio using different
target delays (20 users/cell)
23
• FLSA compared
to the rest
schemes has
the lowest PLR.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Video packet loss ratio using different
target delays (20 users/cell)
24
• FLSA achieves
the lowest
PLR.
• Compared to
FLS presents
up to 7%
lower values.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
VoIP packet loss ratio
25
• FLSA shows a
marginal
decrease of
PLR compared
to FLS.
• The rest
schemes
exhibit worse
PLR values.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Video packet loss ratio
26
• FLSA PLR is 10%
lower than that of
FLS.
• The rest schemes
exhibit worse PLR
values.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
VoIP throughput
27
• FLSA succeeds up
to 330 kbps
higher throughput
than the rest of
the algorithms.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Video throughput
28
• FLSA succeeds up
to 4.7 Mbps higher
throughput than
the rest of the
algorithms.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
VoIP fairness index
29
• The fairness for
all schemes is
close to 1.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Video fairness index
30
• FLSA improves the
fairness compared
to the rest of the
algorithms.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Conclusions
• A three level scheduler - FLS-Advanced (FLSA) to
satisfy real time services.
• The performance of FLSA was tested against other
scheduling algorithms.
• The considered schedulers
– QoS-unaware: PF
– QoS-aware: M-LWDF, EXP/PF, LOG/EXP RULE, FLS
• QoS-aware schedulers support the QoS constraints for
real time flows in LTE.
• FLS-A scheduler achieves better performance in terms
of PLR, attainable throughput and fairness.
IISA 2015
The 6th International Conference on Information, Intelligence, Systems and Applications
Questions ?
32

More Related Content

PPTX
QoS-aware scheduling in LTE-A networks with SDN control (presentation)
PPTX
SDN overview 2014
PDF
Africa Route Collectors Data Analyzer: A compass to support peering growth in...
PDF
Prof. Martyn Guest (Cardiff University) - Data-driven systems medicine
PPTX
An overview of SDN & Openflow
PDF
Pushing the Frontier: Exploring the African Web Ecosystem
PDF
Keynote Speech 1: “Promoting Content in Africa”
PDF
MIPV6 PROTOCOLS: A SURVEY AND COMPARATIVE ANALYSIS
QoS-aware scheduling in LTE-A networks with SDN control (presentation)
SDN overview 2014
Africa Route Collectors Data Analyzer: A compass to support peering growth in...
Prof. Martyn Guest (Cardiff University) - Data-driven systems medicine
An overview of SDN & Openflow
Pushing the Frontier: Exploring the African Web Ecosystem
Keynote Speech 1: “Promoting Content in Africa”
MIPV6 PROTOCOLS: A SURVEY AND COMPARATIVE ANALYSIS

What's hot (14)

PDF
Internet Measurements Infrastructure at KENET
PPTX
National IPv6 Strategies and Migration Plans - ITU Telecom World, Doha 7 Dece...
DOCX
Proposal for System Analysis and Desing
PDF
Cnnic update 1425307402
PDF
Software defined optical communication
PDF
ARIN Update
PDF
IPv6 Readiness Measurement BoF Report
PDF
Crisp_presentation-afrinic22
PDF
IPv6 Deployment: Why and Why not?
PDF
Internet Exchange Points in the Middle East
PDF
PLNOG15: Network Monitoring&Data Analytics at 10/40/100GE speeds. Why spend a...
PDF
SCF Partners' Day: Introduction to XRAN
PDF
Transport SDN & NFV - What does it mean for Optical Networking?
PPT
Project54 Status Report, October 2009
Internet Measurements Infrastructure at KENET
National IPv6 Strategies and Migration Plans - ITU Telecom World, Doha 7 Dece...
Proposal for System Analysis and Desing
Cnnic update 1425307402
Software defined optical communication
ARIN Update
IPv6 Readiness Measurement BoF Report
Crisp_presentation-afrinic22
IPv6 Deployment: Why and Why not?
Internet Exchange Points in the Middle East
PLNOG15: Network Monitoring&Data Analytics at 10/40/100GE speeds. Why spend a...
SCF Partners' Day: Introduction to XRAN
Transport SDN & NFV - What does it mean for Optical Networking?
Project54 Status Report, October 2009
Ad

Similar to A downlink scheduler supporting real time services in LTE cellular networks (presentation) (20)

PPTX
Performance Analysis and Optimization of Next Generation Wireless Networks (P...
PDF
A QoS aware three level scheduler for the LTE downlink
PPTX
Chapter04
PDF
Performance Evaluation of Bidirectional Forwarding Detection (BFD) over the ...
PPT
Protocol For Streaming Media
PDF
Swisscom Network Analytics
PDF
Simulative analysis of channel and qo s aware scheduler to enhance the capaci...
PDF
SIMULATIVE ANALYSIS OF CHANNEL AND QoS AWARE SCHEDULER TO ENHANCE THE CAPACIT...
PDF
Simulative analysis of channel and qo s aware scheduler to enhance the capaci...
PPTX
NetFlow Analyzer Training Part II : Diagnosing and troubleshooting traffic is...
PDF
Edge device multi-unicasting for video streaming
PPT
Active Nets Technology Transfer through High-Performance Network Devices
PPTX
ITNCCNA_NATWORKCOMMUNICATION_Module_17.pptx
PPTX
ITN_Module_17.pptx
PDF
Space legal symposium_2015_lisi
PPTX
The VPOD: Breakthrough Operational Efficiency Improvement For Data Centers
PPTX
The LightConnectTM Fabric V-POD Data Center Architecture
PPT
Session 3 - Emerging technologies.ppt
PDF
17 - Building small network.pdf
PPTX
M1-C17-Armando una red.pptx
Performance Analysis and Optimization of Next Generation Wireless Networks (P...
A QoS aware three level scheduler for the LTE downlink
Chapter04
Performance Evaluation of Bidirectional Forwarding Detection (BFD) over the ...
Protocol For Streaming Media
Swisscom Network Analytics
Simulative analysis of channel and qo s aware scheduler to enhance the capaci...
SIMULATIVE ANALYSIS OF CHANNEL AND QoS AWARE SCHEDULER TO ENHANCE THE CAPACIT...
Simulative analysis of channel and qo s aware scheduler to enhance the capaci...
NetFlow Analyzer Training Part II : Diagnosing and troubleshooting traffic is...
Edge device multi-unicasting for video streaming
Active Nets Technology Transfer through High-Performance Network Devices
ITNCCNA_NATWORKCOMMUNICATION_Module_17.pptx
ITN_Module_17.pptx
Space legal symposium_2015_lisi
The VPOD: Breakthrough Operational Efficiency Improvement For Data Centers
The LightConnectTM Fabric V-POD Data Center Architecture
Session 3 - Emerging technologies.ppt
17 - Building small network.pdf
M1-C17-Armando una red.pptx
Ad

More from University of Piraeus (20)

PDF
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
PPTX
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
PDF
A VHO Scheme for supporting Healthcare Services in 5G Vehicular Cloud Computi...
PDF
A Network Selection Scheme with Adaptive Criteria Weights for 5G Vehicular Sy...
PDF
A Network Selection Algorithm for supporting Drone Services in 5G Network Arc...
PPTX
A Network Selection Algorithm for supporting Drone Services in 5G Network Arc...
PDF
A Survey on Medium Access Control Schemes for 5G Vehicular Cloud Computing Sy...
PPTX
A Survey on Medium Access Control Schemes for 5G Vehicular Cloud Computing Sy...
PDF
The enhancement of Underwater Cultural Heritage Assets using Augmented Realit...
PDF
Mobility Management on 5G Vehicular Cloud Computing Systems
PDF
Performance Analysis and Optimization of Next Generation Wireless Networks
PDF
Personalized Real-Time Virtual Tours in Places with Cultural Interest
PPTX
The Convergence of Blockchain, Internet of Things (IoT) and Building Informat...
PDF
The convergence of blockchain, internet of things (io t) and building informa...
PPTX
The revival of back-filled monuments through Augmented Reality (AR) (presenta...
PDF
An analytic network process and trapezoidal interval-valued fuzzy technique f...
PPT
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standards (presenta...
PPT
A Personalized Audio Server using MPEG-7 and MPEG-21 standards (presentation)
PDF
A Vertical Handover Management Scheme for VANET Cloud Computing Systems
PDF
QoS-aware scheduling in LTE-A networks with SDN control
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
A VHO Scheme for supporting Healthcare Services in 5G Vehicular Cloud Computi...
A Network Selection Scheme with Adaptive Criteria Weights for 5G Vehicular Sy...
A Network Selection Algorithm for supporting Drone Services in 5G Network Arc...
A Network Selection Algorithm for supporting Drone Services in 5G Network Arc...
A Survey on Medium Access Control Schemes for 5G Vehicular Cloud Computing Sy...
A Survey on Medium Access Control Schemes for 5G Vehicular Cloud Computing Sy...
The enhancement of Underwater Cultural Heritage Assets using Augmented Realit...
Mobility Management on 5G Vehicular Cloud Computing Systems
Performance Analysis and Optimization of Next Generation Wireless Networks
Personalized Real-Time Virtual Tours in Places with Cultural Interest
The Convergence of Blockchain, Internet of Things (IoT) and Building Informat...
The convergence of blockchain, internet of things (io t) and building informa...
The revival of back-filled monuments through Augmented Reality (AR) (presenta...
An analytic network process and trapezoidal interval-valued fuzzy technique f...
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standards (presenta...
A Personalized Audio Server using MPEG-7 and MPEG-21 standards (presentation)
A Vertical Handover Management Scheme for VANET Cloud Computing Systems
QoS-aware scheduling in LTE-A networks with SDN control

Recently uploaded (20)

PDF
Building Integrated photovoltaic BIPV_UPV.pdf
PPTX
Understanding_Digital_Forensics_Presentation.pptx
PDF
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
PDF
Diabetes mellitus diagnosis method based random forest with bat algorithm
PDF
Encapsulation theory and applications.pdf
PPTX
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
PPTX
sap open course for s4hana steps from ECC to s4
PPTX
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
PDF
MIND Revenue Release Quarter 2 2025 Press Release
PDF
TokAI - TikTok AI Agent : The First AI Application That Analyzes 10,000+ Vira...
PDF
Unlocking AI with Model Context Protocol (MCP)
PPTX
ACSFv1EN-58255 AWS Academy Cloud Security Foundations.pptx
PDF
Empathic Computing: Creating Shared Understanding
PPTX
20250228 LYD VKU AI Blended-Learning.pptx
PDF
NewMind AI Weekly Chronicles - August'25 Week I
PDF
Encapsulation_ Review paper, used for researhc scholars
DOCX
The AUB Centre for AI in Media Proposal.docx
PDF
Network Security Unit 5.pdf for BCA BBA.
PPTX
MYSQL Presentation for SQL database connectivity
PPTX
Effective Security Operations Center (SOC) A Modern, Strategic, and Threat-In...
Building Integrated photovoltaic BIPV_UPV.pdf
Understanding_Digital_Forensics_Presentation.pptx
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
Diabetes mellitus diagnosis method based random forest with bat algorithm
Encapsulation theory and applications.pdf
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
sap open course for s4hana steps from ECC to s4
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
MIND Revenue Release Quarter 2 2025 Press Release
TokAI - TikTok AI Agent : The First AI Application That Analyzes 10,000+ Vira...
Unlocking AI with Model Context Protocol (MCP)
ACSFv1EN-58255 AWS Academy Cloud Security Foundations.pptx
Empathic Computing: Creating Shared Understanding
20250228 LYD VKU AI Blended-Learning.pptx
NewMind AI Weekly Chronicles - August'25 Week I
Encapsulation_ Review paper, used for researhc scholars
The AUB Centre for AI in Media Proposal.docx
Network Security Unit 5.pdf for BCA BBA.
MYSQL Presentation for SQL database connectivity
Effective Security Operations Center (SOC) A Modern, Strategic, and Threat-In...

A downlink scheduler supporting real time services in LTE cellular networks (presentation)

  • 1. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications A downlink scheduler supporting real time services in LTE cellular networks Emmanouil Skondras1, Angelos Michalas2, Aggeliki Sgora1, Dimitrios D. Vergados1 1Department of Informatics, University of Piraeus, Piraeus, Greece 2Department of Informatics Engineering, Technological Education Institute of Western Macedonia 1
  • 2. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Outline • Introduction • Resource Allocation Schemes & Algorithms • The FLSA scheduler • Simulation Results – Simulation Setting – Simulation Results • Conclusions
  • 3. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Introduction • Proposition of a QoS aware scheduler meeting the requirements of modern services in an LTE networks. • A three level scheduler - FLS-Advanced (FLSA). • FLSA aims at QoS aware resource allocation. – In order to satisfy the requirements of strict real times services. 3
  • 4. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications LTE frame • The LTE frame length is 10 ms – It contains 10 subframes with length equal to 1 ms – Each subfrace is consisted of 3 slots with 0.5 ms length • 7 OFDM symbols per slot • Bandwidth is distributed into sub-channels with 180 Khz length – 12 sub-carriers with length 15 KHz per sub-channel 4
  • 5. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Scheduling Strategies for LTE • Several downlink packet schedulers have been proposed in the current literature. • They can be classified into two groups: – Non-QoS aware – QoS aware • A non-QoS aware scheduler does not take into account parameters that affect the service quality. • A QoS aware distributes resources considering the specific constraints of each service. 5
  • 6. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Non-QoS aware schedulers • Maximum Throughput (MT) • Proportional Fair (PF) • Throughput to Average (TTA) • Blind Equal Throughput (BET)  di k(t): Available throughput in the kth RB of the ithuser.  𝑅i(t-1): Past average throughput.  di(t): Available throughput in the ithuser. 6
  • 7. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications QoS aware schedulers • Modified Largest Weighted Delay First (M-LWDF) • Exponential/PF (EXP/PF)  DHOL,i: Head of line delay.  δi: Target packet loss ratio.  τi: Delay constraint.  Nrt: The number of active real time flows. 7
  • 8. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications QoS aware schedulers • LOG RULE • EXP RULE  DHOL,i: Head of line delay.  Nrt: The number of active real time flows.  Γi k: Spectral efficiency for the ith user on the kth subchannel.  bi and c: Configurable parameters. 8
  • 9. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications QoS aware schedulers • Frame Level Scheduler (FLS) – Two level QoS aware strategy. – Upper level • Estimates the ui(k) quota of data that the ith real time flow must transmit at the kth frame to succeed its QoS constraints. • Coefficients are used in order to guarantee the required delay constraints for real time flows.  qi(k): Queue length in the kth frame.  Mi: the number of coefficients used.  ci(n): The nth coefficient value.  τi: The target delay. 9
  • 10. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications QoS aware schedulers • Frame Level Scheduler (FLS) – Lower level • Uses the PF metric to allocate network resources to real time flows for transmitting their quota of data. • Whereas, the remaining resources are allocated to best effort flows. 10
  • 11. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications The Proposed Scheduler - FLSA • It has been built on three distinct levels. • The three levels cooperate each other. – For dynamically assigning radio resources to users in each TTI. • Real time flows receive higher priority than the best effort ones. – Because of their strict service constraints that must be fulfilled. 11
  • 12. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications The Proposed Scheduler 12
  • 13. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications The Upper Level of the Scheduler • Uses the formula of FLS – To estimate the quota ui(k) of data that the ith real time flow should transmit in each kth TTI, to succeed its QoS constraints. • ui(k) quota is estimated in each kth TTI of a frame. – Whereas in FLS it is estimated once at the beginning of each kth frame. 13
  • 14. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications The Upper Level of the Scheduler • Performance improvement has been observed. – Due to the fact that: • In FLS, when a real time flow transmits its ui(k) quota of data, it loses the opportunity to continue the transmission until the beginning of the next frame. – By recalculating the formula in each TTI (instead of estimating it only at the beginning of each frame): • The FLSA provides more resources to real time flows that have remaining data for transmission. 14
  • 15. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications The Middle Level of the Scheduler • The use of the QoS aware M-LWDF scheduler: – Realizes improved resource distribution among the real time flows. • In comparison with the FLS scheduler which at the second level uses the non-QoS aware PF algorithm. 16
  • 16. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications The Lower Level of the Scheduler • Allocates the remaining RBs of each TTI to both real time and best effort flows using the M-LWDF algorithm. • RBs are allocated to: – Real time flows • For transmitting their qi-ui(t) data. • qi denotes the queue length for the flow i, – Best effort flows • Considering the fact they have no specific service constraints. 17
  • 17. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Performance Evaluation • The performance of the FLSA was evaluated against the schedulers: – PF – M-LWDF – EXP/PF – FLS – EXP-RULE – LOG-RULE • Using the open source simulator LTE-Sim. 19
  • 18. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Performance Evaluation • The parameters considered in each scheduler: 20
  • 19. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Performance Evaluation • The simulation parameters: 21
  • 20. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Performance Evaluation • The simulated topology: 22
  • 21. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications VoIP packet loss ratio using different target delays (20 users/cell) 23 • FLSA compared to the rest schemes has the lowest PLR.
  • 22. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Video packet loss ratio using different target delays (20 users/cell) 24 • FLSA achieves the lowest PLR. • Compared to FLS presents up to 7% lower values.
  • 23. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications VoIP packet loss ratio 25 • FLSA shows a marginal decrease of PLR compared to FLS. • The rest schemes exhibit worse PLR values.
  • 24. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Video packet loss ratio 26 • FLSA PLR is 10% lower than that of FLS. • The rest schemes exhibit worse PLR values.
  • 25. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications VoIP throughput 27 • FLSA succeeds up to 330 kbps higher throughput than the rest of the algorithms.
  • 26. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Video throughput 28 • FLSA succeeds up to 4.7 Mbps higher throughput than the rest of the algorithms.
  • 27. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications VoIP fairness index 29 • The fairness for all schemes is close to 1.
  • 28. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Video fairness index 30 • FLSA improves the fairness compared to the rest of the algorithms.
  • 29. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Conclusions • A three level scheduler - FLS-Advanced (FLSA) to satisfy real time services. • The performance of FLSA was tested against other scheduling algorithms. • The considered schedulers – QoS-unaware: PF – QoS-aware: M-LWDF, EXP/PF, LOG/EXP RULE, FLS • QoS-aware schedulers support the QoS constraints for real time flows in LTE. • FLS-A scheduler achieves better performance in terms of PLR, attainable throughput and fairness.
  • 30. IISA 2015 The 6th International Conference on Information, Intelligence, Systems and Applications Questions ? 32