lookback scheduling for long-term quality-of-service over multiple cells hatem abou-zeid*, stefan...
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Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Lookback Scheduling for Long-Term Quality-of-Service Over
Multiple Cells
Hatem Abou-zeid*, Stefan Valentin†, Hossam S. Hassanein*, and Mohamed F. Feteiha*
* Queen’s University, Canada
†Bell Labs, Alcatel-Lucent, Germany
QoS and QoE in Wireless Communications/Networks Workshop
(QoS-QoE 2013), 9th IWCMC’13, Cagliari, Italy.
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Introduction: Downlink Scheduling Basics
Proportional-Fair Scheduler (PF): Schedule user with highest
Throughput-fairness balance Ri(t) computed over a window Tw
)([
)([
tRtr
i
i
Rate] Average Condition] Channel
Base Station
User Queues
Incoming user data from the core network .
.
.
.
.
.
User Playback Buffers
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Introduction: Downlink Scheduling
Exponential Scheduler (EXP): Schedule user with highest
Idea: when a user queue increases relative to average queues, the user is prioritized exponentially
Base Station
User Queues
Incoming user data from the core network .
.
.
.
.
.
User Playback Buffers
N
i i
N
i ii
i
i
tqN
tqN
tq
tRtr
1
1
)(1
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)(exp)(
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Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Traditional Scheduling: Short-term QoS Indicators
Traditionally, schedulers employ QoS indicators such as average rates Ri(t) to provide service guarantees and fairness.
These indicators are usually computed over a short duration, typically a few seconds.
Further, QoS indictor information from prior cells is not transferred to the user’s current cell
The QoS a user receives in one cell will not impact the future QoS in upcoming cells as
BSs only know the user QoS in their cell
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Today’s networks have fluctuating demand: in different cells at different times of the dayÞ network traffic is uneven in space and time
Today’s mobile usage involves: Longer user sessions and more video content Highly mobile usersÞ users traverse multiple cells during a single session
Motivation for Proposing Long-term QoS
5
Users receive variable QoS as they move
throughout the network
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Long-term notion of scheduling enables cell cooperation over time by looking back
Users served poorly in congested cells can be compensated in future cells
Proposal: BSs monitor and exchange long-term user QoS
Long-Term Multi-cell QoS
6
Result: improve long-term user satisfaction and reduce
subscriber churn
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Simple Scenario: Achieving Long-term QoS
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0 0.2 0.4 0.6 0.8 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Distance [km]
Dis
tan
ce [k
m]
Base StationsMobile User 1Mobile User 2Static Users
Vacant cell
Congested cell
Without LLS With LLS0
10
20
30
40
Per
cent
age
of F
roze
n V
ideo
User 1User 2
Fairness in Video Quality
(Freezing)
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Look-back Scheduling adds long-term QoS indictors into the scheduling decision. This means that user QoS is monitored either by the user,
or the network, and reported during handover. LLS scheduler should also be aware of users immediate
resource needs.
LLS design factors: Which utility functions to use for short and long-term
QoS indicators? How do you combine then for an overall user utility?
Look-back Scheduling (LLS)
8
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Look-back Scheduling: Proportional Fairness (LL-PF)
9
Compute Long-term
User Satisfaction
Combine Long and
Short-term IndicatorsQoS metrics
from users on perceived quality
Long-term indicators
Final User Scheduling Priority
Channel Quality
User Rate
Long-term user throughput over multiple BS
Short-term indicators
Long-term Look-back PF Scheduler
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
LL-PF: Effect of a
Slot Rate Metric: 10th percentile throughput Computed over T slots Indicates slot
starvation level Will be zero if user is
starved for more than 10% of the time slots
A high value indicates that user is served well in the worst 10% of the time slots
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Look-back Scheduling: Exponential (LL-EXP)
11
Compute Long-term
User Satisfaction
Combine Long and
Short-term IndicatorsQoS metrics
from users on perceived quality
Long-term indicators
Final User Scheduling Priority
Channel Quality
Queue Lengths
Long-term user throughput over multiple BS
Short-term indicators
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i i
N
i ii
LTi
i
x
tqN
tqN
tq
tRtr
i
1
1*
)(1
1
)(1
)(exp)(
)(maxarg
Long-term Look-back EXP Scheduler
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Performance Evaluation
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
System Model
19 Cell Network, 1km inter-BS distance Mobility: Random Waypoint Channel:
Path-loss: 128.1 + 37.6 log(d) Slow fading: 8 dB log-normal Fast fading: i.i.d. Rayleigh
Traffic: Full buffer, Constant bit-rate for video traffic
Metrics: Network throughput Jain’s Fairness Index 10th percentile slot throughput: Average freezing
Average ratio of playback time that is frozen for all users in the network
-3 -2 -1 0 1 2 3-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
X (Km)
Y (
Km
)
Time (sec) = 0 Time (sec) = 0
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Fairness Results: LL-PF Scheduling
LL-PF provides long-term fairness over multiple cells, while simultaneously providing short-term rates depending on the tuning factor a
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Throughput Results: LL-PF Scheduling
LL-PF network throughput is also higher than PF for values of a that provide a similar short-term slot rate Therefore there are gains in both throughput and fairness
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Results: LL-EXP Scheduling
LL-EXP achieves throughput and video freezing gains The long-term average rate computation allows the
scheduler to exploit user channel opportunistically Gains increase with load
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Summary In this paper we introduce the notion of Long-term Look-back
Scheduling (LLS) over multiple cells. To achieve this we propose that QoS indicators are monitored
during a user session, and incorporated along with traditional short-term indicators to make the overall scheduling decision
This introduces some signalling during hand-over, where the BS or the user, should transmit the QoS indictors to the target BS.
We developed two LLS and assessed their performance: Proportional fair scheduling with long and short-term user
rates Exponential scheduling with long and short term QoS
indicators Long-term user QoS gains were observed in both cases.
Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells
Thank You
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