Bandwidth Reallocation for Bandwidth Asymmetry Wireless Networks Based on Distributed Multiservice A

1
Bandwidth Reallocation for BandwidthAsymmetry
Wireless Networks Based onDistributed
Multiservice Admission Control

• Robert Schafrik
• Lakshman Krishnamurthy

2
Agenda

• Introduction
• Related work on Admission control and bandwidth
  allocation
• Distributed Multiservice Admission Control
• System model DMS-AC in Two-cell system
• DMS-AC in Multi-cell system
• Performance evaluation
• Competing Systems
• Static Allocations
• Conclusion
• Comments

3
Introduction

• Next generation multiservice wireless networks
  are expected to present distinctive traffic
  asymmetry between uplink and downlink.
• Some resources may be wasted if bandwidth is
  allocated symmetrically
• To match the asymmetric traffic load, it is
  necessary to allocate different bandwidth to
  uplink and downlink.
• Different call classes have different up/down
  ratios
• QoS may be different for Handoff and new call,
  and for each call class

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Introduction (continued)

• If the traffic and mobility patterns are
  predictable, then fixed bandwidth allocation
  works.
• Bursty and variable bandwidth requirements call
  for new treatments of network resource management
• Traffic generated is time dependent
• It is necessary to develop a dynamic bandwidth
  allocation scheme that can adapt to the changing
  traffic conditions

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Problem Statement

• Upload and Download communications are not always
  symmetric
• Need to determine under what conditions bandwidth
  needs to be reallocated
• Need to determine the best way to reallocation
  when multiple call classes and multiple cells
  while preserving QoS

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Time Slots

• Some timeslots are for uplink, some are for
  downlink. This prevents collisions
• Variable time-slots for different cells always
  outperforms fixed time slots
• Reallocation of time slots affects all calls in
  the system, try to limit how frequently this is
  done

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QoS Metric

• Call Admission Control (CAC)
• Critical CAC Parameters
• Pn New call blocking probability
• Ph Handoff call blocking probability
• MINBlock used to optimize

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Distributed Multiservice Admission Control
(DMS-AC)

• Provides a base to compare new techniques against
• Tries to find proper threshold
• Limits new calls of certain classes
• If blocking probability exceeds a bound, it
  reallocates
• If QoS thresholds for some classes cannot be
  found, it reallocates

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Related Work

• CAC schemes
• CDMA (fixed, symmetric)
• CDMA/TDD (fixed, asymmetric)
• SA same-slot allocation (all cells have same
  allocation)
• DA different slot allocation (cells can have
  different allocations, but adjacent cells may
  have slot interference)
• Limited Fractional Guard Channel scheme
• DCA Distributed Admission Control
• Jeons CAC for MSWN 7
• DMS-AC scheme

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Limited Fractional Guard Channel (LFGC)

• Minimize a linear objective function
• Weighted sum of handoff and new call blocking
  probabilities
• C channels
• C-T reserved for new and handoff
• When T channels are used, only handoff calls are
  accepted
• Extended to deal with multiple call classes20

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Distributed Admission Control (DCA)

• Based on communication between cells to predict
  handoffs
• Only deals with one call class
• Knapsack problem 18 to deal with multiple call
  classes

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Distributed Multiservice Admission ControlSystem
Model

• Total bandwidth allocated of a cell is fixed.
• Bandwidth allocated on uplink and downlink is
  different and also adjustable 3 8
• M classes of calls in the system
• The calls of particular class have the same
  bandwidth requirements, mobility characteristics
  and mean resource holding time

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Distributed Multiservice Admission ControlSystem
Model (contined)

• Design goal of the proposed admission control
  scheme is
• fi lt ?i
• Fi lt ?i
• ?i (eta) - Highest tolerable dropping
  probability of class i hand-off calls.
• fi (phi) hand-off call dropping probability of
  class i calls
• Fi (phi) New call blocking probability of class
  i calls.
• ?i (rho) Highest tolerable new call blocking
  probability

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Distributed Multiservice Admission ControlSystem
Model (contined)

• DMS-AC operates in distributed manner
• System states exchanged periodically between
  adjacent cells
• Base station of cell makes an admission decision
  based on the state information of the cell itself
  and its neighboring cells.
• DMS-AC uses the admission threshold of each call
  class based on the system states to limit the
  admission of new calls.
• Dynamic threshold scheme is used.
• Threshold of specific call class is recomputed
  and reset periodically.
• Control period interval between two threshold
  computing process (15 60 minutes).

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Distributed Multiservice Admission control in a
Two-Cell System

• Fig. 1. Two-cell system.
• Cr is the observing cell and Cl is the
  neighbouring cell
• Total bandwidth in Cr (Cl) is denoted by Bru
  Brd (Blu Bld)
• In DMS-AC we need to define the overload states
  of a specific call class in the multiservice
  system.
• In multiservice networks, the set of overload
  states of different call classes may be different.

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Distributed Multiservice Admission control in a
Two-Cell System (contined)

• Example
• Cell has 10 downlink and 5 uplink channels
• Class 1 calls require 1 uplink and 1 downlink
  channel
• Class 2 calls require 1 uplink and 3 downlink
  channels
• (n1, n2) denote the system states, where n1 and
  n2 denote the class 1 calls and class 2 calls in
  the system
• (0,3) and (2,2) are overload states of class 2
  calls. No class 2 calls are not admissible while
  class 1 calls are admissible.

Fig. 2. An example. (a) Overload states of class
1 calls. (b) Overload states of class 2 calls
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Distributed Multiservice Admission control in a
Two-Cell System (contined)

• During a control period, the admission of class i
  new call in the observing cell Cr should satisfy
  the following two conditions
• The admission of a new class i call in Cr cannot
  cause the call dropping probability of class j
  call in Cr denoted by frj to exceed ?j
• The admission of a new class I call in Cr cannot
  cause the call dropping probability of call class
  j in the neighboring cell Cl, denoted by flj to
  exceed ?j
• The key of DMS-AC is to determine the thresholds
  of individual call class in each cell (i.e. we
  need to compute frj and flj)

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Distributed Multiservice Admission control in a
Two-Cell System (continued)

• The key of DMS-AC is to determine the thresholds
  of individual call class in each cell (i.e. we
  need to compute frj and flj)
• The probability that xi class i calls out of ri
  calls stay in Cr has a binomial distribution
  given by
• Similarly, the probability that yi class i calls
  handoff to Cr from Cl during the control period
  is

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Distributed Multiservice Admission control in a
Two-Cell System (continued)

• Using formulas 1 2, we need can find Pr(ni)
• Pr(ni) denote the probability that there are ni
  class i calls in Cr during T units of time
• At any time system stays in feasible state,
  should satisfy

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Distributed Multiservice Admission control in a
Two-Cell System (continued)
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Distributed Multiservice Admission control in a
Two-Cell System (continued)

• Blocking probability of class j calls in Cr can
  be expressed as
• Blocking probability of class j calls in Cl is
  expressed as

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Derivation of Admission threshold

• Thi1 and Thi2 denote the thresholds of class i
  calls that satisfies the first and second
  admission conditions
• The final admission threshold of class i calls in
  Cr, which satisfies all admission conditions , is
  given by

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Extension to multicell system

• C0 be the current observing cell
• C1 to C6 be the neighboring cell

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Extension to multicell system

• During a control period, the admission of a class
  i (I ? 0, M-1) call in C0 should satisfy
• The admission of a new class i call in C0 cannot
  cause the call dropping probability of call class
  j in C0, f0j to exceed ?j
• The admission of a new class i call in C0 cannot
  the call dropping probability of call class j in
  the neighboring cells to exceed ?j

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Valid States
q
n

• Number of calls for class q
• in the system

M
Number of feasible states Constrained by Bu and
Bd
Call classes
Not all of these states are good for the system,
but they are possible. Matrix will not be
symmetric.
S(i,j) is the subset of states such that adding a
call of type i will cause overload for class j
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Threshold-Based Admission Control Scheme
If you are the current call class (note not
always zero!)
Test for conditions 1,2, and 5
You are NOT the current cell
Conditions
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Case 1 Cell i will Become Full for Some Call
Class

• si is in the set S(i,j) adding a call type i
  will cause at least one other class j to become
  full
• Need to reallocate up/down channels

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Admission Case 1 Ratio of Uplink and Downlink
Needs to Change
Need to choose an allocation between
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Admission Case 2 Cell r Will Not be able to
Accept Handoff from Cell l

• Cell r either doesnt have enough room or
  accepting a handoff will cause a class to
  overload
• See if Cell r can reallocate to accommodate

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DMS-AC Pseudocode
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Comparisons

• Analysis using a 2-cell system
• 15 minute control period
• 100 channels
• 2 call classes
• Real time ( 1 up, 1 down )
• Non Real Time ( 1 up, 3 down )

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Jeons scheme

• Similar goal create a scheme for reallocating
  in asymmetric environments
• Accounts for traffic load in both directions
• Uses Markov analysis
• Also only considers QoS for New and Handoff calls

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Comparison with Jeon (1)

• New call QoS is similar, and not shown
• Jeon does not consider NRT QoS

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Comparison with Jeon (2)

• Call types vary independently

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Comparison with Jeon (3)

• Similar performance with small loads
• Jeons begins to lag with NRT calls
• Jeons breaks down when volume is high

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Comparison with Static Soln (1)

• No reallocation is performed for AC without BA
• RT call arrival rates in both Cr and Cl increase
  from 0.07 to 0.12 simultaneously
• Up/down ratio is 30 up/ 70 down

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Comparison with Static Soln (2)

• average NRT call arrival rates in both Cr and Cl
  change from 0.006 to 0.011 simultaneously
• Up/down ratio is initially 50 up/ 50 down

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Comparison with Static Soln (3)

• Traffic increases for Cr, decreases for Cl

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Conclusions

• Changing the up/down ratio for several asymmetric
  call classes helps maximize the resources of a
  Cell, and still guarantees QoS for new and
  handoff calls
• When to reallocate
• Allocations for a call class nears max
• Allocations of neighbor for that class nears max
• How to reallocate
• Find min B that fills QoS requirement

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Comments

• Experimental setup was simplistic
• Perhaps more than 2 call types could be
  considered in a simulation
• Perhaps compare the performance of more than 2
  cells
• A call cannot itself be dynamic (aka use
  1up/1down for a while then switch to 1up/2down)
• Does not consider revenue, but that might be
  achievable by adjusting admittance thresholds
• Performs slightly better than Jeon in some
  conditions

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Backup Slides
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Other Notes

• Assume C0 covers a conference, and becomes
  overloaded
• C1 - C6 will be unable to accept any calls of any
  class (due to the handoff constraint)

C0
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Overview

• Uplink and Downlink bandwidth is asymmetric
• Determine when to change ratio of uplink to
  downlink
• Determine how to compute best ratio to satisfy
  QoS
• Satisfy QoS for call classes