bandwidth reallocation for bandwidth asymmetry wireless networks based on distributed multiservice...

Bandwidth Reallocation for BandwidthAsymmetry Wireless Networks Based on

Distributed Multiservice Admission Control

Robert SchafrikLakshman Krishnamurthy

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

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

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

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

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

QoS Metric

• Call Admission Control (CAC)• Critical CAC Parameters

– Pn – New call blocking probability– Ph – Handoff call blocking probability

• MINBlock used to optimize

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

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

• Jeon’s CAC for MSWN [7]• DMS-AC scheme

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 classes[20]

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

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

Distributed Multiservice Admission ControlSystem Model (contined)

• Design goal of the proposed admission control scheme is:

φi < ηi

Φi < ρi

• ηi (eta) - Highest tolerable dropping probability of class i hand-off calls.

• φi (phi) – hand-off call dropping probability of class i calls• Φi (phi) – New call blocking probability of class i calls.• ρi (rho) – Highest tolerable new call blocking probability

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).

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 + Br

d (Blu + Bl

d)

• 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.

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) Overloadstates of class 2 calls

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:

1) The admission of a new class i call in Cr cannot cause the call dropping probability of class j call in Cr denoted by φr

j to exceed ηj

2) 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 φl

j to exceed ηj

• The key of DMS-AC is to determine the thresholds of individual call class in each cell (i.e. we need to compute φ r

j

and φlj)

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 φr

j

and φlj)

• 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


• 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


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

• Blocking probability of class j calls in Cl is expressed as:

Derivation of Admission threshold

• Thi1 and Thi

2 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

Extension to multicell system

• C0 be the current observing cell

• C1 to C6 be the neighboring cell

Extension to multicell system

• During a control period, the admission of a class i (I Є [0, M-1]) call in C0 should satisfy:1. The admission of a new class i call in C0

cannot cause the call dropping probability of call class j in C0, φ0

j to exceed ηj

2. 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 ηj

Valid States

n M

q-Number of calls for class q in the system

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

Call classes

Number of feasible states Constrained by Bu and Bd

Threshold-Based Admission Control Scheme

Test for conditions 1,2, and 5

If you are the current call class (note: not always zero!)

You are NOT the current cell

Conditions

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

Admission Case 1 – Ratio of Uplink and Downlink Needs to Change

Need to choose an allocation between

Admission Case 2 – Cell r Will Not be able to Accept Handoff from

Cell l• Cell r either doesn’t have enough room or

accepting a handoff will cause a class to overload

• See if Cell r can reallocate to accommodate

DMS-AC Pseudocode

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 )

Jeon’s 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

Comparison with Jeon (1)

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


• Call types vary independently


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

Comparison with Static Sol’n (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


• 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


• Traffic increases for Cr, decreases for Cl

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

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

Backup Slides

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

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