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1
Performance Analysis of a Preemptive and Priority Reservation Handoff Scheme for Integrated Service-
Based Wireless Mobile Networksby Jingao Wang, Quing-An Zeng, and Dharma P. Agrawal
Presented by Okan YilmazCS 6204 Mobile Computing
Virginia TechFall 2005
2
Abstract Analytical Model & Performance Analysis Call Types:
Originating calls Handoff requests
Service Types: Real-time Non-real-time
Partitioning based system model Real-time service calls only Non-real-time service calls only Handoff requests only
Preemptive priority handoff scheme
3
Abstract (cont) Multidimensional Markov Model to estimate
Blocking probability of originating calls Forced termination probability of handoff calls Average transmission delays
Simulation and Performance Analysis Different call holding times Several cell dwell time distributions
Results Significantly reduces the forced termination
probability of real-time calls Negligible packet loss of non-real-time calls
4
Introduction 2G Networks
Limited and far from acceptable Voice Short message Low speed data
3G Networks Demand for Integrated services
Business customers Any time, any place Employees, key customers e.g., brokerage, banking, emergency services, traffic
reporting, navigation, gambling, etc. Wireless and VLSI Technology
Multi-media-ready cell phones, pocket PCs, Palms
5
Challenges of Integrated Services
True combination of real-time and non-real-time services
Maximize the utilization of network infrastructure
Quality of service (QoS) Handoff handling
Forced termination of an outgoing call is more annoying than blocking of a new call
6
Handoffs Handoff: changing parameters of a channel
Frequency, time slot, spreading code, or combination of them
When: crossing cell boundary or deteriorating signal quality
Cell structure Support a drastic increase of demand
Microcell, picocell, hybrid cell Smaller cells More handoffs
7
Handoff Design Issues Forced termination versus new call blocking Increased channel utilization in a fair manner Goal:
Minimization of forced termination of real-time service Without drastically sacrificing the other QoS parameters
Several studies based on voice based cellular networks
Need for support of multiple service types simultaneously
Keys for a good scheme: Service dependent
Delay sensitivity: non-real-time versus real-time Preemptive model: priority reservation handoff
8
SYSTEM MODEL Homogenous cell with fixed number of S channels Reference cell approach Call types:
Real-time originating call: MU dials a number to place a real-time call
Real-time handoff request: MU holding a channel enters the handoff area
Non-real-time originating call: MU places a non-real-time call
Non-real-time handoff request: Non-real-time MU holding a channel approaches and crosses a cell boundary Cell boundary: The points where the received signal
strength between two adjacent cells is equal
9
Notation OR: arrival rate of real-time originating calls HR: arrival rate of real-time handoff requests ON: arrival rate of non-real-time originating calls HN: arrival rate of non-real-time handoff requests RC: real-time service channels group with capacity SR
CC: common handoff channels group with capacity SC
NC: non-real-time service channels group with capacity SN
RT only: In CC, real-time service channels reserved exclusively for real-time handoff calls with capacity SE
CH: In CC, channels that can be used by both real-time and non-real-time handoff calls with capacity SC - SE
RHRQ: real-time service handoff request queue with capacity MR
NHRQ: non-real-time service handoff request queue with capacity MN
10
System model for a reference cell
OR RC(SR) HR RC(SR) HC(Sc-Sc) RT(SE) RHRQ(MR) HN NC(SN) HC(Sc-Sc) NHRQ(MN) ON NC(SN)
11
Algorithm for Originating Calls
12
Algorithm for Handoff Requests
13
System Design (cont) Preemptive procedure: real-time handoff request calls
preempt non-real-time handoff request calls if a non-real-time in CC and NHRQ is not full
Real-time handoff requests may preempt non-real-time handoff requests irrespective of NHRQ being full or not No need if very large NHRQ buffer
Real-time handoff request are dropped If RHRQ is full (both RHRQ and NHRQ are full in
preemptive scheme) If the handoff request in RHRQ cannot get service
until it moves out of the handoff area
14
System Design (cont) Non-real-time handoff requests will never be dropped
If NHRQ is large enough (not necessarily be infinite) Because the non-real-time handoff request is
transferred from the reference cell to another cell Waiting time in NHRQ = dwell time of non-real-time
service subscribers Real-time handoff request calls can continue until
signal strength becomes not enough to get service This is ignored in paper. It is assumed that the call is
blocked.
15
Traffic Model Three characteristics:
Call arrival process Call holding time Cell dwell time
Call arrival: Poisson process Call holding time and cell dwell time
Two approaches: Traffic model: general independent identically distributed (i.i.d.)
Exponential, gamma, lognormal, hyper-exponential, hyper-Erlang Analytical model: User’s mobility, the shape and size of the cell,
and exponential distribution are used to determine cell dwell and call holding time
Paper uses the second for analytical modeling, both for numerical and simulation results
16
Dwell Time Two-dimensional fluid model
fV(v): pdf of the speed V of MU E[V]: mean of the speed of MU
MU moves randomly any direction in [0,2) Assumes uniform density of users
17
Cell Dwell Time
LVEA
TE
A
LVE
A
N
VEL
vvvfL
vvfLv
N
vvfLv
N
dwell
Tdwell
VE
V
VT
VO
0
0
: density of MUs in the cell NO: number of cell outgoing MUs
with moving speed v and v+v NT: total number of cell outgoing
MUs per unit time A: area of the cell L: length of the perimeter dwell: average outgoing rate of an
MU within a cell Tdwell: cell dwell time with a
random exponential distribution with mean 1/dwell
Biased sampling theory in boundaries [1]
18
Handoff Area Dwell Time fV*(v): pdf of the speed of
real-time service subscribers crossing cell boundary V*
D: the length of moving path of mobile users in the handoff area
Th: dwell time of real-time service subscribers in the handoff area
E[Th]: Average handoff area dwell time
Path length and velocity of MUs are independent
VEDE
TE
VEvvf
VE
vVE
vf
vvfvV
E
VDT
VE
vvfvf
hdwellh
V
V
V
h
VV
1
11
11
1
0
0
0*
*
*
*
*
*
19
Channel Holding Time Exponential distribution
TCR: Call holding time of real-time calls
TCN: Call holding time of non-real-time calls
CR: Service rate of real-time calls
CN: Service rate of non-real-time calls
TR: Channel holding time of real-time service calls
TN: Channel holding time of non-real-time service calls
dwellCNNN
dwellCRRR
dwellCNN
dwellCRR
dwelldwell
CNCN
CRCR
TE
TE
T
TT
11
11
1
11
20
Arrival Process of Service Calls Poisson process OR: arrival rate of real-time originating calls HR: arrival rate of real-time handoff requests ON: arrival rate of non-real-time originating calls HN: arrival rate of non-real-time handoff requests Need to compute HR and HN from OR and ON,
respectively Homogenous mobility pattern
Mean number of incoming handoffs to reference cell = mean number of outgoing calls from the reference cell
21
Arrival Process of Service Calls (cont)
E[CR]: average number of real-time calls holding channels in the reference cell
OUTR: departure rate of real-time handoff calls from the reference cell
10dwellROUTRHR CE
22
Arrival Process of Service Calls (cont) E[NN]: average number of both non-real-time
service requests and calls in the reference cell E[CN]: average number of non-real-time MUs holding
channels in the reference cell E[LN ]: average length of NHRQ
)14(
)13(
)12,11(
21
21
NNN
dwellNHNHNHN
dwellNHNdwellNHN
LECENE
NE
LECE
: total arrival rate of calls
)15(HNHRONOR
23
M/M/3/3
0 1 2 3
2 3
blocked/lost
M/M/3/3 [2]: M: Exponential or Poisson arrivals M: Exponential or Poisson service 3: Number of servers 3: Maximum number of customers in the system
P0 + P1 + P2 + P3=1 (+) P1 = P0+ 2 P2
Pblocking = P3
Throughput = (1-P3) *
24
PERFORMANCE ANALYSISi
j
k
l
m
25
Stable State diagram for (i=1, j=1, k=1, l=2, m=0)
S = SR + SC+ SN =12SR = 6; SC=SN=3; SE=1MR=5; MN=50; NT=3162
26
Total number of states Four cases to consider:
1. Both RHRQ and NHRQ are empty: 0≤ i ≤SR;0 ≤ j ≤ Sc - k; 0≤ k ≤ Sc - SE ; 0≤ l ≤ SN ; m = 0
k=0 j=(0 .. Sc) : Sc +1 possibilities k=1 j=(0 .. Sc -1) : Sc possibilities … k= Sc-SE j=(0 .. SE) : SE +1 possibilities Total = [(Sc-SE +1) * (Sc + SE +2)]/2 states
N1=[(SR+1)*(Sc-SE +1)*(Sc + SE +2)*(SN+1)]/2 states2. RHRQ is not empty while NHRQ is empty:
i = SR; Sc < j + k i =SR; Sc-k+1≤ j ≤ Sc + MR + k; 0≤ k ≤ Sc-SE ; 0≤l ≤SN ; m=0
k=0 j=(Sc + 1 .. Sc + MR) : MR possibilities k=1 j=(Sc .. Sc + MR + 1) : MR possibilities … k= Sc-SE j=(SE + 1.. Sc + MR) : MR possibilities Total = [(Sc - SE +1) * MR] states
N2=[(Sc - SE +1) * MR * (SN + 1)]/2 states
27
Total number of states (cont)3. RHRQ is empty NHRQ is not empty:
Sc-SE ≤ j + k; l = SN; 0≤i ≤SR; Sc-SE-k ≤ j ≤Sc-k; 0≤k ≤Sc-SE ; l=SN; 1≤m ≤MN
k = 0 j=(Sc - SE .. Sc) : (SE +1) possibilities k = 1 j=(Sc – SE - 1 .. Sc - 1) : (SE +1) possibilities … k = Sc - SE j=(0 .. SE) : (SE +1) possibilities Total = (Sc - SE +1) * (SE +1) states
N3 = (SR + 1) * (Sc - SE + 1) * (SE + 1) * MN
4. Both RHRQ and NHRQ are not empty i = SR; Sc < j + k; l = SN; i = SR; Sc-k+1 ≤ j ≤Sc+ MR - k; 0≤k ≤Sc-SE ; l=SN; 1≤m ≤MN
k = 0 j=(Sc+1 .. Sc + MR) : MR possibilities k = 1 j=(Sc .. Sc + MR - 1) : MR possibilities … k = Sc-SE j=(SE +1.. SE + MR) : MR possibilities Total = [(Sc-SE +1) * MR]/2 states
N4 = [(Sc-SE+1) * MR * MN]/2 states
28
Normalizing Condition
1. Both RHRQ and NHRQ are empty
2. RHRQ is not empty while NHRQ is empty
3. RHRQ is empty while NHRQ is not empty
4. Both RHRQ and NHRQ are not empty
29
Average number of calls E[CR]: average number of
real-time calls holding channels in the reference cell
1&3: i + j: real-time calls 2&4: RC is full; SC-k real-time
calls
E[NN]: average number of both non-real-time service requests and calls in the reference cell
1&2: k + l: non-real-time calls 3&4: RN is full; SN+k real-time
calls; m calls in NHRQ
30
Pseudo-code to solve (NT+2) independent nonlinear equations
31
Blocking Probabilities Originating real-time
calls are blocked when i= SR
Forced termination of real-time service handoff requests BHR: Blocking
probability MR is full
DR: dropping probability MR is not empty
32
Channel and RHRQ buffer utilizations
Utilization=mean channel used/ S
E[CN]: average number of calls holding channels 1&2: k+l: non-real-time
calls 3&4: NC is full; SN+k real-
time calls; m calls in NHRQ RHRQ utilization = mean
number of channels in RHRQ/MR
E[LR]: average length of RHRQ 1&2: j+k-SC real-time
handoff requests waiting in RHRQ
33
NHRQ Buffer Utilization and Forced Termination probability
NHRQ utilization = mean number of channels in LHRQ/MN
E[LN]: average length of NHRQ 1&2: m non-real-time handoff
requests waiting in NHRQ Ph: Probability that a real-
time service call triggers a handoff request in the reference cell Real-time service call holding
time > the cell dwell time Phf: Forced termination
probability of real-time handoff calls (l-1) successful handoff followed
by a forced termination
34
Transmission Delay of non-real-time service
Td : The lifetime transmission delay of non-real-time service Sum of Tws
Tw : transmission delay on non-real-time service in each cell
Little’s Law Mean waiting time = mean
number of customers in queue / throughput
BON : blocking probability of originating non-real-time calls 1 - P[NCSN]
E[TS]: Average serving time of non-real-time calls (mean number of calls getting
service + in queue) / (total throughput)
BHN: blocking probability of non-real-time service handoff requests NHRQ is full: m = MN
35
Average transmission delay of non-real-time service (cont)
Nh: average number of handoff per a non-real-time handoff request (delay due to Nh
handoffs + call holding time) by average serving time
E[TN]: average transmission delay of non-real-time service Handoff arrival
probability times average delay each handoff request ecounters
36
Numerical and Simulation Results Integrated service homogenous cellular system Call arrivals
Poisson Call holding and cell dwell times
Scenario 1: exponentially distributed as in performance analysis
Scenario 2: iid with Gamma distribution Cell and handoff area dwell times with = 1.5 Call holding time with = 2
Same mean value Cell shape: hexagonal Each neighbor has equal probability to receive handoff
37
Simulation Results: Comparison of QoS Parameters
BOR, BON: blocking probability of real-time & non-real-time service
Phf: Forced termination probability of real-time service calls
TN: Transmission delay of non-real-time service calls
Scen#1 and analytical analysis results are consistent < 4% difference in BOR, BON,
and Phf Accuracy of analysis is
substantiated Scen#1 and Scen#2 results
are comparable Phf: Scen#2 is 20 less BOR, BON: Scen#2 is 6% and
2% larger, respectively TN: Scen#2 is 28% less
Reasonable: Gamma has smaller standard deviation
Parallel trend: Analytical formula with
tolerable error margins
38
Simulation Results: Performance Comparison of real-time calls
Fhr & Phr: Priority and preemptive have 14.7% and 30.9% improvements
over guard channel, respectively BOR: almost the same Priority especially with preemptive procedure is effective in
decreasing forced terminations
Schemes: Standard guard channel
(base) Priority reservation Preemptive priority handoff
Higher QoS parameters when higher arrival rates (lower service quality)
39
Simulation Results: Performance comparison of non-real-time calls
TN increases with higher traffic
Guard channel performs better Channels available for non-
real-time decreases due to lower priority
Largest TN is 3.91sec.; 6.5% of whole service time
31% decrease in forced termination probability is more important
7% increase in blocking probability of originating non-real-time calls
Forced termination probability of non-real-time is negligibly small
Proposed scheme is better in terms of the performance
40
Conclusions A handoff scheme is proposed
Priority reservation Preemptive priority policy
Analytical model for performance analysis has been proposed
Simulation results match the analytical model Several QoS parameters have been evaluated Forced termination probability of handoff requests of
real-time calls can be decreased Non-real-time service handoff requests do not fail
A reasonable 6.5% transmission delay increase
41
References [1] Priority handoff analysis, Vehicular Technology
Conference, 1993 IEEE 43rd, Xie, H.; Kuek, S., Page(s): 855-858, Digital Object Identifier 10.1109/VETEC.1993.510945
[2] CS5214 Course notes, Ing-Ray Chen, 2004.