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Presented by Okan Yilmaz CS 6204 Mobile Computing Virginia Tech Fall 2005

Performance Analysis of a Preemptive and Priority Reservation Handoff Scheme for Integrated Service-Based Wireless Mobile Networks by Jingao Wang, Quing-An Zeng, and Dharma P. Agrawal. Presented by Okan Yilmaz CS 6204 Mobile Computing Virginia Tech Fall 2005. Abstract.

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Presented by Okan Yilmaz CS 6204 Mobile Computing Virginia Tech Fall 2005

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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 Yilmaz CS 6204 Mobile Computing Virginia Tech Fall 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. OR RC(SR) HR RC(SR)  HC(Sc-Sc)  RT(SE)  RHRQ(MR) HN NC(SN)  HC(Sc-Sc)  NHRQ(MN) ON NC(SN) System model for a reference cell

  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 • : 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

  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

  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

  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 • : total arrival rate of calls

  23. M/M/3/3 • 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 ANALYSIS i j k m l

  25. Stable State diagram for (i=1, j=1, k=1, l=2, m=0) S = SR + SC+ SN =12 SR = 6; SC=SN=3; SE=1 MR=5; MN=50; NT=3162

  26. Total number of states • Four cases to consider: • 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 states • 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) • 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 • 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) : MRpossibilities • k = 1  j=(Sc .. Sc + MR - 1) : MRpossibilities • … • k = Sc-SE j=(SE +1.. SE + MR) : MRpossibilities • Total = [(Sc-SE +1) * MR]/2 states • N4 = [(Sc-SE+1) * MR * MN]/2 states

  28. Normalizing Condition • Both RHRQ and NHRQ are empty • RHRQ is not empty while NHRQ is empty • RHRQ is empty while NHRQ is not empty • 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: mnon-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[NCSN] • 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.

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