Wireless MAC Protocol Classification /Performance Wireless MAC 프로토콜성능분석

Transcription

1 무선통신망 MAC 프로토콜성능분석 Wireless Information and Network Engineering Research Lab. School of Electrical amd Computer Engineering Ajou University, Korea jkim@ajou.ac.kr Homepage:

2 Agenda Wireless MAC Protocol Classification /Performance Wireless MAC 프로토콜성능분석 Slotted Aloha 성능분석 Infinite number users model : M/G/ Busy Period 분석기법 Finite number users model : Markov Chain 분석기법 IEEE 802. MAC 프로토콜성능분석 CSMA/CA 분석 M/G/ Busy period 분석기법 Capture effect를고려한 CSMA/CA 분석기법 TFA (Transient Fluid Approximation) 기법 Binary exponential backoff 분석기법 MAC 프로토콜성능분석기법적용사례 RFID 성능분석 RFID Anti-collision algorithm IEEE MAC 프로토콜성능분석 Initial backoff window 분석 Summary and Discussion 2

3 Wireless MAC Protocol Classification Wireless MAC Protocols Contention-Based Hybrid Contention-Free Dynamic Resolution Static Resolution Dynamic Allocation Static Allocation Token Passing MSAP Time of arrival Probabilistic ID Probabilistic Reservation high Exponential Binary Tree Aloha PRMA MSAP priority to oldest one Backoff IEEE 802.3//6 RFID CSMA IEEE 802.e IEEE IEEE DOCSIS IEEE RFID : Radio Frequency ID, CSMA : Carrier Sense Multiple Access, PRMA : Packet Reservation Multiple Access BRAM TDMA FDMA CDMA OFDMA DOCSIS : Data Over Cable Service Interface Specification, MSAP : Mini Slotted Alternating Priority, BRAM : Broadcast Recognition Access Method 3

4 Wireless MAC Protocol Classification IEEE MAC Frame Structure (IEEE Std ) Super frame #m- Super frame #m Super frame #m+ Beacon #m CFP (Contention Free Period) CAP #m Asynchronous Isochronous Asynchronous Isochronous Beacon #m Contention Access Period MCTA MCTA2 CFP (Contention Free Period) CTA CTA 2 CTM n- CTA n CSMA/CA Data/Control,000 ~ 65,535μs S-ALOHA Data/Control TDMA Data - MCTA : Management Channel Time Allocation 4

5 Wireless MAC Protocol Performance Performance Metrics Throughput MAC Level Throughput (Goodput): MAC Layer Data Rate (bits/sec) Channel Throughput : The fraction of time that useful information is carried on the channel Packet Delay (Access Delay) The time from the moment a message is generated until it makes it successfully across the channel Packet Drop Probability The probability is that a packet is dropped 5

6 Wireless MAC Protocol Performance Performance Analysis Method Rigorous Probability Based Binary Tree Based Algorithm : Switching system, RFID Anti-collision etc. [6, 7] Markov Chain Model Slotted Aloha (finite user model) [], Binary Exponential Backoff algorithm [4] (CSMA/CA) Characteristics Exact analysis method High Computational Complexity M/G/ Busy Period Analysis Slotted Aloha (Infinite user model) [], CSMA/CA [2,3] Characteristics Difficult to model the system and to find the probability distribution TFA (Transient Fluid Approximation) Slotted Aloha, CSMA/CA Characteristics Low Computational Complexity, Easy to model the system Need the verification using the simulation 6

7 Slotted Aloha 성능분석 - Infinite User Model : M/G/ Busy Period Analysis - Finite User Model : Markov Chain Analysis 7

8 Slotted Aloha (M/G/ Busy Period Analysis) System model Infinite population Packets transmission time : T Packet arrival (Poisson distribution) : λ packet/sec Offered load (new arrival + backlogged arrival) : g Total average number of transmission per slot : G =gt I : Idle period, B: Busy period, U : Useful period Throughput (S) : E[ U ] U S = = EC [ ] B + I Cycle Busy Period Cycle Idle Period Slot : colliding packets : successful slots 8

9 Idle Period A random variable describing the number of slots in the idle period : I I The probability of some packets P [ I = ] = P [ Some packets scheduled in first slot ] gt = - P[ No packets scheduled in first slot] = e gt gt PI [ = 2] = e ( e ) P k () t In general, the length of the idle period is seen to be geometrically distributed gt k gt ( ) ( ) PI [ = k] = e e k=,2, iii Average length of idle period I = e gt = ( gt ) k e k! ( gt ) 9

10 Busy Period The number of slots in the busy period : B Packets must be scheduled for transmission in each and every one of the first k- slots and none scheduled in the kth gt k gt ( ) ( ) PB [ = k ] = e e k=,2, iii Expected value of B B e gt = e 0

11 Useful Period and Throughput The probability that a given slot in the busy period is successful gt gte gt e gt k gt ( B k) [ B gte gte PU= k B] =,0 k n gt gt k e e EU [ B ] = B gte i e gt gt U = E[ U ] = E[ E[ U B ]] = B i gte e gt gt Throughput (S) EU [ ] U gt G S gte Ge = = = = E[ C ] B + I

12 Slotted Aloha (Markov Chain Analysis) System model Finite number of users Number of users : M (each with a single buffer) Packets transmission time : T (slot duration) Thinking state (No ready packet) Packet generation probability : σ Backlogged state t (Transmission i was unsuccessful) Packet retransmission probability : v Let Nk ( ) denote the number of backlogged users at the beginning g of the kth slot Throughput (S) : expected fraction of slots containing useful transmission S = P suc 2

13 Steady-State State Probability Steady-State Probability Let π i be the steady-state state probability of the system being in state i π i = limk Pr[ Nk ( ) = i] Let pij be the steady-state state transition probability p = lim Pr[ Nk ( ) = j Nk ( ) = i] Π =ΠP ij k State Transition Rate Diagram of Finite Population Aloha 0 2 i M The number of backlogged users From 0 i- To i- i To M i+2 i+ From i+ 3

14 State Transition Probability j i Pr[i backlogged users transmit in a slot / j in backlog]= v ( v) i Pr[i thinking users transmit in a slot M j / j in backlog]= σ ( σ ) i j i i M j i p ij 0 j < i i M i iv( v) ( σ ) j = i i M i M i i iv( v) ( σ ) + ( M i) σ( σ) ( v) j = i = M i i ( M i) σ( σ) ( v) j = i+ M i j i M j σ ( σ) j > i + j i 4

15 Performance Analysis of Slotted Aloha Total throughput (S) P suc ( i) Pr[Successful slot/ i users in backlog] i M i i M i (- v) ( M i) ( ) iv( v) ( ) = σ σ + σ M S = P = E[ P ( i)] = P ( i) π suc suc suc i i= 0 As a special case, we do not distinguish between backlogged packets and new packets (v = σ) ) P () i = Mσ( σ) M suc S = E[ P ( i)] = Mσ ( σ ) M suc When Mσ = G, M G M S = G M S = Ge G 5

16 Throughput Graph with Finite and Infinite Number of Users Red Curve: Blue Curves: S = Ge G M G S = G, M = , 7, 0, 3, 6, 9 M M increases Through hput (S) M increases Offered load (G) 6

17 Performance Analysis of Slotted Aloha Expected delay When the system is in state i there are M-i thinking users each generating packets in every slot with probability σ Average delay () i S = E [( M i ) σ ] = ( M i ) σπ = ( M N ) σ N : the average number of backlogged users b : the average rate at which packets join the backlog N/ b : the average amount of time spent in the backlog (by Little s formula) (S-b)/S : a fraction of the packets is never backlogged (need only slot ) b/s : a fraction of the packets suffers the backlog delay S b b N N D = + + = + S S b S By equation () M = + σ S 7

18 Delay vs. Throughput M increases, Delay (with saturated throughput) increases M=0 Expe ected Delay (D D) M=20 M=30 M=40 M=50 M increases Throughput(S) 8

19 IEEE 802. MAC 프로토콜성능분석 - M/G/ Busy Period 분석기법 : CSMA/CA - M/G/ Busy Period 분석기법 : CSMA/CA with Capture Effect -TFA 분석기법 : CSMA/CA - Binary Exponential Backoff 분석 : CSMA/CA 9

20 IEEE 802. MAC 프로토콜 Network configuration Ad Hoc network / Infrastructure network Service type Asynchronous / Time bounded traffic service Service functions Asynchronous traffic => Distributed Coordination Function (DCF) Time bounded traffic => Point Coordination Function (PCF) Superframe Contention-Free Burst, Contention Traffic Superframe Contention-Free Burst Contention Traffic 20

21 DCF (Distributed Coordination Function) CSMA/CA protocol Use different Inter Frame Space (IFS) to differentiate traffic SIFS (Short Inter Frame Space) : High Priority PIFS (PCF Inter Frame Space) : Medium Priority DIFS (DCF Inter Frame Space) : Low Priority Sense channel during DIFS DIFS Contention Window DIFS PIFS Busy Medium SIFS Backoff-Window Next Frame Slot time Defer Access Backoff slot reduced d when channel is idle 2

22 PCF (Polling Coordination Function) Send request in contention period AP poll Station ti by the polling list Polling List Delete from list when idle too long Add to list when activity Dynamic Polling List Polling List Delete from list when idle too long Async Traffic CF-B CF-B CF-B CF-B CF-B SFP SFP : Superframe Period, CF-B : Contention Free Burst 22

23 IEEE 802. MAC 프로토콜성능분석기법들 M/G/ Busy period 분석기법 Markov Chain model Imbedded Point Insert Consider the steady state and then calculate the state transition probabilities Demerit : System state is increasing as the number of terminals and the state => Computing complexity is also increasing TFA (Transient Fluid Approximation) o TFA => 993 by K. Mukumoto[5] in Japan Similar to EPA (Equilibrium Point Approximation) but not consider the Equilibrium point Define the system vector as the number of state, calculate vector transition probability matrix Find the Equilibrium point using the probability matrix Recursive iteration Bianchi 에의한 binary exponential backoff 분석기법 23

24 M/G/ Busy period 분석기법을통한 CSMA/CA 프로토콜성능분석 24

25 System Model System Model Finite population Slotted Channel CSMA/CA = -persistent CSMA + p-persistent persistent CSMA Cannel (Idle period and Busy period ) Idle Period : no packet is generated Busy period : one or more terminals try to transmit a packet Renewal Theory Idle period and Busy period are independent and geometric distribution The number of users : M Slot size (propagation p delay) : a Packet arrival rate in a slot : g (0 < g <) Packet transmission probability : p ( 0 < p ) All terminals are synchronized. Noiseless channel model Non-capture effect Distance of source and destination pairs is equal 25

26 CSMA/CA Sub-period Model DIFS DIFS DIFS Transmission Delay Transmission Period Period f a +a f D () f T () D (2) T (2) I time B () B (2) Busy Period Idle Period - DIFS : DCF Inter-Frame Space 26

27 Basic CSMA/CA flow chart Slotted CSMA/CA Idle Packet No Channel Busy? Yes wait until next slot Channel Busy? Yes Transmit No x := random Collision? Yes Yes x < p No No Idle Wait until next slot Yes No channel Busy? random delay 27

28 CSMA/CA Throughput Analysis Basic concept I : Idle period, B: Busy period, U : Useful transmission period S U = I + B 분석순서 평균 Busy period 평균 Useful transmission period 평균 Idle period 28

29 Busy Period and Useful Transmission Period Busy period and Useful transmission period B U ( j ) ( j ) = ( ) ( ) D + T ; j = ( j ) ( j ) f + D + T ; j = 2,3, ( j ) T = if is successful 0 if T ( j ) is unsuccessful B = B U = U j 번째 cycle 에서의 Busy period 와 Useful transmission period J J ( j ) ( j ), : Total Busy period와 Total Useful transmission period j= j= Busy period and sub-busy period Prob [ one or more packets arrive during ((/ a) + ) slots ] a M = ( g ) ( / + ) j- 번째 cycle 까지계속하나이상의패킷이전송될확률 Prob[ J = j ] = [ ( g) ] ( g) ( / a + ) M j ( / a + ) M J = ; j = 2,, j 번째 cycle에서어떤패킷도전송되지않을확률 ( g )( / a+ ) M B = E [ B ( ) ] + ( 2 ) ( J ) E [ B ] U = E [ U ( ) ] + ( 2 ) ( J ) E [ U ] 29

30 Idle Period and Probability of n Packets Transmitted during X slots Idle period distribution and average Idle period (geometric distribution) ( k ) M M Prob [ I = ka] = ( g ) [ ( g ) ] ; k=, 2,. I = a [ ( ) ] g M The probability that n users are arrived during X slots P n ( X ) = n packets arrive in M users during X slots Prob one or more packets arrive in M druing X slots M [ ( g) ] ( g) n = XM ( g ) ; n= 2,,, M. X n X( M n) 30

31 Busy Period and Useful Transmission Period The probability that n customer arrive during (j-)th sub- busy period ( j ) Prob [ N0 = n ] = Pn (( / a) + ) j= 2, 3, N o (j) : the number of users at the beginning of j th sub-busy busy period Expected delay of jth cycle (N o (j) = n and j > ) ( j ) ( j ) kn k ( m - n ) Prob b[ D ka N 0 = n ] = ( - p ) ( - g ) ( j ) ( j ) kn k ( M n 0 ) k = E[ D N = n ] = a ( p) ( g) ; j 2, i=, 2, 3, ( j ) E[ D ] M f [ ( g ) ] ; j = a k (( / a ) + ) k k = {( p) ( g) [( p) ( g) ]} (( / a ) ) M + g k ( ) = (( / a ) + a ) M km ( g) ( g) ; j = 2,3, k = M 3

32 Sum of Idle Period and Busy Period B+ I = + + () (2) EB [ ] ( J ) EB [ ] I = () () (2) (2) ED [ T ] ( J ) E [ f D T ] I = f[ ( g) M ] + + a a + f + + a g ( g) k= ((/ a) + ) M ( )[ ( ) ] ((/ a) + ) M + a p g p g k ((/ a) + ) k k M {( ) ( ) [ ( ) ( ) ]} ((/ a) + a) M km a a( g) ( g) + k= ( g) M 32

33 Useful Transmission Period Calculation ( j) ( j) ( j) E[ U D ka, N0 = n ] n np( p) ; k = 0 = n ( M n) n ( M n) [ np( p) ( g) + ( p) ( M n) g( g) ] ; k > 0 ( j ) ( j ) E[ U N n ] 0 = ( j ) ( j ) ( j ) ( j ) ( j ) = E[ U D ka, N = n ] Prob [ D ka N = n ] k = n ( M n ) n ( M n ) = [ np ( p ) ( g ) + ( p ) ( M n ) g ( g ) ] k = [( p) ( g) ( ) ] + np( p) kn k M n n = [ np( p) ( g ) k = ( k+ ) n ( k+ )( M n ) + ( p) ( ) ( M n) g( g) ( )( ) ] + np( p) k+ n k+ M n n 33

34 Average Useful Transmission Period E [ U ( j ) ] = Mg( g) ( g) M M M (( / a ) + ) M ( g ) n= k= [ np( p) ( g) ; j = ( k+ ) n ( k+ )( M n) ( ) ( )( ) + ( M n)( p) g( g) ] + np( p) k+ n k+ M n n M [ ( g) ] ( g) n (( / a) + ) n (( / a) + )( M n) ; j = 2, 3, 34

35 Useful Transmission Period U ( = EU [ ) ( ) ] + ( J ) EU [ 2 ] = M M Mg( g) + np p g M a M [ ( ) ( ) (( / ) + ) ( g ) ( g ) N= k= ( k+ ) n ( k+ )( M n) n + ( M n)( p) g( g) ] + np( p) M a + n [ ( g) ] ( g) n (( / ) ) (( / a) + )( M n) ( k+ ) n ( k+ )( M n) 35

36 Throughput of Basic CSMA/CA S = U B + I M M Mg g ( ) ( k+ ) n + [ np( p) M (( / a) + ) M ( g ) ( g ) N = k= ( k+ )( M n) ( k+ ) n ( k+ )( M n) ( g) + ( M n)( p) g( g) ] M n (( / a) + ) n (( / a) + )( M n) + np ( p ) [ ( g ) ] ( g ) n = f[ ( g) M ] + + a (( / a ) + ) M a ( f + + a) [ ( g ) ] + (( / a) + ) M ( g ) k (( / a ) + ) k k M + a {( p) ( g ) [( p) ( g ) ]} k= a a M km a (( / ) + ) a ( g ) ( g ) + M k= ( g ) 36

37 CSMA/CA Delay Analysis Use channel throughput calculations Average number of retransmission for a packet G S Channel state when the packet is arrived Idle period : B Delay period in Busy period : I + I Transmission period in Busy period : B D + I B B + Average packet delay for Basic CSMA/CA Y : Random delay L G = S D [ + a + Y + R ] + + a + R I 37

38 CSMA/CA Delay Analysis R (delay for a packet) 2 I D B D ( + a) R = f + f + + E D B + I B + I B + I 2( + a) D (backoff delay) D = E D + J E D () ( 2 ) [ ] ( ) [ ] M = f [ ( g ) ] + a ( g ) ((/ a ) + ) M (2) [ ] k = k = k ((/ a ) + ) k k M ((/ a ) + a ) M km {( p) ( g ) [ ( p) ( g ) ]} ( g ) ( g ) E[ D (2) ] calculation a ( 2) k (( / a) + ) k k ED [ ] = {( p) ( g) [( p) ( g) ]} (( / a) ) M ( + g) k= a a M km ( g) (( / ) + ) ( g) k= M 38

39 Expansion to -Persistent CSMA in Infinite Population Model p =, f = 0 and M, ag = gm B U + a a + I = + G( + a) ag e e age G ( + a ) e = + e e e ag G ( + a ) ag G ( + a ) G ( + a ) Slotted -persistent CSMA => In 975, Kleinrock s result S = Ge G ( + a ) [ + a e ag ] ( ( + a ) ( + e ) + ae ag G ( + a ) 39

40 Analytic Results of Basic CSMA/CA Throughput & Delay when the number of user is fixed at 5(a = 0.0, p = 0.03, l = 3) 200 Thro ughput (S S) Simulation Analysis Nor rmalized Delay Offered Load (G) 40

41 Analytic Results of Basic CSMA/CA Packet delay of Basic CSMA/CA when the number of users is fixed at 5 (a =00 0.0, p = , l =3) 200 Norm malized De elay Simulation Analysis Offered Load (G) 4

42 Analytic Results of CSMA/CA Throughput (a=0.0, p = 0.03, l =3, RTS = 0.05, CTS= 0.03, ACK = 0.03, SIFS = 0.0 ) Through hput (S) Basic CSMA/CA SW CSMA/CA 4-WH CSMA/CA Offered Load (G) - J. H. Kim and J. K. Lee, "Performance of Carrier Sense Multiple Access with Collision Avoidance Protocols in Wireless LANs," WPC, Kluwer, Vol. No. 2, pp.6-83, Nov. 999.

43 Analytic Results of CSMA/CA Delay (a=0.0, p = 0.03, l =3, RTS = 0.05, CTS= 0.03, ACK = 0.03, SIFS = 0.0 Y=0.06) No ormalized Delay WH CSMA/CA SW CSMA/CA Basic CSMA/CA Offered Load (G).0.

44 Capture Effect 를고려한 CSMA/CA 분석기법 44

45 Channel Model Channel Model Multipath fading : Rayleigh 분포로가정 Shadow fading : Log-normal 분포로가정 거리에따른감쇠고려 45

46 Received Signal Power (w 0 ) f w s ( ws) = exp 0 0 w L w w Multipath fading s Near-far effect ( ξ r w ) L 2 f () r ln exp 2σ w 2σ s L s L Shadowing dr dw L w s : 수신을원하는테스트신호의수신전력 w L : 페이딩에의한수신전력 r : 테스트송수신터미널의거리 ξ σ s : 거리에의함감쇠상수 : Shadow fading 의표준편차 46

47 Capture Effect 캡쳐현상 (Capture effect) Test Signal( w0 ) Fading Signal(w w L ) > Capture ratio( z) 캡쳐확률 (Capture Probability : q(,z)) 2 2 ( ) ( ) ( ) q(, z) = r exp x f x, y exp y dy dx dr 0 π where, 2 f x,y zr s x y zr 2 2 ( ) Δ exp σ ( ) arctan exp σ ( x y) s 47

48 Capture Probability 캡쳐확률 (Capture probability : q(n- z)) ( ) 2 qn ( z) = rexp x f( x, y) exp( y ) 2 2 dy dxdr π 0 π n r exp ( x ) 2 f ( x, y ) exp( y ) dy2 dx dr π 0 π where, f ( x,y ) Δ zr exp σ s ( x y ) exp s x 4 σ ( y ) 2 zr f ( x 2,y 2 ) Δ zr 2 exp σ s ( x 2 y 2 ) exp σ ( x 4 s 2 y 2 ) 2 zr n :the number of stations, z : capture ratio, r : a distance between terminals y ln ( wr ) σ s 48

49 Capture Probability 사용자수와 Capture ratio 에대한 Capture probability Number of users 49

50 Error Free Channel model VS. Capture Effect 분석방법 기존의 Error Free 모델을사용 평균 Idle 기간, 평균 Busy 기간은동일 단, 전송에성공할확률을새롭게확장 (Capture Prob. 고려 ) Error Free Fading Multi-user Model Model Capture Model Prob() x q( z) x q( z) Prob(n) 0 0 n x q(n z) 50

51 CSMA/CA Throughput in Capture Effect U S = B+ I M i M i M [ ( g) ] ( g) M n i n i n i qi z p p M + a M ( g) g i i n (, ) + ( ) (( / ) ) = ( ) = i= n M n l M n l k g ( g) + ( M n)( p) ( + ) n ( k+ )( M n) g( g) ( i+ l) q( i+ l, z ) l l= n M n n ( p ) ( g ) n + ( ) ( ) ( ) ( ) i n i p p iq i, z n M n p g i i= M ( TP / a) n ( TP / a)( M n) B B [ ( g) ] ( g) n ( ) ( TP / a ) M B g = M a (( / a ) + ) M f [ ( g ) ] + + a + ( f + + a ) [ ( g ) ] + (( / a) + ) M ( g) k (( / a) + ) k k M (( / ) ) a {( p) ( g) [ ( p) ( g) ]} a( g) a + a M ( g) km = = k k a + M ( g ) 5

52 CSMA/CA Throughput in Capture Effect a = 0.0, p = 0.03, DIFS = 0.06, Y = 0.06, σ s = 6 db, ξ = 4, M =50 - J. H. Kim and J. K. Lee, Capture Effects of Wireless CSMA/CA Protocols in Rayleigh and Shadow Fading Channels, IEEE Tran. on Vehicular Technology, vol. 48. No.4, pp , July

53 TFA 기법을통한 CSMA/CA 프로토콜성능분석 53

54 System Model System model Finite population Slotted Channel CSMA/CA = -persistent CSMA + p-persistent persistent CSMA Cannel (Idle period and Busy period ) Idle Period : no packet is generated Busy period : one or more terminals try to transmit a packet Transient Fluid Approximation Idle period and Busy yperiod Slot size (propagation delay) : τ All terminals are synchronized. Noiseless channel model Non-capture effect Distance of source and destination pairs are equal 54

55 CSMA/CA protocol channel model Imbedded point : the beginning of the cycle DIFS DIFS DIFS Transmission Delay Transmission Period Period τ Busy Period Idle Period time Propagation delay 55

56 The Activities of Each Terminals in CSMA/CA I I PG CS WT PT B B I S F WT2 WT3 I TRp B B Abbreviation PG : Packet Generation mode CS : Carrier Sense mode WT, WT3 : Wait for DIFS and check channel WT2 : Wait until channel goes idle TRp : Transmission with probability p PT : Packet Transmission 56

57 CSMA/CA Analytic Model and Assumptions Analytical model TH : Thinking mode TR : Transmission mode P P 2 P 22 2 TH TR Notation and assumptions m(t) = # of terminals in mode TH n(t) = # of terminals in mode TR T = Transmission i time for data packet T D = Delay time for DIFS T C = Length of a cycle σ= packet arrival rate in a slot λ= -e -σ P 2 57

58 State Transition Probability Calculate transition probability P = Pr { the terminal ld doesn't generate a packet kt th the slot ltis idle } + Pr { the terminal doesn't generate a packet at least one terminal transmit packet } + Pr { the terminal generates a packet and sends it successfully } P P P n σ ( ) ( T+ TD + τ ) ( ) στ mt () n στ ( mt ()) = e p + e p e στ n ( )( ) στ ( mt ( ) ) e p e + = P 2 2 = Pr { only one terminal transmits a packet in TR mode } n ( ) m() t = p p e στ = P

59 Throughput and Delay Calculate average T C Tc = I + B n στ m n = τ( p) e ( ) ( ) e + T + TD + τ p e στ m e where, m e 은 equilibrium point 에서의 TH mode 에있는사용자수 ( m(t) m e (t )) Throughput (S) S = T P Succ T C where n m ( )( ) e ( ) P = m e p e + n p p e Succ e στ στ n στm e e e e Average packet delay (D) By Little's formula D = M S σ + where, M is the total number of terminals and σ means packet generate rate. 59

60 Performance Result : Analysis and Simulation 성능분석결과 Th hroughput (S ) Simulation (S) Simulation (S) Analysis (S) Analysis (S) 0.8 Simulation (D) Simulation (D) Analysis (D) Analysis (D) Avea arge Delay ( D) Transmission Probability (p ) Offered Load (G) Th hroughput (S ) Avea arge Delay ( D) Throughput and Delay versus Packet transmission probability Throughput and Delay versus Offered load 60

61 Binary exponential backoff 분석기법 - Bianch s Approach 6

62 Packet Transmission Probability System model Ideal channel conditions ( i.e. no hidden terminals ) Fixed number of stations Each station always has a packet available for transmission CW : Contention Window ( 0 to CW_min ~ CW_max ) : Backoff delay = INT( CW Random() ) Slot Time CW is doubled when transmission is failed CW_min :.a = 5,.b = 7,.b HR = 3, CW_max = 023 Analysis process The behavior of a single station with a Markov model τ The stationary probability that the station transmits a packet in a generic slot time The throughput of both Basic and RTS/CTS access modes as function of the computed value τ 62

63 Packet Transmission Probability Markov Chain model for the backoff window size b(t) : Representing the backoff time counter for a given station s(t) : Representing the backoff stage(0,,m) of the station at time t The collision probability of the transmitted packet is constant and independent Retransmit when the backoff time counter is zero 63

64 Packet Transmission Probability In Markov chain, one-step transition probabilities are Pik {, ik, + } = k (0, Wi 2) i (0, m) P{0, k i,0} = ( pc ) / W0 k (0, W0 ) i (0, m) Pik {, i,0} = pc / Wi k (0, Wi ) i (, m) Pmk {, m,0} = pc / Wm k (0, Wm ).. The probability that the backoff time counter decreases is one 2. Backoff Counter가 0 이되었을경우 RTS를전송하고, 다시 backoff counter를 {0,W 0 } 사이의임의의수를선택 3. i 번 backoff 한 station 이 backoff counter 가 0 이되었을경우 RTS 를전송하였는데 CTS 를못받는경우 Cw 가 W i- 에서 W i 로증가 4. m 번째 backoff 한 station ti 의 RTS 가충돌이발생할경우다시재전송하여야하는데 W m 은 Cwmax이므로변하지않음 64

65 Maximum Saturation Throughput Analysis maximum saturation throughput Maximum throughput is affected by the network size Throughput versus the transmission probability τ for the basic access method Throughput versus the transmission probability τ for the RTS/CTS mechanism 65

66 Disadvantages of Binary Exponential Backoff Analysis Method The collision probability (p c ) is fixed p c is affected by the transmission probability (τ) Each station always has a packet available for transmission The probability of backoff counter decrease is The backoff counter is not decreased in busy period Results based on the Saturated Throughput 66

67 RFID 성능분석 67

68 RFID system What is the RFID system? The RFID system is a simple form of ubiquitous sensor networks that are used to identify physical objects Application of RFID system Asset tracking(e.g. g libraries, animals) Automated inventory Stock-keeping keeping Toll collecting Hospital Cloth ID, Credit card Pet, Cow Casino: i-coin Secret Document 68

69 Anti-Collision Algorithm Tag collision problem in RFID system It is impossible to communicate among passive tags The reader broadcasts the request message to the tags If there are more than one tag response for the reader s request, their responses will collide We need an anti-collision algorithm to solve collision problem Tag collision problem 69

70 Multi-tag tag Anti-collision Algorithms in Standards Arbitration Air Interface EPC Data rate (R->T / T->R) (R->T / T->R) Security AutoID Class 0 Bit-by-bit Binary Tree Pulse Width Mod./ FSK 64/96b 40/80 kbps / 40/80 kbps 24-bit kill AutoID Class Binary tree using 8 bin slots Pulse Width Mod. / Pulse Interval AM 64/96b 70.8 kbps/ kbps 8-bit kill ISO TYPE A Framed Slotted Pulse interval ASK / FM0 not defined 33 kbps / 40 kbps None ISO TYPE B Probabilistic Binary tree Manchester-ASK / FM0 not defined 8/40 kbps / 40 kbps None ISO TYPE C (Gen 2) Probabilistic Slotted Pulse interval ASK / Miller, FM0 96/496b 40 kbps / 640 kbps 32-bit kill, Access 70

71 Dynamic framed slotted ALOHA I/II algorithms Dynamic framed slotted ALOHA I/II algorithms Enhance the performance of the algorithm defined in ISO Type A Basic concept Two Tag Estimation Methods (TEM) C ratio C rate Ratio of the number of collided slots to the frame size n Number of collided slots n = = +. Frame size L L Number of tags related with collision in a slot Prob.that there is the collision i in aslot P = = - Prob. that a tag transfers its ID successfully P idle coll + P coll n Ratio Collision L=8 L=6 L=32 Process for tag estimation L=64 L=28 L=92 L=256 L=320 L=52 L=640 C tags = C = opt _ rate Number of estimated tags = M coll Number of tags Where means the number of collided slots in a frame M coll 7

72 RFID Performance Analysis Performance evaluation Identification time vs. number of tags 6.5 Id entificatio n time Nu mbe r of tags Vogt Vogt 2 tion tim e Identifica Number of tags DFSA Slot - 28 Slot Vogt Vogt 2 DFSA J. R. Cha and J. H. Kim, Dynamic Framed Slotted ALOHA Algorithm using Fast Tag Estimation method for RFID System, in Proc. CCNC2006, Las Vegas, USA, Jan. 8-0,

73 IEEE MAC 프로토콜성능분석 73

74 IEEE MAC 프로토콜 TDMA (Time Division Multiple Access)/Framed slotted aloha protocol Optimize the Initial Backoff Window Size Binary exponential backoff algorithm is applied when the collision is occurred The frames are divided by bandwidth allocation MAP message according to the usage. Gap between Gap between SSs Uplink frame structure transmission and reception Initial Ranging Period Contention Period Data Transmission i Period of SS Data Transmission i Period of SS N Access Collision Access Request Collision Bandwidth Request Bandwidth 74

75 System Model Notations and assumptions Transmission Opportunity is equal to a slot made of eight minislots The propagation delay is neglected. The packet transmission error is not considered. N : The number of station F : The average size of Frame. (F=CP+DTP+IRP) CP : Contention Period, DTP : Data Transmission Period, IRP : Initial Ranging g Period p c : The collision probability of the transmitted packet M : The maximum retry τ : The transmission probability of a station during a slot W 0 : The size of the initial Backoff Window 75

76 Frame structure System Model (2) CP DTP IRP STA(0) W 0 0( (0) W 0 () The backoff window size increases according to this equation, when the request messages are collided W = rw W W W 0 i M i i 0 0 i max W 0 : initial backoff window, r : backoff factor, M : maximum retry, i : the number of retransmission STA() W (0) W () : collision : success 76

77 Packet Transmission Probability Markov chain model for the backoff window size 77

78 Packet Transmission Probability State transition probability Pik {, ik, + } = k (0, Wi 2) i (0, M) P{0, k i,0} = ( pc ) / W0 k (0, W0 ) i (0, M) Pik {, i,0} = pc / Wi k (0, Wi ) i (, M) PMk {, M,0} = pc / WM k (0, WM ). Backoff time counter 가 씩감소할확률 Backoff Counter 가 0 0 이되었을경우 RTS 를전송하고, 다시 backoff counter를 {0,W 0 } 사이의임의의수를선택 i 번 backoff한 station이 backoff counter가 0 이되었을경우 RTS를전송하였는데 CTS 를못받는경우 Cw 가 W i- 에서 W i 로증가 m 번째 backoff 한 station 의 RTS 가충돌이발생할경우다시재전송하여야하는데 W m 은 Cwmax 이므로변하지않음 78

79 Packet Transmission Probability Let bik, = lim t P{ s( t) = i, b( t) = k}, i (0, M), k (0, Wi ) be the stationary distribution of the chain M pc b j 0 j,0 i= = ( ) ( 0) Wi k bik, = pb c i,0 (0 i M) W < < i p ( b b c M,0 M,0) ( i M + = ) b = p b < i< M i i,0 c 0,0 0 p t M i W0 pw c 0 (2 p ) i 0 c 2 = + + = p c 와 p t 에관한등식이기때문에 b N p p t = ( pc ) = 와연동하여 p c 와 p t 에관한 M c M,0 b0,0 pc 해를구함 /( ) 79

80 IEEE MAC 프로토콜성능분석 Throughput (S) N S = pt( pt) N Average delay (D) p t 는하나의 Station 이임의의 slot 으로패킷을전송할확률 N : Station 수 D i 는 i 번째대역폭요청메시지를재전송하는 SS 가임의로선택한 backoff counter N R D i + Di + DN D R N R D= E F + Di + CP + F + DN CP no drop. R i= 0 CP CP CP CP i 번째재전송시지연시간 ( Di + )/ CP :i 번째재전송에서지연되는프레임의수 Di + ( Di + )/ CP CP : 마지막프레임에서남아있는 backoff counter N R 번째재전송시지연시간 D N R / CP : i 번째재전송에서지연되는프레임의수 DN D / R N CP CP R : 마지막프레임에서남아있는 backoff counter 80

81 IEEE MAC 프로토콜성능분석 Average delay M + ( M + ) p W ( p ) r p = ( ) + + r p p p CP M + p ( M + ) p c c + ( F CP). M + 2 pc pc M 0 c n c c D F rp M+ c M 2 ( ) + c n= 0 2 c c M : Maximum retry r : Backoff factor ( Binary exponential backoff r = 2) Packet Drop Probability (p d ) p p + d M = pc p c : 패킷전송시충돌이발생할확률 8

82 IEEE MAC 프로토콜성능분석 Throughput and Delay 분석결과 Throughput according to the number of users (M=6) Delay according to the number of users (M=6) S. M. Oh and J. H. Kim, "The Optimization of the Collision Resolution Algorithm for Broadband Wireless Access Network," in Proc. ICACT'06, Vol 3, Pyong Chang, Korea, Feb , 2006, pp

83 Summary and Discussion Wireless MAC 프로토콜성능분석 Rigorous Probability 분석기법 계산이복잡하고 General한형태를찾기어려움 RFID (Binary Tree Contention Resolution) 분석 M/G/ Busy period 분석기법 시스템모델링어려움, 계산과정복잡 Slotted Aloha (Infinite number user model), CSMA/CA 분석, Capture Effect 를고려한 CSMA/CA 분석 Discrete State Continuous Time Markov Chain 분석기법 분석결과의높은정확성, state 의수, 전이확률계산과정복잡 Slotted Aloha (Finite number user model), Binary Exponential Backoff TFA 분석기법 분석과정수월, 분석결과에대한검증과정필요 ISMA, PRAM, CSMA/CA 분석 Wireless MAC Protocol 의발전 Hbid Hybrid 형태로복잡하게발전 Cross Layer Optimization Issues : Short Range/Wide Area/Data Rate 83

84 Thank you!! jkim@ajou.ac.kr Home : 84

85 Reference ) R. Rom and M. Sidi, Multiple Access Protocols Performance and Analysis, Springer- Verlag 2) JHKimandJKLee"Performance J. H. J. K. Lee, of Carrier Sense Multiple Access with Collision Avoidance Protocols in Wireless LANs," Wireless Personal Communications, Kluwer academic Publishers, Vol. No. 2, pp.6-83, Nov ) J. H. Kim and J. K. Lee, Capture Effects of Wireless CSMA/CA Protocols in Rayleigh and Shadow Fading Channels, IEEE Tran. on Vehicular Technology, vol. 48. No.4, pp , July ) G. Bianchi, Performance Analysis of the IEEE 802. Distributed Coordination Function, IEEE J.Select.Area Commun., vol. 8, no. 3, pp , 547, Mar ) K. Mukumoto, Performance evaluation of mobile packet communication networks by using transient fluid approximation analysis method, Ph. D. Dissertation, Shizuoka University, Japan, Apr. 993 (in Japanese) 6) J. R. Cha and J. H. Kim, Dynamic Framed Slotted ALOHA Algorithm using Fast Tag Estimation method for RFID System, in Proc. CCNC2006, Las Vegas, USA, Jan. 8-0, ) H. S. Choi, J. R. Cha, and J. H. Kim, Fast Wireless ess Anti-collision o Algorithm in Ubiquitous ID System, in Proc. IEEE VTC 2004, L.A., USA, Sep , ) S. M. Oh and J. H. Kim, "The Optimization of the Collision Resolution Algorithm for Broadband Wireless Access Network," in Proc. ICACT'06, Vol 3, Pyong Chang, Korea, Feb , , pp