T R R ECHNICAL ESEARCH EPORT On a Random Sum Formula for the Busy Period of the M|G| Infinity Queue with Applications by Armand M. Makowski CSHCN TR 2001-4 (ISR TR 2001-9) The Center for Satellite and Hybrid Communication Networks is a NASA-sponsored Commercial Space Center also supported by the Department of Defense (DOD), industry, the State of Maryland, the University of Maryland and the Institute for Systems Research. This document is a technical report in the CSHCN series originating at the University of Maryland. Web site http://www.isr.umd.edu/CSHCN/ Report Documentation Page Form Approved OMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. 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SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT see report 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18. NUMBER 19a. NAME OF ABSTRACT OF PAGES RESPONSIBLE PERSON a. REPORT b. ABSTRACT c. THIS PAGE 12 unclassified unclassified unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 On a random sum formula for the busy period M G of the j j1 queue with applications y Armand M. Makowski [email protected] (301) 405-6844 Abstract A random sum formula is derived for the forward recurrence time associated with the busy period length of the MjGj1 queue. This result is then used to (i) provide a necessary and su(cid:14)cient condition for the subexponentiality of this forward recurrence time, and (ii) establishastochasticcomparisonintheconvex increasing(variability) orderingbetween the busyperiodsintwo MjGj1 queues withservice times comparable in the convex increasing ordering. Key words: Random sums, MjGj1 queues, busy period, subexponen- tiality, stochastic orderings AMS: 60K25, 60E15 1 Introduction Random sums, and geometric random sums in particular, are a common occurence in applied probability models [4, 6]. For instance, it is well known y Electrical Engineering Department and Institute for Systems Research, University of Maryland, College Park, MD 20742. The work of this author was supported partially through NSF Grant NSFD CDR-88-03012, NASA Grant NAGW77S and the Army Re- search Laboratoryunder Cooperative Agreement No. DAAL01-96-2-0002. 1 that the stationary waiting time of a stable MjGIj1 queue with Poisson arrival rate (cid:21) and generic service time (cid:27) can be represented (in distribution) as a geometric sum of i.i.d. rvs distributed like the forward recurrence time ? (cid:27) associated with (cid:27) [7]. A similar representation holds for the stationary waiting time of a stable GIjGIj1 queue in terms of ladder height rvs [10]. Such random sum representations have proved useful for establishing various properties of interest [4, 6]. Perhaps less well known is the fact that similar geometric sums can also be found in the context of MjGIj1 queues. Indeed, consider a standard MjGj1queuewitharrivalrate(cid:21)andgenericservicetime(cid:27),andletB denote its generic busy period length. Using some classical results on the Laplace ? transform of B, we show that the forward recurrence time B associated with the busy period of an MjGIj1 can be represented as a geometric sum of i.i.d. rvs whose common distribution is derived from that of the forward ? recurrence time (cid:27) . This random sum representation is presented in Section 2, and its proof is given in Section 5. We give two applications for this representation result: In Section 3, we ? ? show that the subexponentiality of (cid:27) is equivalent to that of B , with a simple relation between the tail of their distributions. This result was orig- inally derived by Boxma [1] for regularly varying (cid:27), and further generalized in the form given here (but with a di(cid:11)erent proof) by Jelenkovic and Lazar ? [5] to the case where (cid:27) is subexponential. In Section 4, we investigate the monotonicitypropertiesofMjGIj1queues underthe(increasing)convex or- dering. Using the random sum representation we show that the busy period distribution is monotone in the increasing convex ordering when the service time distribution is increased in the increasing convex ordering. To the best of the author’s knowledge this result is new [14, p. 147]. A word on the notation used in this paper: For any integrable IR+{valued ? rv X, the forward recurrence time X is de(cid:12)ned as the rv with integrated tail distribution given by 1 ? 1 P[X > x] := P[X > t]dt; x (cid:21) 0: (1) E[X] Zx We shall (cid:12)nd it useful to use the equivalent representation + ? E[(X (cid:0)x) ] P[X > x] := ; x (cid:21) 0 (2) E[X] 2 + (where we write x = max(x;0) for any scalar x). For mappings f;g : IR+ ! f(x) IR, the relation f(x) (cid:24) g(x) is understood as limx!1 g(x) = 1, the quali(cid:12)er (x ! 1) being omitted for the sake of notational simplicity. 2 A random sum in the MjGj1 queue Consider a standard MjGj1 queue with arrival rate (cid:21) and generic service time (cid:27); we refer to this queueing system as the MjGj1 queue ((cid:21);(cid:27)). Let B denote its generic busy period, i.e., the length of time that elapses between the arrival of a customer (cid:12)nding an empty system and the departure of the (cid:12)rst customer thereafter which leaves the system empty. ? In Section 5 we show that the forward recurrence timeB associated with B admits a random sum representation: In order to present this result, let (cid:23) denote the IN{valued rv which is geometrically distributed according to ‘(cid:0)1 P[(cid:23) = ‘] = (1(cid:0)K)K ; ‘ = 1;2;::: (3) with (cid:0)(cid:26) (cid:26) := (cid:21)E[(cid:27)] and K := 1(cid:0)e : (4) Next, we introduce the IR+-valued rv U distributed according to 1 (cid:0)(cid:26)P[(cid:27)?(cid:20)x] P[U (cid:20) x] := (cid:16)1(cid:0)e (cid:17); x (cid:21) 0 (5) K ? where (cid:27) is the forward recurrence time associated with the generic service time (cid:27). We are now ready to formulate the key observation of the paper: Theorem 1 Consider a sequence of IR+{valued i.i.d. rvs fUn; n = 1;2;:::g distributed according to (5), and an IN{valued rv (cid:23) distributed according to (12). Then, with the sequence fUn; n = 1;2;:::g taken to be independent of the rv (cid:23), it holds that ? B =st U1 +:::+U(cid:23): (6) where =st denotes equality in distribution. In analogy with standard results for the GIjGIj1 queue [10], it is natural to wonder whether the forward recurrence time associated with the busy 3 period in the GIjGIj1 queue also admits a representation as a geometric randomsumofi.i.d. rvswhosedistributionisnowderivedfromthatofladder height rvs. To the best of the author’s knowledge no results along these lines are known. In the process of establishing Theorem 1 in Section 5 we shall show that K E[B] = : (7) (cid:21)(1(cid:0)K) We also note from (4) and (5) that (cid:0) (cid:26) e (cid:26)P[(cid:27)?>x] P[U > x] = e (cid:0)1 ; x (cid:21) 0: (8) K (cid:16) (cid:17) Moreover, using (2) we see that (8) can be rewritten as (cid:0) (cid:26) e (cid:21)E[((cid:27)(cid:0)x)+] P[U > x] = e (cid:0)1 ; x (cid:21) 0: (9) K (cid:18) (cid:19) M G 3 Subexponentiality in the j j1 queue Webeginwithsomestandardde(cid:12)nitionsandfactsconcerningsubexponential rvs [2, 3]: The IR+-valued rv X is said to have a subexponential tail, denoted X 2 S, if P[X1 +:::+Xn > x] (cid:24) nP[X > x]; n = 1;2;::: (10) where fXn; n = 1;2;:::g denotes a sequence of i.i.d. rvs, each distributed like X. In fact, (10) holds for all n = 1;2;::: if and only if it holds for some n (cid:21) 2. Under appropriate conditions, the equivalences (10) can be extended to random sums [3, Thm. 1.3.9, p. 45] (and [3, Thm. A3.20, p. 580]). Proposition 1 Let the IN{valued rv N be independent of the sequence of i.i.d. rvs fX;Xn; n = 1;2;:::g. If X 2 S, then X1 +:::+XN 2 S with P[X1 +:::+XN > x] (cid:24) E[N]P[X > x] (11) N provided E z < 1 for some z > 1. h i 4 Of particular interest for the discusssion here is the case when N is dis- tributed according to the geometric distribution (cid:0) ‘ 1 P[N = ‘] = (1(cid:0)p)p ; ‘ = 1;2;::: (12) (cid:0) 1 for some 0 < p < 1. Standard calculations yield E[N] = (1(cid:0)p) , and 1 N ‘(cid:0)1 ‘ (1(cid:0)p)z (cid:0)1 Ehz i = X(1(cid:0)p)p z = ; jzj < p (13) ‘=1 1(cid:0)pz (cid:0)1 with p > 1. Thus, Proposition 1 applies, in fact, can be strenghtened as follows [3, Cor. A3.21, p. 581]: Proposition 2 Let the IN{valued rv N be independent of the sequence of i.i.d. rvs fX;Xn; n = 1;2;:::g, and assume N to be distributed according to (12). Then, X 2 S if and only if X1 +:::+XN 2 S, in which case (cid:0)1 P[X1 +:::+XN > x] (cid:24) (1(cid:0)p) P[X > x] (14) The main result of this section is the following Proposition 3 Consider a standard MjGj1 queue ((cid:21);(cid:27)) with generic busy ? ? period rv B. We have B 2 S if and only if (cid:27) 2 S, in which case ? (cid:26) ? P[B > x] (cid:24) (cid:0)(cid:26)P[(cid:27) > x]: (15) 1(cid:0)e Proof. Combining Theorem 1 with Proposition 2, we already get that ? B 2 S if and only U 2 S, in which case ? (cid:0)1 P[B > x] (cid:24) (1(cid:0)K) P[U > x]: (16) ? Next, with (8) in mind, we observe that limx!1P[(cid:27) > x] = 0, so that (cid:26)P[(cid:27)?>x] ? ? e = 1+(cid:26)P[(cid:27) > x]+o(P[(cid:27) > x]): Hence, from (8) we get (cid:0)(cid:26) e ? ? P[U > x] = ((cid:26)P[(cid:27) > x]+o(P[(cid:27) > x])); K 5 and the conclusion (cid:0) (cid:26) (cid:26)e ? P[U > x] (cid:24) P[(cid:27) > x] (17) K follows. Therefore, since S is closed under tail-equivalence [3, Lemma A3.15, ? p. 572], we get U 2 S if and only if (cid:27) 2 S, and we complete the proof of (15) by injecting this last fact with (17) into the equivalence (16). M G 4 Orderings in the j j1 queue For IR{valued random variables X and Y, we say that X is smaller than Y in the strong stochastic (resp. convex, increasing convex) ordering if E[’(X)] (cid:20) E[’(Y)] (18) for all mappings ’ : IR ! IR which are monotone increasing (resp. convex, increasing and convex) provided the expectations in (18) exist. In that case we write X (cid:20)st Y (resp. X (cid:20)cx Y, X (cid:20)icx Y). Additional material on these orderings can be found in the monographs [11, 13, 14]. The following result is well known [14, Prop. 2.2.5, p. 45]. Proposition 4 Let the IN{valued rv N be independent of the sequences of i.i.d. rvs fX;Xn; n = 1;2;:::g and fY;Yn; n = 1;2;:::g. If X (cid:20)st Y, then it holds that X1 +:::+XN (cid:20)st Y1 +:::+YN (19) Results similar to (19) hold mutatis mutandis under the weaker assump- tions X (cid:20)cx Y and X (cid:20)icx Y. The main result of this section is the following stochastic comparison. Proposition 5 ConsidertwoMjGj1queues ((cid:21);(cid:27)1)and((cid:21);(cid:27)2)withgeneric busy period rvs B1 and B2, respectively. If (cid:27)1 (cid:20)cx (cid:27)2, then B1 (cid:20)cx B2. Throughout, for each i = 1;2, quantities associated with the MjGj1 queues ((cid:21);(cid:27)i) are subscripted by i. Proof. Under the condition (cid:27)1 (cid:20)cx (cid:27)2, E[(cid:27)1] = E[(cid:27)2], whence (cid:26)1 = (cid:26)2 6 + + and K1 = K2, and the inequalities E[((cid:27)1 (cid:0)x) ] (cid:20) E[((cid:27)2 (cid:0)x) ] hold for all x (cid:21) 0. Invoking (9), we immediately conclude that U1 (cid:20)st U2. Next, applying Proposition 4 to the random sum representation (6), we see that ? ? B1 (cid:20)st B2, namely 1 1 1 1 P[B1 > t]dt (cid:20) P[B2 > t]dt; x (cid:21) 0: (20) E[B1] Zx E[B2] Zx This is equivalent to + + E[(B1 (cid:0)x) ] E[(B2 (cid:0)x) ] (cid:20) ; x (cid:21) 0: (21) E[B1] E[B2] Finally,observefrom(7)andfromtheobservationsmadeabovethatE[B1] = + + E[B2], so that E[(B1 (cid:0)x) ] (cid:20) E[(B2 (cid:0)x) ] for all x (cid:21) 0, and the desired conclusion readily follows [14, Thm. 1.3.1, p. 9]. Theliteraturecontainsfewstochasticcomparisonresultsforin(cid:12)niteserver queues; they dealmostlywiththenumberofcustomers, e.g., [14, Prop. 7.1.1, p. 127], [14, Table 7.2, p. 147]. However, a simple coupling argument readily leads to the following comparison: Proposition 6 Consider twoMjGj1queues ((cid:21);(cid:27)1)and((cid:21);(cid:27)2)withgeneric busy period rv B1 and B2, respectively. If (cid:27)1 (cid:20)st (cid:27)2, then B1 (cid:20)st B2. Finally, we combine Propositions 5 and 6 with the characterization of the convex increasing ordering provided in [9]: Proposition 7 ConsidertwoMjGj1queues ((cid:21);(cid:27)1)and((cid:21);(cid:27)2)withgeneric busy period rv B1 and B2, respectively. If (cid:27)1 (cid:20)icx (cid:27)2, then B1 (cid:20)icx B2. 5 A Proof of Theorem 1 Consider the process of particle counting as described in Chapter 6 of the monographby Tak(cid:19)acs [15, p. 205]. Type II counters areequivalent toin(cid:12)nite server queues if particles are interpreted as customers. So-called \registered" particles [15, p. 205] are those particles which arrive at an instant when there is no other particle present; in the in(cid:12)nite server queue context, such 7 a registered customer is a customer that initiates a busy period. Let the rv R denote the length of time that elpases between the arrival epochs of two consecutive registered particles, or equivalently, in the in(cid:12)nite server queue, the time duration between the start of two consecutive busy periods. Theorem 1 in [15, p. 210] provides a closed form expression for the Laplace{Stieltjes transform of the rv R when customers arriva according to a Poisson process: For the MjGj1 queue ((cid:21);(cid:27)), it holds that (cid:0)(cid:18)R 1 1 E e = 1(cid:0) (cid:1) ; (cid:18) (cid:21) 0 (22) (cid:21)+(cid:18) T((cid:18)) h i with 1 t T((cid:18)) := exp (cid:0)(cid:18)t(cid:0)(cid:21) P[(cid:27) > x]dx dt: (23) 0 0 Z (cid:18) Z (cid:19) Lemma 1 With the notation (4){(5), it holds that 1 (cid:0)(cid:18)U T((cid:18)) = 1(cid:0)KE e ; (cid:18) > 0: (24) (cid:18) (cid:16) h i(cid:17) Proof. Fix (cid:18) (cid:21) 0. From (5) we note that e(cid:0)(cid:21)E[(cid:27)]P[(cid:27)?(cid:20)t] = 1(cid:0)KP[U (cid:20) t]; t (cid:21) 0: (25) Making use of this fact in the de(cid:12)nition (23), we (cid:12)nd 1 (cid:0)(cid:18)t (cid:0)(cid:21)E[(cid:27)]P[(cid:27)?(cid:20)t] T((cid:18)) = e e dt 0 Z 1 (cid:0)(cid:18)t = e (1(cid:0)KP[U (cid:20) t])dt 0 Z 1 1 (cid:0)(cid:18)t = (cid:0)K e P[U (cid:20) t]dt (cid:18) 0 Z (cid:0)(cid:18)t 1 1 (cid:0)(cid:18)t 1 e e d = (cid:0)K P[U (cid:20) t] (cid:0) P[U (cid:20) t]dt (cid:18) " (cid:0)(cid:18) #0 Z0 (cid:0)(cid:18) dt ! and the desired conclusion (24) follows from the fact P[U (cid:20) 0] = 0. 8