CS SOR: Polling models

CS SOR: Polling models • Vacation models • Multi type branching processes • Polling systems (cycle times, queue lengths, waiting times, conservation laws, service policies, visit orders) Richard J. Boucheriedepartment of Applied Mathematics University of Twente

Polling models • N infinite buffer queues, Q1, …, QN • Service time distribution at queue j: Bj(.), mean βj, LST βj(.) • Poisson arrivals to queue j at rate λj • Single server in cyclic order • Switch over times: random variable Sj, mean σ j, LST σj(.) • This week:vacation queues • Next week…..Multi-type branching processes (Resing) • In two weeks: polling • Then: 3 presentations by you

Polling modelsToday: Vacation models • S.C. Borst. Polling Systems, CWI: Tract, chapters 1 – 3. • S.W. Fuhrmann, R.B. Cooper. Operations Research, Sep/Oct 1985, Vol. 33 Issue 5, p1117-1129 • J.A.C. Resing. Polling systems and multitype branching processes, Queueing Systems, 13, p 409 – 426 • I. Adan: Queueing Systems, lecture notes • M/G/1 queue, PK formula • M/G/1 queue with vacations • M/G/1 queue with Generalized vacations

M/G/1 queue • Poisson arrival process rate λ, single server, General service times, mean 1/μ=E(B) • Service time distribution FB(.), density fB(.), LST B • state: pair (n,x), n=#customer, x= received service time • Pollaczek-Khintchine formulafor queue length

Ancestral line • I0 group of customers • I1 set of customers who arrive while members of I0 are being served: first generation offspring of I0 • Ik, k>1 set of customers who arrive while members of Ik-1 are being served: k-th generation offspring of I0 • ancestral line of I0 • For us: I0 single customer, or set of customers arriving during some vacation • Vacation customer: arrive while server is on vacation • To each customer, C, corresponds a unique vacation customer, A, such that C is in ancestral line of A: A is ancestor of C.

Vacation queue: exhaustive service • Consider M/G/1 queue • Server takes a vacation (general distribution) when the system becomes idle • Upon return from vacation, if system idle new vacationotherwise serve until system idle: exhaustive service • No preemption • Theorem: Queue length decomposition N=NM/G/1 + NIwhere equality is in distribution, and N:= queue length at arbitrary epochNM/G/1 := queue length at arbitrary epoch in corresponding M/G/1NI := queue length at arbitrary epoch in vacation periodNM/G/1 and NI are independent r.v.

Vacation queue: Exhaustive service • Alternative formulation: • ψ(.) = p.g.f. stat distrib # cust random time • π(.) = p.g.f. idem in corresp M/G/1 queue • α(.) = p.g.f. # arrivals during vacation period = Vac(λ-λz) • π(z)=

Generalized vacations: assumptions • Server can take vacation at any time: vacation = server unavailable • Service time independent of sequence of vacation periods preceding that service time. • Order of service independent of service times. • Service non-preemptive • Rules that govern when server begins and ends vacations do not anticipate future jumps of the arrival process.

Generalized vacations: examples • Standard vacation model: vacation upon idling • N-policy: server waits until exactly N customers present before starting service, then work continues until system empty • M/G/1 with gated vacations: when server returns from vacation, he accepts only those customers waiting upon return, service of other customers deferred to next visit • Limited service: serve at most k customers • Polling model • Priority system

Generalized vacations • Decomposition property holds for any vacation system under assumptions stated. • Theorem: Consider a random (tagged) customer C. Let A the ancestor, I0 the set of vacation customers who arrived during the same vacation to which A arrived. Let I the ancestral line of I0, and let X the number of members of I present in system when C departs. X has p.g.f. • Proof: there may have been other customers in system at start of vacation. Due to LIFO these will remain in system, rest as proof last time

Generalized vacations • Assume that the number of customers that arrive during a vacation is independent of the number of customers present in the system when vacation began. • Theorem: Under this assumption • Proof: LIFO, p.g.f. of number of customers already present at beginning of vacation. Independence yields product.

Generalised vacations • Theorem: Queue length decomposition N=NM/G/1 + NIwhere equality is in distribution, and N:= queue length at arbitrary epochNM/G/1 := queue length at arbitrary epoch in corresponding M/G/1NI := queue length at arbitrary epoch in vacation periodNM/G/1 and NI are independent r.v. • Theorem: Work decomposition V=VM/G/1 + VIwhere equality is in distribution, and V:= work at arbitrary epochVM/G/1 := work at arbitrary epoch in corresponding M/G/1VI := work at arbitrary epoch in vacation periodVM/G/1 and VI are independent r.v.

Generalized vacations: Gated service • Gated service: At time tn server finds Xn customers. Gate closes. Server serves those Xn then takes vacation of length Vn and returns at time tn+1 • Recall RecursionMarkov chain; from recursion:

Generalized vacations: Gated service • Assume limiting distribution of Xn n ∞ exists, with pgf X(z), thenLet then

Generalized vacations: Gated service • Let M ∞ inresulting infinite product exists if ρ<1, and • Hence, if ρ<1

Convergence hence, indeed if ρ<1 • Observe • So that infinite product indeed converges

Interpretation: Branching processes (Wolff, sec 3-9) • Let Yr (i.i.d) be the first generation off-spring of individual r • Xn n-th generation off-spring of particular individual • Pgf n-th generation off-spring individual

Branching processes (Wolff, sec 3-9) • Xn+1 is sum of descendants of the j individuals of the first generation:

Generalized vacations: Gated service • Gated service: recall:Defineis p.g.f. number of the k-th generation offspringfirst previous gated period, second previous gated period

Generalized vacations • Server can take vacation at any time • Service time independent of sequence of vacation periods preceding that service time. • Order of service independent of service times. • Service non-preemptive • Rules that govern when server begins and ends vacations do not anticipate future jumps of the arrival process. • Number of customers that arrive during a vacation is independent of the number of customers present in the system when vacation began. • Theorem:

Polling models • N infinite buffer queues, Q1, …, QN • Service time distribution at queue j: Bj(.), mean βj, LST βj(.) • Poisson arrivals to queue j at rate λj • Single server in cyclic order • Switch over times: random variable Sj, mean σ j, LST σj(.) • Next week….. • Multi-type branching processes • and polling (Resing)

CS SOR: Polling models