Claims Analysis
Total Claims: 10
Claim 1
Independent Claim
168 words
A method for temporal allocation of a number of servers in a nonstationary finite server queueing system comprising the steps of: determining a probability distribution function of a number of busy servers in a nonstationary finite server queueing system as a function of time, based on input parameters representing servers and customers and interaction therebetween in said system, wherein one of said input parameters characterizes an arrival rate of customers to said finite server queueing system, wherein one of said input parameters characterizes a service time distribution for a customer arriving at said finite server queueing system, wherein said probability distribution is characterized by a mean function and a variance function, wherein said mean function and said variance function are based on said input parameters; determining a number of servers for allocation to said finite server queueing system based on said distribution and based on a target probability; and allocating the number of servers needed at a given time in said system as determined in said determining steps.
Claim 2
Independent Claim
168 words
A method for temporal allocation of a number of servers in a nonstationary finite server queueing system comprising the steps of: determining a probability distribution function of a number of busy servers in a nonstationary finite server queueing system as a function of time, based on input parameters representing servers and customers and interaction therebetween in said system, wherein one of said input parameters characterizes an arrival rate of customers to said finite server queueing system, wherein one of said input parameters characterizes a service time distribution for a customer arriving at said finite server queueing system, wherein said probability distribution is characterized by a mean function and a variance function, wherein said mean function and said variance function are based on said input parameters; determining a number of servers for allocation to said finite server queueing system based on said distribution and based on a target probability; and allocating the number of servers needed at a given time in said system as determined in said determining steps.
Claim 3
Dependent Claim
32 words
The method of claim 1 wherein said target probability is a delay probability characterizing the probability that a customer in said finite server queueing system will have to wait before receiving service.
Claim 4
Dependent Claim
59 words
The method of claim 1 wherein said mean function is function of time, m(t), determined according to ##EQU12## where G u c (t)≡1-G u (t)≡P(S(u)>t) with S(u) being the service time of a customer arriving at time u to said finite server queueing system and λ(u) is the arrival rate of said finite server queueing system at time u.
Claim 5
Dependent Claim
39 words
The method of claim 3 wherein said variance function is a function of time, v(t), determined according to v(t)≈z(t)m(t), where ##EQU13## where η>0, where A(t) counts the number of arrivals before time t and where Var is the variance.
Claim 6
Dependent Claim
25 words
The method of claim 1 or claim 2 or claim 3 wherein said service time distribution is an exponential function characterized by a time-varying mean.
Claim 7
Dependent Claim
28 words
The method of claim 1 or claim 3 wherein said arrival rate specifies a Poisson arrival process and wherein said variance function is equal to said mean function.
Claim 8
Dependent Claim
28 words
The method of claim 1 wherein said probability distribution function of said number of busy servers in said nonstationary infinite server queueing system characterized as a normal distribution..
Claim 9
Dependent Claim
24 words
The method of claim 1 wherein said number of servers for said finite server queueing system is adapted using a modified offered load approximation.
Claim 10
Dependent Claim
67 words
The method of claim 1 wherein said target probability, α, is adapted so that the target probability is replaced by a quantity, p D -1 (α), where p D -1 (α) is the inverse of p D (α) where ##EQU14## and where z.sub.α, for a normal distribution characterized by a mean of zero and a standard deviation of one, N(0,1), satisfies P(N(0,1)>z.sub.α)=α, where P(•) is the probability.