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Renewal Processes · Tutorial 561 of 994

Deterministic Interarrival Times

Learn how deterministic interarrivals produce equally spaced renewal epochs, how endpoint conventions change the count, and how to calculate the renewal function.

Intermediate 9 min read

What You'll Learn

  • Define deterministic interarrivals and renewal epochs.
  • Derive the inclusive renewal count using a floor function.
  • Derive the strict endpoint count and handle time zero separately.
  • Identify exactly when the two endpoint conventions differ.
  • Compute the renewal function from the deterministic count.
  • Check endpoint formulas with explicit epoch lists.

Equally Spaced Renewal Epochs

A renewal process records events separated by successive interarrival times. When every interarrival time is the same positive constant, the randomness in the event times disappears: the epochs are equally spaced. The main care needed is at the endpoints. Counting events at or before time \(t\) is not the same as counting events strictly before \(t\) when \(t\) itself is a renewal epoch, and time zero requires separate attention because the first renewal occurs after one interarrival time, not at time zero.

Work on a probability space \((\Omega,\mathcal{F},\mathbb{P})\). Let \((X_k)_{k\ge1}\) be the interarrival sequence, with each \(X_k\) taking values in \((0,\infty)\), and define the \(n\)th renewal epoch by \(S_n=\sum_{k=1}^n X_k\) for \(n\ge1\). The renewal count \(N(t)\), for continuous time \(t\ge0\), counts epochs at or before \(t\). It is a process with state space \(\{0,1,2,\ldots\}\). In this tutorial, assume there is a constant \(c>0\) such that \(\mathbb{P}(X_k=c)=1\) for every \(k\). No independence assumption is needed.

Definition: The inclusive renewal count is \(N(t)=\sum_{n\ge1}\mathbf{1}_{\{S_n\le t\}}\). The strict renewal count is \(N_{<}(t)=\sum_{n\ge1}\mathbf{1}_{\{S_n<t\}}\). Both counts begin at zero: no renewal has occurred at time \(0\).

Although each equality \(X_k=c\) holds almost surely, the countably many equalities hold simultaneously on an event of probability one: the intersection of countably many probability-one events has probability one. On that event, \(S_n=nc\) for every \(n\ge1\). Thus the pathwise calculation reduces to counting positive integers \(n\) that satisfy an endpoint inequality.

Counting at and before an Endpoint

Theorem: If \(X_k=c\) almost surely for every \(k\), where \(c>0\), then for every \(t\ge0\), $$ S_n=nc,\qquad N(t)=\left\lfloor\frac{t}{c}\right\rfloor,\qquad N_{<}(t)=\max\left\{0,\left\lceil\frac{t}{c}\right\rceil-1\right\} $$ almost surely. For \(t=0\), both counts are zero. For \(t>0\) with \(t/c\) a positive integer, the inclusive count exceeds the strict count by one; at all other positive times they are equal.

Proof. Intersect the probability-one events \(\{X_k=c\}\) over all \(k\ge1\). On this intersection, summing the first \(n\) interarrivals gives \(S_n=nc\). Fix any \(t\ge0\) and write \(x=t/c\), so \(x\ge0\). The inclusive count is the number of positive integers \(n\) satisfying \(n\le x\). If \(x=0\), there are no such integers and \(\lfloor x\rfloor=0\). If \(x>0\), the positive integers not exceeding \(x\) are \(1,\ldots,\lfloor x\rfloor\), so their number is \(\lfloor x\rfloor\), including zero when \(0<x<1\). Hence \(N(t)=\lfloor t/c\rfloor\).

For the strict count, we must count positive integers \(n<x\). At \(x=0\), that set is empty, so its size is zero. If \(0<x<1\), it is also empty; in this case \(\lceil x\rceil-1=0\). If \(x=m\) is a positive integer, the eligible integers are \(1,\ldots,m-1\), giving \(m-1=\lceil x\rceil-1\). If \(x>0\) is not an integer, write \(m=\lfloor x\rfloor\); then \(m<x<m+1\), so the eligible integers are \(1,\ldots,m\), with none when \(m=0\). Their number is \(m=\lceil x\rceil-1\). These cases give \(N_{<}(t)=\max\{0,\lceil t/c\rceil-1\}\) for all \(t\ge0\). Finally, at \(t=0\) both counts are zero. At a positive integer \(x=m\), the inclusive count is \(m\) and the strict count is \(m-1\). At positive noninteger \(x\), both counts equal \(\lfloor x\rfloor\). This proves the endpoint comparison. \(\square\)

The floor and ceiling functions encode different inequalities: \(\lfloor x\rfloor\) counts positive integers satisfying \(n\le x\), while \(\lceil x\rceil-1\) counts those satisfying \(n<x\) when \(x>0\). The maximum with zero in the strict formula makes the result valid at \(t=0\) as well. It also keeps the count nonnegative when \(0\le t<c\).

Worked Example: An Endpoint That Is a Renewal Epoch

Let every interarrival time equal \(c=2\), and count renewals at and before \(t=6\), then strictly before \(t=6\). The first epochs are \(S_1=2\), \(S_2=4\), \(S_3=6\), and \(S_4=8\). Since \(t/c=6/2=3\), the inclusive formula gives \(N(6)=\lfloor3\rfloor=3\). The strict formula gives \(N_{<}(6)=\max\{0,\lceil3\rceil-1\}=\max\{0,3-1\}=2\).

Check: The epochs at or before \(6\) are \(2,4,6\), which gives three; the epochs strictly before \(6\) are \(2,4\), which gives two. The difference is exactly the renewal at the positive boundary time \(6\).

Worked Example: A Time Between Renewal Epochs

Let \(c=\tfrac54\) and \(t=\tfrac{17}{8}\). The ratio is $$ \frac{t}{c}=\frac{17}{8}\cdot\frac45=\frac{68}{40}=\frac{17}{10}. $$ Since \(\tfrac{17}{10}\) lies strictly between \(1\) and \(2\), the inclusive count is \(N(t)=\lfloor\tfrac{17}{10}\rfloor=1\). The strict count is \(N_{<}(t)=\max\{0,\lceil\tfrac{17}{10}\rceil-1\}=\max\{0,2-1\}=1\).

Check: The first epoch is \(S_1=\tfrac54=\tfrac{10}{8}<\tfrac{17}{8}\). The second is \(S_2=\tfrac52=\tfrac{20}{8}>\tfrac{17}{8}\). Thus exactly one epoch satisfies either endpoint convention; no renewal occurs at \(t\).

The Renewal Function

The renewal function is the expected number of renewals by time \(t\). Under the inclusive convention used here, it is \(m(t)=\mathbb{E}[N(t)]\) for \(t\ge0\). In general, an expected count can vary because the renewal epochs are random. With deterministic interarrivals, the count is itself nonrandom, so its expectation equals its pathwise value.

Corollary: For deterministic interarrival time \(c>0\), the renewal function is $$ m(t)=\mathbb{E}[N(t)]=\left\lfloor\frac{t}{c}\right\rfloor,\qquad t\ge0. $$

Proof. The theorem gives \(N(t)=\lfloor t/c\rfloor\) almost surely. Since this is a finite constant for each fixed \(t\ge0\), its expectation is that same constant: \(\mathbb{E}[N(t)]=\lfloor t/c\rfloor\). At \(t=0\), the formula gives zero, in agreement with the fact that \(S_n=nc>0\) for every \(n\ge1\). \(\square\)

This renewal function is a step function. It stays constant between consecutive epochs and increases by one at each positive epoch \(c,2c,3c,\ldots\). Its value at each jump includes the renewal at that time; immediately before the jump, the strict count is one smaller. This is why the endpoint convention must be stated whenever a count or expected count is reported.

Worked Example: Computing the Renewal Function

Suppose \(c=\tfrac32\), and find the renewal function at \(t=\tfrac{15}{4}\). First compute the ratio: $$ \frac{t}{c}=\frac{15}{4}\cdot\frac23=\frac{30}{12}=\frac52. $$ Therefore \(m(\tfrac{15}{4})=\lfloor\tfrac52\rfloor=2\). In this deterministic process, this expectation is also the actual count on every path in the probability-one event where all interarrivals equal \(\tfrac32\).

Check: The first three epochs are \(S_1=\tfrac32=\tfrac64\), \(S_2=3=\tfrac{12}{4}\), and \(S_3=\tfrac92=\tfrac{18}{4}\). The first two are at or before \(\tfrac{15}{4}\), while the third is after it, so the count is two. At the boundary \(t=3\), the ratio is \(3/(\tfrac32)=2\), so \(m(3)=\lfloor2\rfloor=2\); strictly before \(3\), only the epoch \(\tfrac32\) is counted.

Worked Example: Time Zero and the First Renewal

Let \(c=4\). At time \(t=0\), the inclusive count is \(N(0)=\lfloor0/4\rfloor=0\), and the strict count is \(N_{<}(0)=\max\{0,\lceil0/4\rceil-1\}=\max\{0,-1\}=0\). At time \(t=4\), the inclusive count is \(N(4)=\lfloor4/4\rfloor=1\), while the strict count is \(N_{<}(4)=\max\{0,\lceil4/4\rceil-1\}=\max\{0,1-1\}=0\).

Check: The first renewal epoch is \(S_1=4\). There are no epochs before time zero, and there is no renewal at time zero. At time four, the inclusive convention counts \(S_1=4\), whereas the strict convention does not. The computed counts, zero and one inclusively at the two respective times, match the epoch definition.

Endpoint Pitfalls and Interpretation

Common mistake: using the strict formula without its zero-time case. A tempting formula is \(N_{<}(t)=\lceil t/c\rceil-1\). At \(t=0\), it gives \(\lceil0\rceil-1=0-1=-1\), which cannot be a renewal count and disagrees with the definition: no epoch \(S_n\), \(n\ge1\), is strictly before zero. The correction is $$ N_{<}(t)=\max\left\{0,\left\lceil\frac{t}{c}\right\rceil-1\right\},\qquad t\ge0. $$ Equivalently, one may use \(\lceil t/c\rceil-1\) only for \(t>0\), while stating separately that \(N_{<}(0)=0\).

A related overstatement is that the inclusive and strict counts differ whenever \(t/c\) is an integer. The integer zero is an exception: when \(t=0\), both counts are zero because renewals are indexed from \(n=1\), not from \(n=0\). They differ by one precisely when \(t/c\) is a positive integer. A further common error is to insert an initial renewal at time zero; doing so would change the count by one and would no longer match the definition \(S_n=\sum_{k=1}^nX_k\).

Deterministic interarrivals provide a direct reference case for renewal calculations: the epochs, counts, and expected count can all be checked from the same arithmetic sequence. The floor formula answers an inclusive counting question; the strict formula answers a different endpoint question. Neither formula should be used until the intended convention and the value \(t=0\) have been checked.

Check Your Understanding

For each question, state whether the count includes the endpoint and verify your answer by listing the relevant epochs.

  1. If \(c=3\) and \(t=9\), calculate \(N(t)\) and \(N_{<}(t)\). Explain why the counts differ.
  2. If \(c=2\) and \(t=5\), calculate both counts and identify the epochs that are counted.
  3. For an arbitrary \(c>0\), calculate \(N(0)\) and \(N_{<}(0)\) from their definitions, then check both formulas.
  4. For deterministic interarrival time \(c=\tfrac23\), find the renewal function at \(t=\tfrac53\).
  5. Why is \(\lceil t/c\rceil-1\) not a valid strict-count formula for every \(t\ge0\) unless it is modified?