Estimate the number of subscribers that can be supported by a cell with 400 radio channels.
Assume each subscriber generates on an average 2.5 calls per hour with call holding time of
120 seconds. Assume 2% blocking.
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I am working on creating a spreadsheet template for a video observation tool that my organization will use. Specifically, we will watch ~20-minute long videos, and record the rate (occurrences per minute) of certain behaviors within subsections of the video. For example, "in the clip from 2:06 to 4:30, the speaker asked the audience an average of 2.5 questions per minute."
I think it would be easiest for users to denote individual clips by providing start and end times (e.g. Start: 22:40 End: 23:02). Users should be able to input a count of certain occurrences, and then the spreadsheet will divide that number by the time elapsed and calculate a rate per minute. That is to say, if the speaker asked 8 questions between the timestamps 22:40 and 24:20, the spreadsheet should return a value of 8/(1.67 minutes) = 4.8 questions per minute.
I'm having trouble figuring out a way to enter time values in Google Sheets without it treating them as actual times in a 24-hour day. For example, 22:40 shouldn't refer to 00:22:40am nor to 10:40pm; I just mean 22 minutes and 40 seconds. I guess in theory, I would need it to treat the End Time as x-many minutes (or fractions of a minute) after a given Start Time, so it would need to calculate the total number of seconds elapsed between two mm:ss values and divide that sum by 60 to get the time elapsed in minutes. Then, I could simply divide the count of occurrences (e.g. 8 questions) by that number (1.67 minutes), and get my answer.
Does anyone have any tips about how this could be done? Thank you so much for your help!!
Current State:
Start Time: 22:40
End Time: 24:20
Questions Asked: 8
When I enter =8/(End Time - Start Time), I get 0:00 for some reason. I want it to return 4.8.
Format those durations as Format > Number > Duration. Enter durations complete with elapsed hours, minutes and seconds, as in 0:22:40 and 0:24:20.
You can then calculate events per minute like this:
=E2 / 24 / 60 / (T2 - S2)
...where E2 is the total number of events, S2 is the start moment, and T2 is the end moment.
Format the formula cell as Format > Number > Number.
See this answer for an explanation of how date and time values work in spreadsheets.
I have question about the effects of multiple users.
I assume that the scheduler only allocates the frequency elements per the number of users and ignore multiuser interference. Ex) 1 user : can using 100 RBs / 2 user : can using 50 RBs / 3 user : can using 33 RBs ...
and for example, If one user needs to transmit 100000 bits and in 1 transmission time interval (TTI), 100 bits can be transmitted per 1 RB. (5000 bits per 50 RBs / 10000 bits per 100 RBs)
In this example, I assumed two cases as below
Case 1) If user can use 100 RBs, the user can transmit in 10 TTI (only 1 user exists)
Case 2) If user can use only 50 RBs, the user can transmits in 20 TTI ( 2 users exist )
In both cases, in my opinion three conclusions are expected.
A) Their error will be same since their total payload traffic is equal to 100000 bits
B) the performance block error rate (BLER) of case 1 is worse than case 2. Even though TTI is half of case 2 but the number of RBs per transmission is larger, therefore retransmission will occurs more frequently in case 1.
C) the performance block error rate (BLER) of case 2 is worse than case 1. Even though the number of RBs are half of case 1 but in case 2 should transmits a data during longer TTI thus, retransmission will occurs more frequently in case 2.
What conclusion can be derived? I have searched many papers and standards but i could not have found clear conclusion.
Thank you for reading a long question
have a nice day :)
I am looking for a solution because the sth-channel is full.
I am troubled with calculating the appropriate capacity of channel capacity.
This document has the following description.
In order to calculate the appropriate capacity, just have in consideration the following parameters:
・The amount of events to be put into the channel by the sources per unit time (let's say 1 minute).
・The amount of events to be gotten from the channel by the sinks per unit time.
・An estimation of the amount of events that could not be processed per unit time, and thus to be reinjected into the channel (see next section).
How can I check the values of these parameters?
How can I check the values of these parameters?
You can't just check these parameters. They depend on your application.
What they are saying is that you should have a size which is large enough so the generator doesn't get stuck. This may not be possible in your application.
Say your generator receives one event per second and it takes 2 seconds for a receiver to manage that event. Now lets assume you have 3 receivers. In 1 second, you can manage to process 0.5 events per receiver. You have 3 receivers, so your receivers, together, are capable of processing 0.5 × 3 = 1.5 events, which is more than what you get as input. Your capacity can be 1 or 2, using 2 will greatly increase your chances that you do not get blocked.
Let's review another example:
Your generator wants to pushes 1,000 events per second
Your receivers take 3 seconds to process one event
You would need 1,000 x 3 = 3,000 receivers (3,000 goroutines that can run at full speed in parallel...)
In this example, the total number of receivers is so large that you have to either break up your code to work on multiple computers or optimize your receiver code so it can process the data in an amount of time that makes sense. Say you have 50 processors, your receivers will get 1,000 events per second, all 50 can run at full speed, you need one receiver to do its work in:
50 / 1000 = 0.05 seconds
Now let's assume that in most cases your goroutines take 0.02 but once in a while one will take 1 second. That means your goroutines can get a little behind. In that case your capacity (so the generator doesn't get blocked) should be a little over 1,000. Again, it will depend on how many of the routines get slowed down, etc. In this last example, a run is 0.02 seconds so to process 1,000 events it usually takes 0.02 seconds. If you can send those 1,000 event over the 1 second period, you may not even need the 50 goroutines and could have a smaller capacity. On the other hand, if you have big bursts where you may end up sending many (say 500) events all at ones, then more goroutines and a larger capacity is important to not get blocked.
If you are writing a bosun alert which is based of a percentage error rate for requests handled by your system, how do you write it in such a way that it handles periods of low traffic.
For example:
If I have an alert which looks back over the last 5 minutes and works out the error rate for requests
$errorRate = $numberErr/$numberReq and then triggers an alarm if the errorRate exceeds a predefined threshold crit = $errorRate > 0.05 this can work quite well so long as every 5 minute period had a sufficiently large number of requests ($numberReq).
If the number of requests in a 5 minute period was 10,000 then 501 errors would be required to trigger an alarm. However if the number of requests in a 5 minute period was 100 then only 5 errors would be required to trigger an alarm.
How can I write an alert which handles periods where the number of requests are so low that a small number of errors will equate to a large error rate. I had considered a sliding window of time, rather than a fixed 5 minute period, where the window would increase in size until the number of requests was high enough to give some confidence in the alarm. e.g. increase the time period until the number of requests is 10,000.
I can't find a way to achieve this in bosun, and I don't want to commit to a larger period of time for my alerts because the traffic rate varies so much. A longer period during peak traffic could result in an actual error causing a much larger impact.
I generally pair any percentage and/or historical based alerts with a static threshold.
For example: crit = numberErr > 100 && $errorRate > 0.05. That way the percent part doesn't matter unless the number of errors have also crossed some threshold because the entire statement won't be true.
I want to use Google Analytics to track my iOS application hits.
I've read Google Analytics Collection Limits and Quotas article. It says
Each property starts with 60 hits that are replenished at a rate of 1 hit every 2 seconds. Applies to All hits except for ecommerce (item or transaction)
It is not quite clear for me what "1 hit every 2 seconds" means.
Here is what i think:
1 hit every 2 seconds = 0.5 hits per second
frequency (hits per second) = number of hits / time interval (seconds)
So my question is:
What time interval does Google Analytics use to calculate hits frequency?
Is it time elapsed from session start? Or is it a time for current day? Or is it calculated every 2 seconds?
I believe this rate limiting happens on the client (via the SDK) and not on the server. Server side limits exist, but they apply equally to all clients (so not iOS-specific).
The 60 hits + 1 per 2 seconds rule means that when you instantiate the tracker object in your app, it starts out with a 60 hit quota, and it adds 1 additional hit every 2 seconds.
As an example, if you instantiated the tracker, and the user didn't do anything for 10 seconds, you'd have 65 hits left in your quota. If the user then performed 10 actions within the next 10 seconds, you'd be back to 60 hits left in your quota. Does that make sense?
So to answer your ultimate question, the it's not about time interval, it's about when the clock starts, and that happens when the tracker object is created on the client.