When testing my website performance with webpagetest I get excellent results, with my pages being fully loaded under 1s, taking aound 0.6s.
Those tests are being made using my user base location (Brazil - São Paulo), so it may be similar to their result.
But when I do check Google Search Console for the speed result it shows around 1.4s, which is too far away from the results I do have in here.
What I am in doubt is:
Is it because the speed result in Goolge Search Console is still experimental?
Or is there something wrong that I am doing on those tests?
The webpage I am testing is:
https://www.99contratos.com.br/contrato-locacao-residencial.php
And a result I get from webpagetest can be seen clicking the link bellow:
Results
I do appreciate all the help / tips / explanations.
Kind Regards
The data in search console is 'real world data' based on visitor experiences.
It is more accurate than synthetic tests.
What you need to look at is your break-down, not just the speeds. If you have a small percentage in the "red" and "orange" (less than 20%) then you do not need to worry, those users probably have super cheap phones and or a poor 3G connection. You cannot do much about that.
What you need to think about also is where people are accessing your site from. If they are all from abroad then you need a CDN as close to them as possible as latency will ruin your site load speed (so look at your visitor stats in Google Analytics).
Look at what devices your users are accessing your site on, if they all have super cheap android phones then expect higher load times while they process the page (hard to determine).
Just to reassure you - your page scores 98 / 100 for me using Developer Tools Audit, which considering I am in the UK is plenty quick enough.
Couple of suggestions to improve the speed
The main thing you haven't done is inline your critical CSS.
This means that your 'above the fold' content can display the second all the HTML has loaded. By not having to wait for the CSS to load from a separate request this can really speed your page up on FCP and FMP, especially if someone is on a high latency connection.
Also your number of requests could be reduced by using inline SVGs for your icons, making your page smaller and reducing network requests (which yet again helps with round-trip latency as up to 8 requests can be completed at a time, so with 26 requests you have at least 5 round trips to the server (1 (html), 8, 8, 8, 1) ).
The speed (in seconds, not scores) displayed on the speed test results is very influential on the test server region. The closer the test server region is, the faster the loading time will be.
Example of speed test results for your page, using servers from Australia - Sydney, Canada - Vancouver, and your base location: Brazil - São Paulo, using GTmetrix.
Australia - Sydney (3,2s)
Canada - Vancouver (1,9s)
Brazil - São Paulo (0,8s)
So, it can be concluded LARGE POSSIBLE test server region used by Google Search Console is far from your base location.
By the way, when I open your page from Indonesia, it only takes about 0.9-1.2 seconds. So, congratulations, your page is fast!
I've got over 100 hours of audio associated with video interviews for a documentary that need to be transcribed to text - hopefully with some kind of timecode markers every 30 seconds or so so the video can easily be matched up to the text in the edit suite.
The files are BWAV 24 bit 96khz and WAV 16 bit 48khz and last anywhere from 20 minutes to 2 hours.
What kind of resources need to be setup in a VM to do this kind of activity? I suspect it will be rather compute intensive so the VM might need 32 cores and a fair amount of memory, but there is no need for realtime response so it is ok if priorities are low and it takes several hours to process a file. My budget is miniscule - $300 is about the most we can afford for all the files (which is one reason we aren't sending these files out to a transcription service at $75+/hour).
I've already got a Cloud Platform account but have never used it. There is no point in my floundering around if someone has already done something similar and can give me some help.
I would like to track a large number of beacons (~500) at once within a 50-100 m radius via an app on an iPhone (5s). I've had a look at the spec and online and I can't see if there is any limit on the number of beacons you can track at once using BLE. Does anyone know if there is limitation on the number of beacons you can track exists or if an iPhone 5s would be up to the task of tracking that many beacons?
You used the word track, but iOS has two different methods: monitoring and ranging.
You can set a maximum of 20 regions to monitor. (Found in documentation for the startMonitoringForRegion: method.) Region limits mostly come into play if your app is in the background. The OS will alert your app when you enter or leave a region that you're monitoring (give or take a few minutes). The OS will even launch your app just to let it know what happened (although only for a short time).
The other method is ranging, which is to find all the beacons within the Bluetooth range of the device (typically around 100 feet give or take). If your beacons are spread out over 100 miles, then you probably won't run into any practical limit here. I have not found any documentation for this, and I have only four beacons that I'm testing with, and four at a time works.
Here's one way to handle your situation. Make all your 500 beacons use the same UUID, and make a beacon region using initWithProximityUUID:identifier: method. (Identifier is just for you -- it doesn't affect anything). Starting monitoring for that beacon region. That way, your app will be notified whenever one of your 500 beacons are found (give or take a few minutes). Once notified, you can use startRangingBeaconsInRegion: to find all the beacons around that area, then use the major and minor values to figure out which beacons the user is near.
I'll add to Tim Tisdall's answer, which sets out the right framework. I can't speak to the specific capabilities of the iPhone 5s, or iOS in general, but I don't see any reason why it wouldn't return every ADV_IND packet (i.e. beacon transmission) that it receives.
The question is, will the 500 beacons be able to transmit their ADV_IND packets without collisions?
It takes about 0.128ms to transmit an ADV_IND packet. The time between advertising transmissions is configurable between 20ms and 10240ms (at intervals of 0.625ms), so the probability of collisions depends on the configuration of the beacons.
Based on the Poisson distribution, the probability of a collision for any given ADV_IND packet is 1-exp(-2*N*(0.128/AI)), where N is the number of beacons within range, AI is the time in milliseconds of the advertising interval (assuming all the beacons are configured the same), and the 0.128 is the time in milliseconds it takes to send the ADV_IND packet. (See http://www3.cs.stonybrook.edu/~jgao/CSE590-fall09/aloha-analysis.pdf if you want an explanation.)
For 500 beacons with the maximum advertising interval of about 10 seconds, there will be a collision about once every 81 packets (or about 6 out of 500). If you're willing to wait for a couple intervals (i.e. 30 seconds), there's a good chance you'll be able to receive all 500 ADV_IND packets.
On the other hand, if the advertising interval is smaller, say 500ms, you'll have a collision about 23% of the time (or 113 out of 500). You'd have to wait for several more intervals to improve the probability that you'd see the broadcasts from all the beacons.
The other way to look at it is that the more beacons you have, the longer you have to wait to make sure you receive all their packets. (The math to calculate the delay to receive the packets with a certain probability from the number of beacons and the advertising interval is too much for me today.)
One caveat: if you want to connect to these beacons, as opposed to just receiving the ADV_IND packet, that requires an exchange of two more packets on the advertising channels, and the probability of a collision in the advertising channels goes up a bit.
If I am reading your question right, you want to put all 500 iBeacons within 100 meters of each other, meaning their transmissions will overlap. You will probably run into radio congestion problems long before you run into any limitations of iOS7 or your phone.
I have successfully tested 20 iBeacons in close proximity without problems, but 500 iBeacons is an extreme density. this discussion on the hardware issue suggests you may run into trouble.
At a minimum, the collisions of the transmissions of 500 iBEacons will make it take longer for your iOS device to see each iBeacon. Normally, iOS7 provides a ranging update once per second for each iOS device, but you may find that you get updates much less often. It all depends on your application whether or not less frequent updates are acceptable.
Even if delays are acceptable, I would absolutely test this before counting on it working at all. Unfortunately, that means getting your hands on lots of iBeacons.
I don't agree. It is true that ble beacons only transmit advertising data, but the transmission of such data last about 3ms (considering three advertising channels).
Having 500 beacons, WITHOUT considering any collision, the scanner will takes 1.5s to see them all.
But, if all beacons are configured in same way (same advertising interval) it is inevitable to have collisions which lead to have undiscovered beacons. Even if the advertising interval is different between beacons collisions occur. To avoid collision probability one should use longer advertising interval, but this lead to longer discovery latency.
This reasoning is very raw, it doesn't take care of many effects, but is just an order of magnitude calculation.
By the way, the question is not easy, there are many parameters which play role, some are known some are unknown. But I'm working with ble since one year about and, to me, 500 is a huge number and there is the possibility that you don't see the majority of nodes because of collisions.
I was doing some research into iBeacon's because of this question (I had no idea what it was about).
It seems that on the "beacon" side of things all that happens is general advertising packets are sent out. It's similar to how a device advertises that you can connect to it. However, you don't actually connect to iBeacon's, it just reads those advertising packets. There's no built-in limitation on how many advertising packets a device can receive.
So, it wouldn't surprise me if 500 iBeacon's would run with no issues. The advertising packets are small and are spaced out (time wise, they are repeated every X ms). There's no communication going from the phone to the iBeacon, the phone is simply receiving the packets it hears. If there's interference on one packet it'll likely manage to get the next one.
I am currently working on a project involving a Lego Mindstorms kit. The brick is the NXT and I was curious about the bluetooth ping rates.
I ran a test of 100 pings on it and got some interesting results. The latencies seemed to fall into bands. I increased to 10,000 pings and it highlighted this trend even more clearly. Does anyone know what could cause this to happen?
In case it is relevant, the distance between the sender and receiver was about 3 metres.
Few reasons :
Buffering and internal timers to flush buffers can cause it.
Also depends on the ping intervals (i.e. time between subsequent pings), as the link might go to power save mode during inactivity and it will take a fine time to come back up.
Size of the ping packets
What bluetooth profile is used here ?
I am working on a system with laser trip detectors(if something breaks the laser path I get a one on the output of the laser receiver).
I have many of these trip detectors and I want to detect if one is malfunctioning, but I do not know how to go about doing this. The lasers should not trip all that often..maybe a few times a day.
A typical case would be that the laser gets tripped for a .5-2 seconds, or brief intermittent tripping for a short time period, and possibly again after that(within 2-10 seconds)...
Are there any good ways to check the sensor is malfunctioning using a good statistical methodology?
You could just create a "profile" which includes the avg/mean/min/max of how often each sensor is tripped/how long it is tripped/how long is the time between a trip and the next trip etc. for example by using the data of some period of time like the last week/month or similar...
THEN you can compare the current state of a sensor to its profile... when the deviation is "big enough" you can assume an exceptional situation/perhaps a malfunction... the hardest part is to adjust the threshold for the deviation from the profile which in turn if hit triggers for example "malfunction handling"...