Seamless offloading of web app computations from mobile device to edge clouds

https://blog.acolyer.org/2020/01/31/web-worker-migration/

by godelmachine • 6 years ago

60 19 6 years ago

blog.acolyer.org

janci• 6 years ago

Interesting idea, but why they are offloading heavy computation to the less powerful device? I don't see any device around me that is more powerful than my smartphone. Except for the computer, for which it makes sense to run the computation at the first place.

iudqnolq• 6 years ago

According to them they can support 2x the objects with acceptable perf on the server compared to the client.

It appears you intuition is wrong in this case.

trevyn• 6 years ago

Thermals too, keeps your phone from getting hot?

colordrops• 6 years ago

It seems to me they are suggesting adding more powerful processors to edge devices such as routers if this turns out to be a useful technique.

homero• 6 years ago

With so many WiFi devices it would be very innovative to have my router expose a computation API. Nothing real time but why not move Fitbit data processing to the router and save my battery. Web workers are a great API. Upload the script then get the results later or upload directly.

dspillett• 6 years ago

Those other devices aren't running on battery power, which could be a significant factor.

Also, there are many less powerful phones out there which may see greater benefit.

And the "edge device" presumably doesn't have to be the absolute edge, perhaps another part of the edge infrastructure (in my home this could be the server that sits directly behind the wireless AP topologically speaking.

And some APs do have significant computing power, they may not be taking about the cheapest router in existence provided by a penny-pinching ISP.

NohatCoder• 6 years ago

Seems like a complicated process for maybe getting slightly more compute power. Phones are plenty fast these days, processing power is rarely a major limiting factor.

xf00• 6 years ago

processing power is rarely a major limiting factor.

Autonomy is. I could see compute clouds like this being offered at the OS level rather than browser, along with a claim for multiple days charge cycles, or slashed device weight/thickness. However, it would likely only work well for common and predictable computing tasks. And it would further separate users from hardware.

jbverschoor• 6 years ago

Ahhh the first step of the cycle. We're going back to on premise computing.

DSingularity• 6 years ago

It really is a pendulum isn’t it? Is it driven by cost dynamics? Computers become expensive and incentivize sharing (mainframes, cloud, sevens, ...). Prices come down — either because workload become more complex or hardware becomes cheaper — and the incentives for exclusive ownership come back.

_davebennett• 6 years ago

What exactly are we doing on IOT devices that we require so much computing power for? Phones are already strong enough and everything else just captures audio/video.

ovi256• 6 years ago

Deep learning can be used for many interesting things, like computer vision applications.

Even visual odometry and SLAM, necessary for AR, can be solved through DL.

I, for one, can't wait to have something in a raspberry Pi form and power factor that can run a big deep CNN at 30fps.

That opens the way to a lot of neat gadgets that can be summarized as "computers that can see":

https://www.ben-evans.com/benedictevans/2019/7/19/computers-...

Frost1x• 6 years ago

Phones come packed with quite a few sensors and communication capabilities (multiple cameras with parallax and varied optical parameters, microphones, accelerometers, GPS, depth sensors sometimes, etc.). There has been a lot of focus over the years to do useful things with commodity sensors since they're so pervasive.

There are a lot of very sophisticated and computationally intensive algorithms out there that can use specific sensors or combinations of these sensors to infer other useful things.

Now take into account you may have multiple phones collecting data distributed in some spatiotemporal fashion, you can really get fancy with some aspects and increase accuracy of some of these algorithms.

Instead of hand waving, one novel example I've worked with is using video feeds from streams or rivers to perform LSPIV (large scale particle velocemetry) analysis to estimate instantaneous discharge rates of rivers. There are at least 6-7 other use cases for projects I've been involved with that could leverage these resources in interesting ways--some use phones, some use other sensors.

sp332• 6 years ago

Some phones are strong. Most are cheap and crappy.

dangerface• 6 years ago

you’ve got mobile devices without the computing power needed to deliver a great experience

I can play call of duty on my mobile with graphics better than xbox 360, what are you on about?

cloud computing that has all the needed power that’s too far away

The issue is mobile bandwidth not just latency.

Edge servers are the middle ground

More expensive, less powerful and scales worse than the mobile, while also increasing latency and bandwidth the mobile just doesn't have.

Wifi is a bigger drain on battery than cpu so it will drain phones batteries faster not slower, this is truly a compromise thats the worst of both worlds.

dalore• 6 years ago

Wifi is not a bigger drain than cpu when you're playing CoD on your mobile. Your smart phone now has multiple cpu's and would have a GPU. When you're doing something intensive like CoD it will fire up that GPU and suck up power.

Wifi power used will vary with a few factors, how far you away from the station, how many other wifi signals, etc.

In addition a big bright screen uses a lot more power than wifi. But that would be used either way so not part of the comparison.

folex2• 6 years ago

Agreed. Also, it looks to me that paper's idea intended to be used for batch (or, at least, batchable) computations, where you submit data, and then retrieve the result.

In that case, Wi-Fi isn't used intensively, only for data transmission, meaning it could be idle during computation. So the power savings could be relatively big.

jotm• 6 years ago

I can play call of duty on my mobile with graphics better than xbox 360

I noticed graphics on smartphones are pretty damn great (I don't play mobile games) these days.

So, the Snapdragon 855+ has a GPU that does 1030 GFLOPS, which is very close to the XBox One (1300 GFLOPS), at a fraction of the power usage. Amazing!

folex2• 6 years ago

There's a similar paper from 2018 https://www.researchgate.net/publication/325255736_Decentral...

Seamless offloading of web app computations from mobile device to edge clouds

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