> 
> As Thomas said, maybe the simplest thing would be to use the ROOT THttpServer. Honestly, I do 
> not think that ROOT was ever meant to act as an online monitor due to its wacky memory 
> management and abysmal multithread support. In other words, I think that by using ROOT we would 
> inevitably lose some performance.
>

Yes. The previous data analysis frameworks - PAW/PAW++/CERNlib (CERN), NOVA (TRIUMF) - certainly had
support for online monitoring. In CERNlib/PAW the histograms were stored in shared memory,
the analyzer running in the background was filling them, the PAW/PAW++ display was displaying
them "live". I was very surprised to find this function removed/not implemented in ROOT, given
that the same people were behind both projects (Rene Brun & co).

We tried to roll our own implementation of this in ROOTANA/ROODY, with mixed success.

I am glad the JSROOT project finally gained traction and web based "I can see the data" is now
available in ROOT.

> 
> Perhaps there are better ways of achieving the same goal. For example, I was leaning towards a 
> plotly.js based approach where 
>

There are many web/javascript graphics libraries out there, all have the weak spot - how do you
get your data into them?

Going forward, I see us standardizing on JSROOT: https://root.cern.ch/js/

>
> ... send them to the client through the MJSONRPC mechanism ...
>

I am not sure JSROOT have any support for interacting from the web page to the back-end analyzer. Perhaps
we can use the MIDAS MJSONRPC library for this. Hmm... (Note that the ROOT HTTP server is a derivative
of the mongoose web server library, which we use in mhttpd, so I already know how to work it)

>
> I would encode a series of vectors in base64 strings (for better transmission performance)
>

We looked into this when deciding on the data encoding for the midas history data. There is a tradeoff
between network use and cpu use - to save on the network, you try to reduce the data size by using
compressed binary data - to save on the CPU you try to minimize data encoding.

For history data, we gave up on binary json (extra decoding needed), gave up on text json (extra decoding 
needed), gave up on compression (extra cpu use for decompression) and use javascript native binary processing
("arraybuffer").

Our thinking is that network bandwidth is usually quite big and is getting bigger, but cpu resource is limited
and is expensive. (mobile devices seems to be stuck with ~2 GHz CPUs; cpu use means battery use and
battery capacity is limited, not improving quickly)

> 
> So ROOT it is. I will use the ROOTANA javascript display as a reference. Do you happen to know 
> who wrote that part? 
> 

Yes. See "Contact" at https://root.cern.ch/js/

>
> In that example, you have some "static" histograms that you keep always in memory, while in our 
> case the number of channels is so big that we have to dynamically generate the histograms only 
> when needed (when the user select a single channel).
> 

This requires interaction with the analyzer, requires some kind of RPC mechanism. I am now curious what jsroot 
have, also it would not be too hard to add the mjsonrpc library to rootana. Cooperation from ROOT multithreading
is not required: I can queue the RPC requests in a separate (thread safe, non-ROOT) buffer, then process
them in the ROOT main event loop (this is how the ROOTANA histogram server worked in the days when
ROOT had no multithread support at all).

K.O.