I have application where I am listening on multiple sockets using select. If I start processing request that came in from Socket A and in the meanwhile if another request on socket B arrives then I want to know how long does socket B request had to wait before I could get it. Since this is a single threaded application I cannot spawn a new thread and go back to select to monitor again and instantly start processing request from socket B.
Is there a 'C' api available to get me this metric or is this just not possible to get?
There is no a straightforward way how to measure the interval between the 'data ready' time and 'data read' time because there is not any timestamp written together with the data. Moreover the situation is even more complex because a stream oriented socket may receive several data segments till select is closed and the it is not what interval should be measured.
If the application data processing is longer than packet processing in the kernel the you can do a reasonable measurement in following way:
print current time and some unique data id based on application protocol when select wakes up due to socket B data availability.
log any packet received for the socket B. You can use either a network traffic capture tool like wireshark or tcpdump. Or you can configure an iptables firewall rule (if it is running on linux) with target -j LOG.
Write a simple script/program that correlates the captured packets and the application log and subtract received and start processing time.
Of course the idea above does ignore the kernel processing time. If you really need exact time I have to introduce a new thread to your application.
Related
Let's say I have a car with different sensors: several cameras, LIDAR and so on, the data from this sensors are going to be send to some host over 5G network (omnetpp + inet + simu5g). For video it is like 5000 packets 1400 bytes each, for lidar 7500 packets 1240 bytes and so on. Each flow is encoded in UDP packets.
So in omnetpp module in handleMessage method I have two sentTo calls, each is scheduled "as soon as possible", i.e., with no delay - that corresponds to the idea of multiple parallel streaming. How does omnetpp handle situations, when it needs to send two different packets at the same time from the same module to the same module (some client, which receives sensor data streams)? Does it create some inner buffer on the sender or receiver side, therefore allowing really only one packet sending per handleMessage call or is it wrong? I want to optimize data transmission and play with packet sizes and maybe with sending intervals, so I want to know, how omnetpp handles multiple streaming at the same time, because if it actually buffers, maybe than it makes sense to form a single package from multiple streams, each such package will consist of a certain amount of data from each stream.
There is some confusion here that needs to be clarified first:
OMNeT++ is a discrete event simulator framework. An OMNeT++ model contains modules that communicate with each other, using OMNeT++ API calls like sendTo() and handleMessage(). Any call of the sendTo() method just queues the provided message into the future event queue (an internal, time ordered queue). So if you send more than one packet in a single handleMessage() method, they will be queued in that order. The packets will be delivered one by one to the requested destination modules when the requested simulation time is reached. So you can send as many packets as you wish and those packets will be delivered one by one to the destination's handleMessage() method. But beware! Even if the different packets will be delivered one by one sequentially in the program's logic, they can still be delivered simultaneously considering the simulation time. There are two time concepts here: real-time that describes the execution order of the code and simulation-time which describes the time passes from the point of the simulated system. That's why, while OMNeT++ is a single threaded application that runs each events sequentially it still can simulate infinite number of parallel running systems.
BUT:
You are not modeling directly with OMNeT++ modules, but rather using INET Framework which is a model directly created to simulate internet protocols and networks. INET's core entity is a node which is something that has network interface(s) (and queues belonging to them). Transmission between nodes are properly modeled and only a single packet can travel on an ethernet line at a time. Other packets must queue in the network interface queue and wait for an opportunity to be delivered from there.
This is actually the core of the problem for Time Sensitive Networks: given a lot of pre-defined data streams in a network, how the various packets interfere and affect each other and how they change the delay and jitter statistics of various streams at the destination, Plus, how you can configure the source and network gate scheduling to achieve some desired upper bounds on those statistics.
The INET master branch (to be released as INET 4.4) contains a lot TSN code, so I highly recommend to try to use it if you want to model in vehicle networks.
If you are not interested in the in-vehicle communication, bit rather want to stream some data over 5G, then TSN is not your interest, but you should NOT start to multiplex/demultiplex data streams at application level. The communication layers below your UDP application will fragment/defragment and queue the packets exactly how it is done in the real world. You will not gain anything by doing mux/demux at application layer.
I saw the socket option TCP_NODELAY, which is used to turn on or off the Nagle alorithm.
I checked what the Nagle algorithm is, and it seems similar to 'stop and wait'.
Can someone give me a clear difference between these two concepts?
In a stop and wait protocol, one
sends a message to the peer
waits for an ack for that message
sends the next message
(i.e. one cannot send a new message until the previous one has been acknowledged)
Nagle's algorithem as used in TCP is orthoginal to this concept. When the TCP application sends some data, the protocol buffers the data and waits a little while to see if there's more data to be sent instead of sending data to the peer immediately.
If the application has more data to send in this small timeframe, the protocol stack merges that data into the current buffer and can send it as one large message.
This concept could very well be applied to a stop and go protocol as well. (Note that TCP is not a stop and wait protocol)
The Nagle Algorithm is used to control whether the socket provider sends outgoing data immediately as-is at the cost of less efficient network transmissions (off), or if it buffers outgoing data so it can make more efficient network transmissions at the cost of speed (on).
Stop and Wait is a mechanism used to ensure the integrity of transmitted data, by making the sender send a frame of data and then wait for an acknowledgement from the receiver before sending another frame, thus ensuring frames are received in the same order in which they are sent.
These two features operate independently of each other.
I am acting as server which receives multiple requests from client in socket and handles in a thread.
Should i set any parameter in TCP level to set maximum number of requests a connection can handle simultaneously?
because in my server side ,if processing the request is slow i observe that other requests are queued up (client says request has been sent but i receive it late)
Kindly guide me
If it takes a long time to do the work and you want to handle multiple connections simultaneously, you have to change how you do things.
If you are actively using a lot of CPU during processing a long request, you'll need multiple threads. That's the only way to actually get more CPU time / second -- assuming you have multiple cores available.
If you are waiting on things like file IO, then you can instead use asynchronous processing to handle the requests on a single thread, but just handle a little piece at a time.
Setting a maximum number of TCP connections won't help you handle more processes more quickly. It will just reject connections and not even allow a first-come first-served type of behavior - it will just be random if a specific client ever gets through or not.
How come every site explains that in SSE a single connection stays opened between client and server "With SSE, a client sends a standard HTTP request asking for an event stream, and the server responds initially with a standard HTTP response and holds the connection open"
And then, when server decides it can send data to the client while what I am trying to implement SSE I see on fiddler requests being sent every couple of seconds
For me it feels like long polling and not a one single connection kept opened.
Moreover, It is not that the server decides to send data to the client and it sends it but it sends data only when the client sends next request
If i respond with "retry: 10000" even tough something has happened that the server wants to notify right now, will get to the client only on the next request (in 10 seconds from now) which for me does not really looks like connection that is kept opened and server sends data as soon as he wants to
Your server is closing the connection immediately. SSE has a built-in retry function for when the connection is lost, so what you are seeing is:
Client connects to server
Server myteriously dies
Client waits two seconds then auto-reconnects
Server myteriously dies
Client waits two seconds then auto-reconnects
...
To fix the server-side script, you want to go against everything your parents taught you about right and wrong, and deliberately create an infinite loop. So, it will end up looking something like this:
validate user, set up database connection, etc.
while(true){
get next bit of data
send it to client
flush
sleep 2 seconds
}
Where get next bit of data might be polling a DB table for new records since the last poll, or scan a file system directory for new files, etc.
Alternatively, if the server-side process is a long-running data analysis, your script might instead look like this:
validate user, set-up, etc.
while(true){
calculate next 1000 digits of pi
send them to client
flush
}
This assumes that the calculate line takes at least half a second to run; any more frequently and you will start to clog up the socket with lots of small packets of data for no benefit (the user won't notice that they are getting 10 updates/second instead of 2 updates/second).
I want to use a real time TCP connection, I have a streaming of data from server , and I receive it by a client, but this client is too slow to receive as fast as the sender is, so the server buffer the data until it's reach the destination, for example if I "produce" data at time t, and suppose that the client are 10 time slower, then the data produced at time t, will arrive at time 10t.
I want to make the server "drop" the data that can't reach the client at the present time, and send the new data which is expected to arrive at the time?
B.S : I know that UDP protocol do this, but I want to do this by TCP.
I've done this sort of thing in the past, and got reasonably good results. Here's how I did it:
1) On the sending side, use setsockopt(SOL_SOCKET, SO_SNDBUF) to make the server's TCP socket's send buffer as small as you can get away with (since you can't drop data once it's already in the socket's send buffer, you want to keep as little data there as possible)
2) On the sending side, never proactively send() any outgoing data into the socket at all. Instead, write a function (we'll call it DumpCurrentStateToBuffer()) that writes the "current state" bytes (that you want to send to the client) into an in-memory buffer.
3) When the client's socket select()'s (or poll()'s, or whatever mechanism you use) as ready-for-write, call DumpCurrentStateToBuffer() to create a memory-buffer of bytes that are to be sent to the client. Now send that data to the client (if you're using blocking I/O you can do it synchronously, at the cost of potentially stalling your server until the data can be sent; OTOH if you're using non-blocking I/O, you may need to keep the memory-buffer and your current sent-bytes index into the buffer around as state variables, so you can keep sending more sub-chunks of the memory buffer over time, whenever the socket indicates that it can receive more bytes)
4) Once the memory-buffer's contents have been fully sent, you can free the memory buffer, and then wait for the socket to select as ready-for-write again; when it does, goto (3).
This technique doesn't solve all of TCP's non-real-time issues; for example, a dropped TCP packet will still have to be resent to the client. What it does do is guarantee that the client-to-server data backlog will never be more than one or two "states" long, because you never generate any new data unless/until there is at least some room in the socket's output buffer.