I am creating a web application having a login page , where number of users can tries to login at same time. so here I need to handle number of requests at a time.
I know this is already implemented for number of popular sites like G talk.
So I have some questions in my mind.
"How many requests can a port handle at a time ?"
How many sockets can I(server) create ? is there any limitations?
For e.g . As we know when we implement client server communication using Socket programming(TCP), we pass 'a port number(unreserved port number)to server for creating a socket .
So I mean to say if 100000 requests came at a single time then what will be approach of port to these all requests.
Is he manitains some queue for all these requests , or he just accepts number of requests as per his limit? if yes what is handling request limit size of port ?
Summary:
I want to know how server serves multiple requests simultaneously?I don't know any thing about it. I know we are connection to a server via its ip address and port number that's it.
So I thought there is only one port and many request come to that port only via different clients so how server manages all the requests?
This is all I want to know. If you explain this concept in detail it would be very helpful. Thanks any way.
A port doesn't handle requests, it receives packets. Depending on the implementation of the server this packets may be handled by one or more processes / threads, so this is unlimited theoretically. But you'll always be limited by bandwith and processing performance.
If lots of packets arrive at one port and cannot be handled in a timely manner they will be buffered (by the server, the operating system or hardware). If those buffers are full, the congestion maybe handled by network components (routers, switches) and the protocols the network traffic is based on. TCP for example has some methods to avoid or control congestion: http://en.wikipedia.org/wiki/Transmission_Control_Protocol#Congestion_control
This is typically configured in the application/web server you are using. How you limit the number of concurrent requests is by limiting the number of parallel worker threads you allow the server to spawn to serve requests. If more requests come in than there are available threads to handle them, they will start to queue up. This is the second thing you typically configure, the socket back-log size. When the back-log is full, the server will start responding with "connection refused" when new requests come in.
Then you'll probably be restricted by number of File Descriptors your os supports (in case of *nix) or the number of simultaneous connections your webserver supports. The OS maximum on my machine seems to be 75000.
100,000 concurrent connections should be easily possible in Java if you use something like Netty.
You need to be able to:
Accept incoming connections fast enough. The NIO framework helps enormously here, which is what Netty uses internally. There is a smallish queue for incoming requests, so you need to be able to handle these faster than the queue can fill up.
Create connections for each client (this implies some memory overhead for things like connection info, buffers etc.) - you may need to tweak your VM settings to have enough free memory for all the connections
See this article from 2009 where they discuss achieving 100,000 concurrent connections with about 20% CPU usage on a quad-core server.
Related
I've set up sockets for communication between a server and client and have threads running on the server for multiple client connections. Furthermore I'm now sending byte arrays between server and client for data however I'm thinking of implementing cyclic barriers to make the server wait for a specific number of clients to connect before a different message is sent to each client.
This communication and waiting will need to be ongoing for example once this threshold of client connections is made and the message sent out, the server should now wait again for a message to come back from each client, probably a different message. This should continue for a few iterations at least, I'm wondering if I implement cyclic barriers for this process would i go be finding the best solution to this process?
Is this the intended use of cyclic barriers or would there be a better alternative to my idea?
To keep it simple, I intend to wait for 2 clients to connect. There will also be timeout conditions enforced to deal with possible failure.
I've been looking into making a simple Sockets-based game in Java, and read in multiple places that client sockets are destroyed after a single exchange. Is this good practice for continued connections? The server needs to maintain a connection with a client (i.e. not using socket.accept() every time it wants to tell a client about something), but can't wait every time for the client's response. I already have the server/client running in separate threads, but won't destroying the socket after every exchange mean re-acquiring (or failing to re-acquire) a connection to that client? I've seen so many conflicting websites about sockets in Java and how they should be implemented.
There's no hard and fast rules, but it does depend slightly on what data rates you want to achieve.
For example, YouTube is a streaming video service, but the video data is delivered by means of the client using https to fetch batches of video data. Inefficient, yes, but very easy to program for. There's lots of reasons to use https for an application like YouTube (firewalls, etc), but ultimate power saving and network performance were not one of them. The "proper" way would be to use a protocol like RTP which uses UDP to deliver small packets of data which can then be rearranged into order, you also have to deal with missing frames at the CODEC level, etc. Much less network traffic, friendly to bandwidth constrained network links, but significantly more difficult to deal with traversing across firewalls, in client software, etc.
So if your game is sending modest amounts of data, the only thing wrong with setting up and tearing down a whole socket connection for every message is the nagging feeling you yourself will have that it is somehow not the most efficient solution.
Though it sounds like you have a conflict between the need to communicate between client / server and a need to process something else whilst waiting for the communication to complete. Here you're getting into asynchronous I/O territory. To make that easy i strongly suggest you take a look at ZeroMQ - that will make everything a whole lot simpler.
and read in multiple places that client sockets are destroyed after a single exchange.
Only in the places where that actually happens. There are numerous contexts where it doesn't, the outstanding example being HTTP, where every effort is made to reuse connections.
Is this good practice for continued connections?
The question is a contradiction in terms. A continued connection is a connection that isn't closed. A closed connection can't be continued.
The server needs to maintain a connection with a client (i.e. not using socket.accept() every time it wants to tell a client about something), but can't wait every time for the client's response.
The word you are groping for here is 'session'.
I already have the server/client running in separate threads, but won't destroying the socket after every exchange mean re-acquiring (or failing to re-acquire) a connection to that client?
Yes.
I've seen so many conflicting websites about sockets in Java and how they should be implemented.
You should use a connection pool at the client; a request loop at the server that looks for multiple requests per connection; a client-side facility that closes idle connections after some idle timeout; and a read timeout at the server that closes connections on which no request has been read within the timeout.
I need to implement analytics system with server and terminals which in realtime.
I use library ZeroMq (pub|sub mode) to send messages to client (~40bytes).
if I connect with 1 client, messages come with delay (sometime more than 250ms).
if I connect with 100 clients a lot of clients lose uniformity of delivery (more than 750ms no one message, after that huge scope of data). It is so critical issue for me.
I have to publish to more than 6000 terminals...
Publish every 30ms, it is about 1700bytes to each client in the worst case (tcp)
Maybe I should use another technology to deliver messages in realtime?
As I said in the comment, Multicast is the way. The primary overriding concern is whether your terminals can join the group you are publishing on - irrespective of how far away they are.
You've not indicated how the terminals connect to your network - (for example vpn over internet, private line whatever..) You asked for a better technology - it's multicast.
Now there are some options if you are going to go down the tcp route:
Build a load-balacing infrastructure which sits in front of your
service. Meaning that your terminals don't connect to your
service, but to a set of load balancers which then connect to your
service. If you have 10 of these for example, each only has to deal
with 600 clients. Your problem is much smaller - you can scale this
way. Don't forget to use asynchronous io.
Buy better hardware - for example solace or tervela do hardware
message brokers which can scale to very large numbers concurrent tcp
connections - but this is not cheap.
I'm developing a Java client/server application in which there will be a great number of servers with which the clients are going to have to connect. The problem is that probably the vast majority of them will not be serving at the same time. The client needs to find at least one available in the list, so it will iterate it, looking for an available server (when it finds the first it stops, one is enough).
The problem is that the list will probably be long, tens of zousands, they could be even hundreds... and it may happen that only 1% of them are connected (i.e. executing the server). That's why I need a clever and a fast way to know if a server is connected, without waiting for time-outs or so. I accept all kinds of suggestions.
I have thought about ordering the server list statistically, so that the servers that are available more often are the first hosts attempted. But this is not enough.
Perhaps multicasting UDP datagrams? The connections between clients/servers are TCP, but perhaps to find a server it's better to do an UDP multicast first and wait for the answer, for example... what do you think?
:)
EDIT:
Both the server and client use thread pools.
The server pool handles 200 threads concurrently, and when the pool is full, queues the rest until the queue is 200 runnables long. Then it blocks, and stop accepting connections until there is free room in the queue again.
The client has a cached thread pool, it can make all the request to the server you want concurrently (with common sense, obviously...).
This is just an initial thought and would add some over head, but you could have the servers periodically ping some centralized server which the clients would connect through. Then if the server doesn't ping for some set time it gets removed.
You might want to use a peer-to-peer network.
Have a look at JXTA/JXSE:
http://jxse.kenai.com/index.html
If it is your own code which is running on each of these servers, could you send an alive to a central server (which is controlled by you and is guaranteed to be up at all times)? The central server can then maintain an updated list of all servers which are active. The client just needs a copy of this list from the central server and then start whatever communication it needs.
Sounds like a job for Threads. You cannot speed up the connection, it takes time to contact the server.
IMHO, the best way is to get few hundred Threads to march through the list of servers. The first one to find one server alive wins. Then signal other threads to die out.
Btw, did you really mean to order the server list "sadistically"? :)
I have a Java program that creates a server socket and accepts connections from various clients.
I am interested in finding out the number of connections that are in queue (waiting to be processed by the server). I have used the default constructor without specifying the backlog parameter.
At runtime, is it possible to know how many connections are pending for the server?
I want to implement a monitor process, which will check how full the queue is and based on that, trigger clone processes for load balancing (so that the connections are not dropped).
According to this SO answer, you can't.