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Java: Managing more connections than there are threads, using a queue

For an exercise, we are to implement a server that has a thread that listens for connections, accepts them and throws the socket into a BlockingQueue. A set of worker threads in a pool then goes through the queue and processes the requests coming in through the sockets.
Each client connects to the server, sends a large number of requests (waiting for the response before sending the next request) and eventually disconnects when done.
My current approach is to have each worker thread waiting on the queue, getting a socket, then processing one request, and finally putting the (still open) socket back into the queue before handling another request, potentially from a different client. There are many more clients than there are worker threads, so many connections queue up.
The problem with this approach: A thread will be blocked by a client even if the client doesn't send anything. Possible pseudo-solutions, all not satisfactory:
Call available() on the inputStream and put the connection back into the queue if it returns 0. The problem: It's impossible to detect if the client is still connected.
As above but use socket.isClosed() or socket.isConnected() to figure out if the client is still connected. The problem: Both methods don't detect a client hangup, as described nicely by EJP in Java socket API: How to tell if a connection has been closed?
Probe if the client is still there by reading from or writing to it. The problem: Reading blocks (i.e. back to the original situation where an inactive client blocks the queue) and writing actually sends something to the client, making the tests fail.
Is there a way to solve this problem? I.e. is it possible to distinguish a disconnected client from a passive client without blocking or sending something?

Short answer: no. For a longer answer, refer to the one by EJP.
Which is why you probably shouldn't put the socket back on the queue at all, but rather handle all the requests from the socket, then close it. Passing the connection to different worker threads to handle requests separately won't give you any advantage.
If you have badly behaving clients you can use a read timeout on the socket, so reading will block only until the timeout occurs. Then you can close that socket, because your server doesn't have time to cater to clients that don't behave nicely.

Is there a way to solve this problem? I.e. is it possible to distinguish a disconnected client from a passive client without blocking or sending something?
Not really when using blocking IO.
You could look into the non-blocking (NIO) package, which deals with things a little differently.
In essence you have a socket which can be registered with a "selector". If you register sockets for "is data ready to be read" you can then determine which sockets to read from without having to poll individually.
Same sort of thing for writing.
Here is a tutorial on writing NIO servers

Turns out the problem is solvable with a few tricks. After long discussions with several people, I combined their ideas to get the job done in reasonnable time:
After creating the socket, configure it such that a blocking read will only block for a certain time, say 100ms: socket.setSoTimeout(100);
Additionally, record the timestamp of the last successful read of each connection, e.g. with System.currentTimeMillis()
In principle (see below for exception to this principle), run available() on the connection before reading. If this returns 0, put the connection back into the queue since there is nothing to read.
Exception to the above principle in which case available() is not used: If the timestamp is too old (say, more than 1 second), use read() to actually block on the connection. This will not take longer than the SoTimeout that you set above for the socket. If you get a TimeoutException, put the connection back into the queue. If you read -1, throw the connection away since it was closed by the remote end.
With this strategy, most read attempts terminate immediately, either returning some data or nothing beause they were skipped since there was nothing available(). If the other end closed its connection, we will detect this within one second since the timestamp of the last successful read is too old. In this case, we perform an actual read that will return -1 and the socket's isClosed() is updated accordingly. And in the case where the socket is still open but the queue is so long that we have more than a second of delay, it takes us aditionally 100ms to find out that the connection is still there but not ready.
EDIT: An enhancement of this is to change "last succesful read" to "last blocking read" and also update the timestamp when getting a TimeoutException.

No, the only way to discern an inactive client from a client that didn't shut down their socket properly is to send a ping or something to check if they're still there.
Possible solutions I can see is
Kick clients that haven't sent anything for a while. You would have to keep track of how long they've been quiet for, and once they reach a limit you assume they've disconnected .
Ping the client to see if they're still there. I know you asked for a way to do this without sending anything, but if this is really a problem, i.e you can't use the above solution, this is probably the best way to do it depending on the specifics(since it's an exercise you might have to imagine the specifics).
A mix of both, actually this is probably better. Keep track of how long they've been quiet for, after a bit send them a ping to see if they still live.

Java - Making a chatserver for multiple clients - how many threads do i need?

So I've been given a school exercise, where I am to make a chatserver in java. I've done it in TCP, but I could just aswell have done it in UDP.
I'm starting to do some thread implementations, but now I'm not really sure how I should approach it, and how many threads to make.
So fare, this is my approach:
Server needs 1 thread for running, 1 thread for receiving messages, and 1 thread to send messages. Furthermore, I've made a thread for each Client connected, which the server puts in a ClientThread[], which is then used for messaging each client. This comes to a total of 13 threads ( 10 clients max )
Furthermore, I guess each local client needs a local thread, for sending and receiving messages aswell.
Is this the right approach here? Will it be problematic to have a server running 13 threads?
Thanks in advance!

Your approach looks solid, but you don't really want to handle an array of so much client threads. You should use Threadpools
You store in memory a list of already initialized threads, you only open them at startup and close them at shutdown. every time a client/server needs to send a message, you will use a thread, then return it to the pool (instead of closing it). you can also configure a pool to grow on demand

Java TCP latency

I am developing an Android application communicating with a TCP Java-server over a WLAN connection. The Android application is a game with sprites being moved around the screen. Whenever a sprite moves, the AndroidClient sends its coordinates to the Java-server, wich then sends the data to the other clients (maximum 4 clients). The server handles each client on a separate thread, data updates are sent about every 20 ms., and each packet consists of about 1-10 bytes. I am on a 70 Mbit network (with about 15 Mbit effective on my Wireless).
I am having problems with an unstable connection, and experiencing latency at about 50-500 ms. every 10th-30th packet. I have set the tcpNoDelay to true, wich stopped the consistent 200ms latency, although it still lags a lot. As I am quite new to both Android and networking I don't know whether this is to be expected or not. I am also wondering if UDP could be suitable for my program, as I am interested in sending updates fast rather than every packet arriving correctly.
I would appreciate any guidance as to how to avoid/work around this latency problem. General tips on how to implement such a client-server architecture would also be applauded.

On a wireless LAN you'll occasionally see dropped packets, which results in a packet retransmission after a delay. If you want to control the delay before retransmission you're almost certainly going to have to use UDP.

You definitely want to use UDP. For a game you don't care if the position of a sprite is incorrect for a short time. So UDP is ideal in this case.
Also, if you have any control over the server code, I would not use separate threads for clients. Threads are useful if you need to make calls to libraries that you don't have control over and that can block (such as because they touch a file or try to perform additional network communication). But they are expensive. They consume a lot of resources and as such they actually make things slower than they could be.
So for a network game server where latency and performance are absolutely critical, I would just use one thread to process a queue of commands that have a state and then make sure that you never perform an operation that blocks. So each command is processed in order, it's state is evaluated and updated (like a laser blast intersected with another object). If the command requires blocking (like reading from a file) then you need to perform a non-blocking read and set the state of that command accordingly so that your command processor never blocks. The key is that the command processor can never never ever block. It would just run in a loop but you would have to call Thread.sleep(x) in an appropriate way so as not to waste CPU.
As for the client side, when a client submits a command (like they fired a laser or some such), the client would generate a response object and insert it into a Map with a sequence id as the key. Then it would send the request with the sequence id and when the server responds with the that id, you just lookup the response object in the Map and decode the response into that object. Meaning this allows you to perform concurrent operations.

Faster detection of a broken socket in Java/Android

Background
My application gathers data from the phone and sends the to a remote server.
The data is first stored in memory (or on file when it's big enough) and every X seconds or so the application flushes that data and sends it to the server.
It's mission critical that every single piece of data is sent successfully, I'd rather send the data twice than not at all.
Problem
As a test I set up the app to send data with a timestamp every 5 seconds, this means that every 5 seconds a new line appear on the server.
If I kill the server I expect the lines to stop, they should now be written to memory instead.
When I enable the server again I should be able to confirm that no events are missing.
The problem however is that when I kill the server it takes about 20 seconds for IO operations to start failing meaning that during those 20 seconds the app happily sends the events and removes them from memory but they never reach the server and are lost forever.
I need a way to make certain that the data actually reaches the server.
This is possibly one of the more basic TCP questions but non the less, I haven't found any solution to it.
Stuff I've tried
Setting Socket.setTcpNoDelay(true)
Removing all buffered writers and just using OutputStream directly
Flushing the stream after every send
Additional info
I cannot change how the server responds meaning I can't tell the server to acknowledge the data (more than mechanics of TCP that is), the server will just silently accept the data without sending anything back.
Snippet of code
Initialization of the class:
socket = new Socket(host, port);
socket.setTcpNoDelay(true);
Where data is sent:
while(!dataList.isEmpty()) {
String data = dataList.removeFirst();
inMemoryCount -= data.length();
try {
OutputStream os = socket.getOutputStream();
os.write(data.getBytes());
os.flush();
}
catch(IOException e) {
inMemoryCount += data.length();
dataList.addFirst(data);
socket = null;
return false;
}
}
return true;
Update 1
I'll say this again, I cannot change the way the server behaves.
It receive data over TCP and UPD and does not send any data back to confirm the receive. This is a fact and sure in a perfect world the server would acknowledge the data but that will simply not happen.
Update 2
The solution posted by Fraggle works perfect (closing the socket and waiting for the input stream to be closed).
This however comes with a new set of problems.
Since I'm on a phone I have to assume that the user cannot send an infinite amount of bytes and I would like to keep all data traffic to a minimum if possible.
I'm not worried by the overhead of opening a new socket, those few bytes will not make a difference. What I am worried about however is that every time I connect to the server I have to send a short string identifying who I am.
The string itself is not that long (around 30 characters) but that adds up if I close and open the socket too often.
One solution is only to "flush" the data every X bytes, the problem is I have to choose X wisely; if too big there will be too much duplicate data sent if the socket goes down and if it's too small the overhead is too big.
Final update
My final solution is to "flush" the socket by closing it every X bytes and if all didn't got well those X bytes will be sent again.
This will possibly create some duplicate events on the server but that can be filtered there.

Dan's solution is the one I'd suggest right after reading your question, he's got my up-vote.
Now can I suggest working around the problem? I don't know if this is possible with your setup, but one way of dealing with badly designed software (this is your server, sorry) is to wrap it, or in fancy-design-pattern-talk provide a facade, or in plain-talk put a proxy in front of your pain-in-the-behind server. Design meaningful ack-based protocol, have the proxy keep enough data samples in memory to be able to detect and tolerate broken connections, etc. etc. In short, have the phone app connect to a proxy residing somewhere on a "server-grade" machine using "good" protocol, then have the proxy connect to the server process using the "bad" protocol. The client is responsible for generating data. The proxy is responsible for dealing with the server.
Just another idea.
Edit 0:
You might find this one entertaining: The ultimate SO_LINGER page, or: why is my tcp not reliable.

The bad news: You can't detect a failed connection except by trying to send or receive data on that connection.
The good news: As you say, it's OK if you send duplicate data. So your solution is not to worry about detecting failure in less than the 20 seconds it now takes. Instead, simply keep a circular buffer containing the last 30 or 60 seconds' worth of data. Each time you detect a failure and then reconnect, you can start the session by resending that saved data.
(This could get to be problematic if the server repeatedly cycles up and down in less than a minute; but if it's doing that, you have other problems to deal with.)

See the accepted answer here: Java Sockets and Dropped Connections
socket.shutdownOutput();
wait for inputStream.read() to return -1, indicating the peer has also shutdown its socket

Won't work: server cannot be modified
Can't your server acknowledge every message it receives with another packet? The client won't remove the messages that the server did not acknowledge yet.
This will have performance implications. To avoid slowing down you can keep on sending messages before an acknowledgement is received, and acknowledge several messages in one return message.
If you send a message every 5 seconds, and disconnection is not detected by the network stack for 30 seconds, you'll have to store just 6 messages. If 6 sent messages are not acknowledged, you can consider the connection to be down. (I suppose that logic of reconnection and backlog sending is already implemented in your app.)

What about sending UDP datagrams on a separate UDP socket while making the remote host respond to each, and then when the remote host doesn't respond, you kill the TCP connection? It detects a link breakage quickly enough :)

Use http POST instead of socket connection, then you can send a response to each post. On the client side you only remove the data from memory if the response indicates success.
Sure its more overhead, but gives you what you want 100% of the time.

Best way to configure a Threadpool for a Java RIA client app

I've a Java client which accesses our server side over HTTP making several small requests to load each new page of data. We maintain a thread pool to handle all non UI processing, so any background client side tasks and any tasks which want to make a connection to the server. I've been looking into some performance issues and I'm not certain we've got our threadpool set up as well as possible. Currently we use a ThreadPoolExecutor with a core pool size of 8, we use a LinkedBlockingQueue for the work queue so the max pool size is ignored. No doubt there's no simple do this certain thing in all situations answer, but are there any best practices. My thinking at the moment is
1) I'll switch to using a SynchronousQueue instead of a LinkedBlockingQueue so the pool can grow to the max pool size figure.
2) I'll set the max pool size to be unlimited.
Basically my current fear is that occasional performance issues on the server side are causing unrelated client side processing to halt due to the upper limit on the thread pool size. My fear with unbounding it is the additional hit on managing those threads on the client, possibly just the better of 2 evils.
Any suggestions, best practices or useful references?
Cheers,
Robin

It sounds like you'd probably be better of limiting the queue size: does your application still behave properly when there are many requests queued (is it acceptable for all task to be queued for a long time, are some more important to others)? What happens if there are still queued tasks left and the user quits the application? If the queue growing very large, is there a chance that the server will catch-up (soon enough) to hide the problem completely from the user?
I'd say create one queue for requests whose response is needed to update the user interface, and keep its queue very small. If this queue gets too big, notify the user.
For real background tasks keep a separate pool, with a longer queue, but not infinite. Define graceful behavior for this pool when it grows or when the user wants to quit but there are tasks left, what should happen?

In general, network latencies are easily orders of magnitude higher than anything that can be happening in regards to memory allocation or thread management on the client side. So, as a general rule, if you are running into a performance bottle neck, look first and foremost to the networking link.
If the issue is that your server simply can not keep up with the requests from the clients, bumping up the threads on the client side is not going to help matters: you'll simply progress from having 8 threads waiting to get a response to more threads waiting (and you may even aggravate the server side issues by increasing its load due to higher number of connections it is managing).
Both of the concurrent queues in JDK are high performers; the choice really boils down to usage semantics. If you have non-blocking plumbing, then it is more natural to use the non-blocking queue. IF you don't, then using the blocking queues makes more sense. (You can always specify Integer.MAX_VALUE as the limit). If FIFO processing is not a requirement, make sure you do not specify fair ordering as that will entail a substantial performance hit.

As alphazero said, if you've got a bottleneck, your number of client side waiting jobs will continue to grow regardless of what approach you use.
The real question is how you want to deal with the bottleneck. Or more correctly, how you want your users to deal with the bottleneck.
If you use an unbounded queue, then you don't get feedback that the bottleneck has occurred. And in some applications, this is fine: if the user is kicking off asynchronous tasks, then there's no need to report a backlog (assuming it eventually clears). However, if the user needs to wait for a response before doing the next client-side task, this is very bad.
If you use LinkedBlockingQueue.offer() on a bounded queue, then you'll immediately get a response that says the queue is full, and can take action such as disabling certain application features, popping a dialog, whatever. This will, however, require more work on your part, particularly if requests can be submitted from multiple places. I'd suggest, if you don't have it already, you create a GUI-aware layer over the server queue to provide common behavior.
And, of course, never ever call LinkedBlockingQueue.put() from the event thread (unless you don't mind a hung client, that is).

Why not create an unbounded queue, but reject tasks (and maybe even inform the user that the server is busy (app dependent!)) when the queue reaches a certain size? You can then log this event and find out what happened on the server side for the backup to occur, Additionally, unless you are connecting to a multiple remote servers there is probably not much point having more than a couple of threads in the pool, although this does depend on your app and what it does and who it talks to.
Having an unbounded pool is usually dangerous as it generally doesn't degrade gracefully. Better to log the problem, raise an alert, prevent further actions being queued and figure out how to scale the server side, if the problem is there, to prevent this happening again.