I have a c++ program with a socket communications class. Each socket has a large dedicated
buffer for assembling an output message, so usage would be like:
class CSocketClass {
public:
SetMsgHeader(int n) { Mutex_.lock(); DoWhateverIsNeededToSetHeaderInBuffer(n); } // where n would be the message type
SetMsgField(double a); { DoWhateverIsNeededToSetDataInBuffer(a); } // where a would be some arbitrary content
SendMsg(); { DoWhateverIsNeededToSendBuffer(); Mutex_.unlock(); } // where this would send the number of bytes added to the buffer since the header was set
private:
char buffer[reallylarge];
MiscSocketApparatus...
boost::mutex Mutex_;
};
Multiple threads could be trying to send messages, each consisting of three or more calls the set the header, the content, and finally sending the message on its way. To keep them from conflicting, I've tried to keep only a single writer at a time by using the Mutex. The desired behavior would be for a second-to-arrive writer to be blocked until the first-to-arrive writer unlocked the mutex. Then the blocked writer would be able to proceed.
This seems to work most of the time, but on rare occasions (not every day), deadlocks still seem to occur.
I'm much more familiar with simpler lock issues using scoped locks, but those concepts may not translate perfectly to this problem, where the lock needs to be persistent across a number of calls to the object owning the lock.
From reading the Boost synchronication tutorial, I think there are better ways to do this, but its not clear what would be best.
Any recommendations would be greatly appreciated.
Since each thread has its own buffer, have each build the complete message in its own buffer, then lock the mutex and send the message.
Better still, have one thread to actually dispatch messages, and N threads to create them. Put a thread-safe queue in between, so a thread creates a message, puts it in the queue, then (if needed) goes back to creating another message. The message sender just constantly waits for a message in the queue, retrieves it, sends it, and repeats.
You probably also want a thread-safe collection of buffers, so when a message has been sent, the sending thread can put the buffer where a message-builder thread can use it again when needed.
As an aside: for the buffer I'd use an std::string or a std::vector, instead of a raw array.
Related
I'm working on a multithreaded project in C++ that sends data to a series of network connections. Here's some pseudocode that illustrates what's going on:
class NetworkManager
{
Thread writer; // responsible for writing data in queues to the network
Queue[] outqueue; // holds data until the network is ready to receive it
Network[] nets; // sockets or whatever
Mutex[] outlock; // protects access to members of outqueue
Mutex managerlock; // protects access to all queues
Condition notifier; // blocks the write thread when there is no data
}
In reality it's a whole lot more complicated than that, but I've axed a lot of unnecessary details. One important detail is that the networking is rate-limited, and the ability of the program to queue data independently from sending it is a feature of the design (the program should not have to wait to process new data because it's blocking on a network write).
Here's a brief description of how the program is expected to interact with this class. Note that QueueWriteToNetwork and DoAdministrativeStuff are, in my implementation, managed by THE SAME external thread.
QueueWriteToNetwork(network, data) // responsibility of external thread
Let i = the index of the network to send to
Lock(outlock[i])
outqueue[i].Add(data)
Unlock(outlock[i])
Signal(notifier)
DoAdministrativeStuff(network, more) // responsibility of external thread
Lock(managerlock)
more.Process() // might do any of the following:
// connect or disconnect networks
// add or remove networks from list
// immediate write data to network, bypassing rate limiting
// other things that I forgot
Unlock(managerlock)
WriterThreadMain() // responsibility of internal write thread
Lock(managerlock)
Loop forever:
Check for data in every queue (locking and unlocking each queue)
If all queues have no data to write:
Wait(notifier, managerlock)
continue
If outqueue[i] has data ready to write
Lock(outlock[i])
Send data from outqueue[i]
outqueue[i].Pop()
Unlock(outqueue[i])
As you might be able to see, there are a few issues with this approach (for example, if a write is queued to the network with QueueWriteToNetwork as WriterThreadMain is checking if the queues are empty, the call to Signal(notifier) could potentially be dropped, and the write queue could remain waiting even though there was data ready).
I need to phrase this in such a way that the following are possible:
Adding data to a write queue does not block, or blocks for only a reasonably short time (specifically, it does not block for the duration of a network write that's in progress)
The DoAdministrativeStuff function must have the ability to ensure that the writer thread is blocked in a safe state (i.e. not accessing any queue, queue lock, or network)
I've explored the possibility of using a semaphore to track the number of items in write queues. This would solve the lost-update problem I mentioned earlier.
Finally, I'm targeting Linux (using Posix libraries to provide the types pthread_t, pthread_mutex_t, pthread_cond_t, and sem_t), and I don't care about compatibility with Windows. Also, please don't recommend Boost. Pulling any Boost header into my code makes compilation take unbearably long.
So I've made a socket class that uses boost::asio library to make asynchronous reads and writes. It works, but I have a few questions.
Here's a basic code example:
class Socket
{
public:
void doRead()
{
m_sock->async_receive_from(boost::asio::buffer(m_recvBuffer), m_from, boost::bind(&Socket::handleRecv, this, boost::asio::placeholders::error(), boost::asio::placeholders::bytes_transferred()));
}
void handleRecv(boost::system::error_code e, int bytes)
{
if (e.value() || !bytes)
{
handle_error();
return;
}
//do something with data read
do_something(m_recvBuffer);
doRead(); //read another packet
}
protected:
boost::array<char, 1024> m_recvBuffer;
boost::asio::ip::udp::endpoint m_from;
};
It seems that the program will read a packet, handle it, then prepare to read another. Simple.
But what if I set up a thread pool? Should the next call to doRead() be before or after handling the read data? It seems that if it is put before do_something(), the program can immediately begin reading another packet, and if it is put after, the thread is tied up doing whatever do_something() does, which could possibly take a while. If I put the doRead() before the handling, does that mean the data in m_readBuffer might change while I'm handling it?
Also, if I'm using async_send_to(), should I copy the data to be sent into a temporary buffer, because the actual send might not happen until after the data has fallen out of scope? i.e.
void send()
{
char data[] = {1, 2, 3, 4, 5};
m_sock->async_send_to(boost::buffer(&data[0], 5), someEndpoint, someHandler);
} //"data" gets deallocated, but the write might not have happened yet!
Additionally, when the socket is closed, the handleRecv will be called with an error indicating it was interrupted. If I do
Socket* mySocket = new Socket()...
...
mySocket->close();
delete mySocket;
could it cause an error, because there is a chance that mySocket will be deleted before handleRecv() gets called/finished?
Lots of questions here, I'll try to address them one at a time.
But what if I set up a thread pool?
The traditional way to use a thread pool with Boost.Asio is to invoke io_service::run() from multiple threads. Beware this isn't a one-size-fits-all answer though, there can be scalability or performance issues, but this methodology is by far the easiest to implement. There are many similar questions on Stackoverflow with more information.
Should the next call to doRead be before or after handling the read
data? It seems that if it is put before do_something(), the program
can immediately begin reading another packet, and if it is put after,
the thread is tied up doing whatever do_something does, which could
possibly take a while.
This really depends on what do_something() needs to do with m_recvBuffer. If you wish to invoke do_something() in parallel with doRead() using io_service::post() you will likely need to make a copy of m_recvBuffer.
If I put the doRead() before the handling, does
that mean the data in m_readBuffer might change while I'm handling it?
as I mentioned previously, yes this can and will happen.
Also, if I'm using async_send_to(), should I copy the data to be sent
into a temporary buffer, because the actual send might not happen
until after the data has fallen out of scope?
As the documentation describes, it is up to the caller (you) to ensure the buffer remains in scope for the duration of the asynchronous operation. As you suspected, your current example invokes undefined behavior because data[] will go out of scope.
Additionally, when the socket is closed, the handleRecv() will be called
with an error indicating it was interrupted.
If you wish to continue to use the socket, use cancel() to interrupt outstanding asynchronous operations. Otherwise, close() will work. The error passed to outstanding asynchronous operations in either scenario is boost::asio::error::operation_aborted.
When using pthread, I can pass data at thread creation time.
What is the proper way of passing new data to an already running thread?
I'm considering making a global variable and make my thread read from that.
Thanks
That will certainly work. Basically, threads are just lightweight processes that share the same memory space. Global variables, being in that memory space, are available to every thread.
The trick is not with the readers so much as the writers. If you have a simple chunk of global memory, like an int, then assigning to that int will probably be safe. Bt consider something a little more complicated, like a struct. Just to be definite, let's say we have
struct S { int a; float b; } s1, s2;
Now s1,s2 are variables of type struct S. We can initialize them
s1 = { 42, 3.14f };
and we can assign them
s2 = s1;
But when we assign them the processor isn't guaranteed to complete the assignment to the whole struct in one step -- we say it's not atomic. So let's now imagine two threads:
thread 1:
while (true){
printf("{%d,%f}\n", s2.a, s2.b );
sleep(1);
}
thread 2:
while(true){
sleep(1);
s2 = s1;
s1.a += 1;
s1.b += 3.14f ;
}
We can see that we'd expect s2 to have the values {42, 3.14}, {43, 6.28}, {44, 9.42} ....
But what we see printed might be anything like
{42,3.14}
{43,3.14}
{43,6.28}
or
{43,3.14}
{44,6.28}
and so on. The problem is that thread 1 may get control and "look at" s2 at any time during that assignment.
The moral is that while global memory is a perfectly workable way to do it, you need to take into account the possibility that your threads will cross over one another. There are several solutions to this, with the basic one being to use semaphores. A semaphore has two operations, confusingly named from Dutch as P and V.
P simply waits until a variable is 0 and the goes on, adding 1 to the variable; V subtracts 1 from the variable. The only thing special is that they do this atomically -- they can't be interrupted.
Now, do you code as
thread 1:
while (true){
P();
printf("{%d,%f}\n", s2.a, s2.b );
V();
sleep(1);
}
thread 2:
while(true){
sleep(1);
P();
s2 = s1;
V();
s1.a += 1;
s1.b += 3.14f ;
}
and you're guaranteed that you'll never have thread 2 half-completing an assignment while thread 1 is trying to print.
(Pthreads has semaphores, by the way.)
I have been using the message-passing, producer-consumer queue-based, comms mechanism, as suggested by asveikau, for decades without any problems specifically related to multiThreading. There are some advantages:
1) The 'threadCommsClass' instances passed on the queue can often contain everything required for the thread to do its work - member/s for input data, member/s for output data, methods for the thread to call to do the work, somewhere to put any error/exception messages and a 'returnToSender(this)' event to call so returning everything to the requester by some thread-safe means that the worker thread does not need to know about. The worker thread then runs asynchronously on one set of fully encapsulated data that requires no locking. 'returnToSender(this)' might queue the object onto a another P-C queue, it might PostMessage it to a GUI thread, it might release the object back to a pool or just dispose() it. Whatever it does, the worker thread does not need to know about it.
2) There is no need for the requesting thread to know anything about which thread did the work - all the requestor needs is a queue to push on. In an extreme case, the worker thread on the other end of the queue might serialize the data and communicate it to another machine over a network, only calling returnToSender(this) when a network reply is received - the requestor does not need to know this detail - only that the work has been done.
3) It is usually possible to arrange for the 'threadCommsClass' instances and the queues to outlive both the requester thread and the worker thread. This greatly eases those problems when the requester or worker are terminated and dispose()'d before the other - since they share no data directly, there can be no AV/whatever. This also blows away all those 'I can't stop my work thread because it's stuck on a blocking API' issues - why bother stopping it if it can be just orphaned and left to die with no possibility of writing to something that is freed?
4) A threadpool reduces to a one-line for loop that creates several work threads and passes them the same input queue.
5) Locking is restricted to the queues. The more mutexes, condVars, critical-sections and other synchro locks there are in an app, the more difficult it is to control it all and the greater the chance of of an intermittent deadlock that is a nightmare to debug. With queued messages, (ideally), only the queue class has locks. The queue class must work 100% with mutiple producers/consumers, but that's one class, not an app full of uncooordinated locking, (yech!).
6) A threadCommsClass can be raised anytime, anywhere, in any thread and pushed onto a queue. It's not even necessary for the requester code to do it directly, eg. a call to a logger class method, 'myLogger.logString("Operation completed successfully");' could copy the string into a comms object, queue it up to the thread that performs the log write and return 'immediately'. It is then up to the logger class thread to handle the log data when it dequeues it - it may write it to a log file, it may find after a minute that the log file is unreachable because of a network problem. It may decide that the log file is too big, archive it and start another one. It may write the string to disk and then PostMessage the threadCommsClass instance on to a GUI thread for display in a terminal window, whatever. It doesn't matter to the log requesting thread, which just carries on, as do any other threads that have called for logging, without significant impact on performance.
7) If you do need to kill of a thread waiting on a queue, rather than waiing for the OS to kill it on app close, just queue it a message telling it to teminate.
There are surely disadvantages:
1) Shoving data directly into thread members, signaling it to run and waiting for it to finish is easier to understand and will be faster, assuming that the thread does not have to be created each time.
2) Truly asynchronous operation, where the thread is queued some work and, sometime later, returns it by calling some event handler that has to communicate the results back, is more difficult to handle for developers used to single-threaded code and often requires state-machine type design where context data must be sent in the threadCommsClass so that the correct actions can be taken when the results come back. If there is the occasional case where the requestor just has to wait, it can send an event in the threadCommsClass that gets signaled by the returnToSender method, but this is obviously more complex than simply waiting on some thread handle for completion.
Whatever design is used, forget the simple global variables as other posters have said. There is a case for some global types in thread comms - one I use very often is a thread-safe pool of threadCommsClass instances, (this is just a queue that gets pre-filled with objects). Any thread that wishes to communicate has to get a threadCommsClass instance from the pool, load it up and queue it off. When the comms is done, the last thread to use it releases it back to the pool. This approach prevents runaway new(), and allows me to easily monitor the pool level during testing without any complex memory-managers, (I usually dump the pool level to a status bar every second with a timer). Leaking objects, (level goes down), and double-released objects, (level goes up), are easily detected and so get fixed.
MultiThreading can be safe and deliver scaleable, high-performance apps that are almost a pleasure to maintain/enhance, (almost:), but you have to lay off the simple globals - treat them like Tequila - quick and easy high for now but you just know they'll blow your head off tomorrow.
Good luck!
Martin
Global variables are bad to begin with, and even worse with multi-threaded programming. Instead, the creator of the thread should allocate some sort of context object that's passed to pthread_create, which contains whatever buffers, locks, condition variables, queues, etc. are needed for passing information to and from the thread.
You will need to build this yourself. The most typical approach requires some cooperation from the other thread as it would be a bit of a weird interface to "interrupt" a running thread with some data and code to execute on it... That would also have some of the same trickiness as something like POSIX signals or IRQs, both of which it's easy to shoot yourself in the foot while processing, if you haven't carefully thought it through... (Simple example: You can't call malloc inside a signal handler because you might be interrupted in the middle of malloc, so you might crash while accessing malloc's internal data structures which are only partially updated.)
The typical approach is to have your thread creation routine basically be an event loop. You can build a queue structure and pass that as the argument to the thread creation routine. Then other threads can enqueue things and the thread's event loop will dequeue it and process the data. Note this is cleaner than a global variable (or global queue) because it can scale to have multiple of these queues.
You will need some synchronization on that queue data structure. Entire books could be written about how to implement your queue structure's synchronization, but the most simple thing would have a lock and a semaphore. When modifying the queue, threads take a lock. When waiting for something to be dequeued, consumer threads would wait on a semaphore which is incremented by enqueuers. It's also a good idea to implement some mechanism to shut down the consumer thread.
I am about to implement a worker thread with work item queuing, and while I was thinking about the problem, I wanted to know if I'm doing the best thing.
The thread in question will have to have some thread local data (preinitialized at construction) and will loop on work items until some condition will be met.
pseudocode:
volatile bool run = true;
int WorkerThread(param)
{
localclassinstance c1 = new c1();
[other initialization]
while(true) {
[LOCK]
[unqueue work item]
[UNLOCK]
if([hasWorkItem]) {
[process data]
[PostMessage with pointer to data]
}
[Sleep]
if(!run)
break;
}
[uninitialize]
return 0;
}
I guess I will do the locking via critical section, as the queue will be std::vector or std::queue, but maybe there is a better way.
The part with Sleep doesn't look too great, as there will be a lot of extra Sleep with big Sleep values, or lot's of extra locking when Sleep value is small, and that's definitely unnecessary.
But I can't think of a WaitForSingleObject friendly primitive I could use instead of critical section, as there might be two threads queuing work items at the same time. So Event, which seems to be the best candidate, can loose the second work item if the Event was set already, and it doesn't guarantee a mutual exclusion.
Maybe there is even a better approach with InterlockedExchange kind of functions that leads to even less serialization.
P.S.: I might need to preprocess the whole queue and drop the obsolete work items during the unqueuing stage.
There are a multitude of ways to do this.
One option is to use a semaphore for the waiting. The semaphore is signalled every time a value is pushed on the queue, so the worker thread will only block if there are no items in the queue. This will still require separate synchronization on the queue itself.
A second option is to use a manual-reset event which is set when there are items in the queue and cleared when the queue is empty. Again, you will need to do separate synchronization on the queue.
A third option is to have an invisible message-only window created on the thread, and use a special WM_USER or WM_APP message to post items to the queue, attaching the item to the message via a pointer.
Another option is to use condition variables. The native Windows condition variables only work if you're targetting Windows Vista or Windows 7, but condition variables are also available for Windows XP with Boost or an implementation of the C++0x thread library. An example queue using boost condition variables is available on my blog: http://www.justsoftwaresolutions.co.uk/threading/implementing-a-thread-safe-queue-using-condition-variables.html
It is possible to share a resource between threads without using blocking locks at all, if your scenario meets certain requirements.
You need an atomic pointer exchange primitive, such as Win32's InterlockedExchange. Most processor architectures provide some sort of atomic swap, and it's usually much less expensive than acquiring a formal lock.
You can store your queue of work items in a pointer variable that is accessible to all the threads that will be interested in it. (global var, or field of an object that all the threads have access to)
This scenario assumes that the threads involved always have something to do, and only occasionally "glance" at the shared resource. If you want a design where threads block waiting for input, use a traditional blocking event object.
Before anything begins, create your queue or work item list object and assign it to the shared pointer variable.
Now, when producers want to push something onto the queue, they "acquire" exclusive access to the queue object by swapping a null into the shared pointer variable using InterlockedExchange. If the result of the swap returns a null, then somebody else is currently modifying the queue object. Sleep(0) to release the rest of your thread's time slice, then loop to retry the swap until it returns non-null. Even if you end up looping a few times, this is many. many times faster than making a kernel call to acquire a mutex object. Kernel calls require hundreds of clock cycles to transition into kernel mode.
When you successfully obtain the pointer, make your modifications to the queue, then swap the queue pointer back into the shared pointer.
When consuming items from the queue, you do the same thing: swap a null into the shared pointer and loop until you get a non-null result, operate on the object in the local var, then swap it back into the shared pointer var.
This technique is a combination of atomic swap and brief spin loops. It works well in scenarios where the threads involved are not blocked and collisions are rare. Most of the time the swap will give you exclusive access to the shared object on the first try, and as long as the length of time the queue object is held exclusively by any thread is very short then no thread should have to loop more than a few times before the queue object becomes available again.
If you expect a lot of contention between threads in your scenario, or you want a design where threads spend most of their time blocked waiting for work to arrive, you may be better served by a formal mutex synchronization object.
The fastest locking primitive is usually a spin-lock or spin-sleep-lock. CRITICAL_SECTION is just such a (user-space) spin-sleep-lock.
(Well, aside from not using locking primitives at all of course. But that means using lock-free data-structures, and those are really really hard to get right.)
As for avoiding the Sleep: have a look at condition-variables. They're designed to be used together with a "mutex", and I think they're much easier to use correctly than Windows' EVENTs.
Boost.Thread has a nice portable implementation of both, fast user-space spin-sleep-locks and condition variables:
http://www.boost.org/doc/libs/1_44_0/doc/html/thread/synchronization.html#thread.synchronization.condvar_ref
A work-queue using Boost.Thread could look something like this:
template <class T>
class Queue : private boost::noncopyable
{
public:
void Enqueue(T const& t)
{
unique_lock lock(m_mutex);
// wait until the queue is not full
while (m_backingStore.size() >= m_maxSize)
m_queueNotFullCondition.wait(lock); // releases the lock temporarily
m_backingStore.push_back(t);
m_queueNotEmptyCondition.notify_all(); // notify waiters that the queue is not empty
}
T DequeueOrBlock()
{
unique_lock lock(m_mutex);
// wait until the queue is not empty
while (m_backingStore.empty())
m_queueNotEmptyCondition.wait(lock); // releases the lock temporarily
T t = m_backingStore.front();
m_backingStore.pop_front();
m_queueNotFullCondition.notify_all(); // notify waiters that the queue is not full
return t;
}
private:
typedef boost::recursive_mutex mutex;
typedef boost::unique_lock<boost::recursive_mutex> unique_lock;
size_t const m_maxSize;
mutex mutable m_mutex;
boost::condition_variable_any m_queueNotEmptyCondition;
boost::condition_variable_any m_queueNotFullCondition;
std::deque<T> m_backingStore;
};
There are various ways to do this
For one you could create an event instead called 'run' and then use that to detect when thread should terminate, the main thread then signals. Instead of sleep you would then use WaitForSingleObject with a timeout, that way you will quit directly instead of waiting for sleep ms.
Another way is to accept messages in your loop and then invent a user defined message that you post to the thread
EDIT: depending on situation it may also be wise to have yet another thread that monitors this thread to check if it is dead or not, this can be done by the above mentioned message queue so replying to a certain message within x ms would mean that the thread hasn't locked up.
I'd restructure a bit:
WorkItem GetWorkItem()
{
while(true)
{
WaitForSingleObject(queue.Ready);
{
ScopeLock lock(queue.Lock);
if(!queue.IsEmpty())
{
return queue.GetItem();
}
}
}
}
int WorkerThread(param)
{
bool done = false;
do
{
WorkItem work = GetWorkItem();
if( work.IsQuitMessage() )
{
done = true;
}
else
{
work.Process();
}
} while(!done);
return 0;
}
Points of interest:
ScopeLock is a RAII class to make critical section usage safer.
Block on event until workitem is (possibly) ready - then lock while trying to dequeue it.
don't use a global "IsDone" flag, enqueue special quitmessage WorkItems.
You can have a look at another approach here that uses C++0x atomic operations
http://www.drdobbs.com/high-performance-computing/210604448
Use a semaphore instead of an event.
Keep the signaling and synchronizing separate. Something along these lines...
// in main thread
HANDLE events[2];
events[0] = CreateEvent(...); // for shutdown
events[1] = CreateEvent(...); // for work to do
// start thread and pass the events
// in worker thread
DWORD ret;
while (true)
{
ret = WaitForMultipleObjects(2, events, FALSE, <timeout val or INFINITE>);
if shutdown
return
else if do-work
enter crit sec
unqueue work
leave crit sec
etc.
else if timeout
do something else that has to be done
}
Given that this question is tagged windows, Ill answer thus:
Don't create 1 worker thread. Your worker thread jobs are presumably independent, so you can process multiple jobs at once? If so:
In your main thread call CreateIOCompletionPort to create an io completion port object.
Create a pool of worker threads. The number you need to create depends on how many jobs you might want to service in parallel. Some multiple of the number of CPU cores is a good start.
Each time a job comes in call PostQueuedCompletionStatus() passing a pointer to the job struct as the lpOverlapped struct.
Each worker thread calls GetQueuedCompletionItem() - retrieves the work item from the lpOverlapped pointer and does the job before returning to GetQueuedCompletionStatus.
This looks heavy, but io completion ports are implemented in kernel mode and represent a queue that can be deserialized into any of the worker threads associated with the queue (i.e. waiting on a call to GetQueuedCompletionStatus). The io completion port knows how many of the threads that are processing an item are actually using a CPU vs blocked on an IO call - and will release more worker threads from the pool to ensure that the concurrency count is met.
So, its not lightweight, but it is very very efficient... io completion port can be associated with pipe and socket handles for example and can dequeue the results of asynchronous operations on those handles. io completion port designs can scale to handling 10's of thousands of socket connects on a single server - but on the desktop side of the world make a very convenient way of scaling processing of jobs over the 2 or 4 cores now common in desktop PCs.
I'm writing server using boost.asio. I have read and write buffer for each connection and use asynchronized read/write function (async_write_some / async_read_some).
With read buffer and async_read_some, there's no problem. Just invoking async_read_some function is okay because read buffer is read only in read handler (means in same thread usually).
But, write buffer need to be accessed from several threads so it need to be locked for modifying.
FIRST QUESTION!
Are there any way to avoid LOCK for write buffer?
I write my own packet into stack buffer and copy it to the write buffer. Then, call async_write_some function to send the packet. In this way, if I send two packet in serial, is it okay invoking async_write_some function two times?
SECOND QUESTION!
What is common way for asynchronized writing in socket programming?
Thanks for reading.
Sorry but you have two choices:
Serialise the write statement, either with locks, or better
start a separate writer thread which reads requests from
a queue, other threads can then stack up requests on the
queue without too much contention (some mutexing would be required).
Give each writing thread its own socket!
This is actually the better solution if the program at the other end
of the wire can support it.
Answer #1:
You are correct that locking is a viable approach, but there is a much simpler way to do all of this. Boost has a nice little construct in ASIO called a strand. Any callback that has been wrapped using the strand will be serialized, guaranteed, no matter which thread executes the callback. Basically, it handles any locking for you.
This means that you can have as many writers as you want, and if they are all wrapped by the same strand (so, share your single strand among all of your writers) they will execute serially. One thing to watch out for is to make sure that you aren't trying to use the same actual buffer in memory for doing all of the writes. For example, this is what to avoid:
char buffer_to_write[256]; // shared among threads
/* ... in thread 1 ... */
memcpy(buffer_to_write, packet_1, std::min(sizeof(packet_1), sizeof(buffer_to_write)));
my_socket.async_write_some(boost::asio::buffer(buffer_to_write, sizeof(buffer_to_write)), &my_callback);
/* ... in thread 2 ... */
memcpy(buffer_to_write, packet_2, std::min(sizeof(packet_2), sizeof(buffer_to_write)));
my_socket.async_write_some(boost::asio::buffer(buffer_to_write, sizeof(buffer_to_write)), &my_callback);
There, you're sharing your actual write buffer (buffer_to_write). If you did something like this instead, you'll be okay:
/* A utility class that you can use */
class PacketWriter
{
private:
typedef std::vector<char> buffer_type;
static void WriteIsComplete(boost::shared_ptr<buffer_type> op_buffer, const boost::system::error_code& error, std::size_t bytes_transferred)
{
// Handle your write completion here
}
public:
template<class IO>
static bool WritePacket(const std::vector<char>& packet_data, IO& asio_object)
{
boost::shared_ptr<buffer_type> op_buffer(new buffer_type(packet_data));
if (!op_buffer)
{
return (false);
}
asio_object.async_write_some(boost::asio::buffer(*op_buffer), boost::bind(&PacketWriter::WriteIsComplete, op_buffer, boost::asio::placeholder::error, boost::asio::placeholder::bytes_transferred));
}
};
/* ... in thread 1 ... */
PacketWriter::WritePacket(packet_1, my_socket);
/* ... in thread 2 ... */
PacketWriter::WritePacket(packet_2, my_socket);
Here, it would help if you passed your strand into WritePacket as well. You get the idea, though.
Answer #2:
I think you are already taking a very good approach. One suggestion I would offer is to use async_write instead of async_write_some so that you are guaranteed the whole buffer is written before your callback gets called.
You could queue your modifications and perform them on the data in the write handler.
Network would most probably be the slowest part of the pipe (assuming your modification are not
computationaly expensive), so that you could perform mods while the socket layer is sending the
previous data.
Incase you are handling large number of clients with frequent connect/disconnect take a look at
IO completion ports or similar mechanism.