I'm in a situation where, logically, UDP would be the perfect choice (i need to be able to broadcast to hundreds of clients). This is in a very small and controlled environment (the whole network is over a few square metters, all devices are local, the network is way oversized with gigabit ethernet and switches everywhere).
Can i simply "ignore" all of the added reliability that needs to be tossed on udp (checking messages arrived, resending them etc) as those mostly apply where the is expected packet loss (the internet) or is it really suggested to handle udp as "may not arrive" even in such conditions?
I'm not asking for theorycrafting, really wondering if anyone could tell me from experience if i'm actually likely to have udp packets missing in such an environment or is it's going to be a really rare event as obviously sending things and assuming that worked is much simpler than handling all possible errors.
This is a matter of stochastics. Even in small local networks, packet losses will occur. Maybe they have an absolute probability of 1e-10 in a normal usage scenario. Maybe more, maybe less.
So, now comes real-world experience: Network controllers and Operating systems do have a tough live, if used in high-throughput scenarios. Worse applies to switches. So, if you're near the capacity of your network infrastructure, or your computational power, losses become far more likely.
So, in the end it's just a question on how high up in the networking stack you want to deal with errors: If you don't want to risk your application failing in 1 in 1e6 cases, you will need to add some flow/data integrity control; which really isn't that hard. If you can live with the fact that the average program has to be restarted every once in a while, well, that's error correction on user level...
Generally, I'd encourage you to not take risks. CPU power is just too cheap, and bandwidth, too, in most cases. Try ZeroMQ, which has broadcast communication models, and will ensure data integrity (and resend stuff if necessary), is available for practically all relevant languages, and runs on all relevant OSes, and is (at least from my perspective) easier to use than raw UDP sockets.
Related
Suppose, there is a network which gives a lot of Timeout errors when packets are transmitted over it. Now, timeouts can happen either because the network itself is inherently lossy (say, poor hardware) or it might be that the network is highly congested, due to which network devices are losing packets in between, leading to Timeouts. Now, what additional statistics about the traffic being transmitted (like Missing Packets errors etc.) are required that might help us to find out whether timeouts are happening due to poor hardware, or too much network load.
Please note that we have access only to one node in the network (from which we are transmitting packets) and as such, we cannot get to know the load being put by other nodes on the network. Similarly, we don't really have any information about the hardware being used in the network. Statistics is all that we have.
A network node only has hardware information about its local collision domain, which on a standard network will be the cable that links the host to the switch.
All the TCP stack will know about lost packets is that it is not receiving acknowledgements so it needs to resend, there is no mechanism for devices (E.g. switches & routers) between a source and destination to tell the source that there is a problem.
Without access to any other nodes the only way to ascertain if your problem is load based would be to run a test that sends consistent traffic over the network for a long period, if the packet retry count per second/minute/hour remains the same then it would suggest that there is a hardware issue, if the losses only occur during peak traffic periods then the issue could be load related. Of course there could be a situation where misconfigured hardware issues will only be apparent during high traffic periods, this takes things back to the main problem which is that you need access to network stats from beyond your single node.
In practice, nearly all loss on terrestrial network paths is due to either congestion or firewalls. Loss due to bit-errors is extremely rare. Even on wireless networks, forward error correction handles most bit/media/transmission errors. Congestion can be caused by a lot of different factors: any given network path will involve dozens of devices and if any one of them becomes overloaded for even a moment, packets will be dropped.
The only way to tell the difference between congestion induced packet loss and media errors is that media errors will occur independent of load. In other words, the loss rate will be the same whether you are sending a lot of data or only a little data.
To test that, you will need some control, or at least knowledge, of the load on the path. Since you don't have control and the only knowledge you have is from source-node observation, the best you can do is to take test samples (using ping is the easiest) around the clock and throughout the week, recording loss rates and latencies. These should give you an idea of when the path is relatively idle. If loss rates remain significant even when the path is (probably) idle, then there might be a media-loss issue. But again, that is extremely rare.
For background, I have written a few articles on the subject:
Loss, Latency, and Speed, discussing what statistics you can observe about a path and what they mean.
Common Network Performance Problems, discussing the most common components in a network path and how they affect performance (congestion).
So I'm writing a fairly simple game with very low networking requirements, I'm using TCP.
I'm unsure where to start in even defining/implementing a protocol for the client and server to use. I've been looking around and I've seen a few examples, for instance Mojang's Minecraft which uses a table of 'commands' the client sends the server and the server sends the client, with numbers of arguments and such.
What's a good way to do this? I've heard complaints about Minecraft's protocol because if you overread by a byte you ruin the entire stream.
Game networking is a broad question, depending on what type of problem you are solving. TCP (may) not even be the correct choice for you.
For example - games that send movement of characters is typically done with UDP. The reason being that character movement isn't critical to the operation of the game, so some data loss of movement is "acceptable". That may be why sometimes your character "jumps" - some UDP packets were lost, or severely out-of-order.
UDP is argued as the preferred protocol for networked games. So before you even get started, carefully consider whether you are even picking the correct protocol.
Overall, I consider Glenn Fiedler's series on developing a networked game a fantastic read. I'd start here. He covers all of the basics of using UDP for gaming.
If you want to use TCP simply just to get a handle on TCP - then Minecraft is a reasonable example. A known list of commands that can be sent back and forth is a simple way to start. However, as you stated, is prone to some problems. This is more aligned with using the wrong protocol than how it was developed.
Google "game networking library" and you'll get a bunch of results. GNE would be a good one to look at.
I guess it depends on what your game is, what it mechanics are, what information is necessary. In any case I think this stack exchange https://gamedev.stackexchange.com/ is more suited to answer your question.
Gamedev.net's networking forum has a great FAQ covering these sorts of questions and many others, however, to make this more than a 'go-there-look-at-that' answer, I'll suggest some small improvements you can make. When using tcp, delivery is guarenteed, but this has a speed cost, which is fine if your not making a fps, but it means you need to get more from the data you do send, a great way to do this is via deltas/differentials, that is, sending only the change in state, not the entire game state, you can also validate your incoming packets for corrupt/anomalys data over and about tcp checks by predicting possibilities are allow, and with the same prediction, you can cut out even more data etc. But as others have said, this is a broad question, and not suited to getting truely helpful answers
As you're coding in lua, the only library anyone uses is luasocket (though ZMQ is gaining ground).
You're really going to have several protocols going: TCP for data that must be received (eg, server commands such as changemap or you_got_kicked, conversations and such; then use UDP for non-compulsory data, or data that quickly expires (eg, character positions).
Imagine you have many clustered servers, across many hosts, in a heterogeneous network environment, such that the connections between servers may have wildly varying latencies and bandwidth. You want to build a map of the connections between servers by transferring data between them.
Of course, this map may become stale over time as the network topology changes - but lets ignore those complexities for now and assume the network is relatively static.
Given the latencies between nodes in this host graph, calculating the bandwidth is a relative simply timing exercise. I'm having more difficulty with the latencies - however. To get round-trip time, it is a simple matter of timing a return-trip ping from the local host to a remote host - both timing events (start, stop) occur on the local host.
What if I want one-way times under the assumption that the latency is not equal in both directions? Assuming that the clocks on the various hosts are not precisely synchronized (at least that their error is of the the same magnitude as the latencies involved) - how can I calculate the one-way latency?
In a related question - is this asymmetric latency (where a link is quicker in direction than the other) common in practice? For what reasons/hardware configurations? Certainly I'm aware of asymmetric bandwidth scenarios, especially on last-mile consumer links such as DSL and Cable, but I'm not so sure about latency.
Added: After considering the comment below, the second portion of the question is probably better off on serverfault.
To the best of my knowledge, asymmetric latencies -- especially "last mile" asymmetries -- cannot be automatically determined, because any network time synchronization protocol is equally affected by the same asymmetry, so you don't have a point of reference from which to evaluate the asymmetry.
If each endpoint had, for example, its own GPS clock, then you'd have a reference point to work from.
In Fast Measurement of LogP Parameters
for Message Passing Platforms, the authors note that latency measurement requires clock synchronization external to the system being measured. (Boldface emphasis mine, italics in original text.)
Asymmetric latency can only be measured by sending a message with a timestamp ts, and letting the receiver derive the latency from tr - ts, where tr is the receive time. This requires clock synchronization between sender and receiver. Without external clock synchronization (like using GPS receivers or specialized software like the network time protocol, NTP), clocks can only be synchronized up to a granularity of the roundtrip time between two hosts [10], which is useless for measuring network latency.
No network-based algorithm (such as NTP) will eliminate last-mile link issues, though, since every input to the algorithm will itself be uniformly subject to the performance characteristics of the last-mile link and is therefore not "external" in the sense given above. (I'm confident it's possible to construct a proof, but I don't have time to construct one right now.)
There is a project called One-Way Ping (OWAMP) specifically to solve this issue. Activity can be seen in the LKML for adding high resolution timestamps to incoming packets (SO_TIMESTAMP, SO_TIMESTAMPNS, etc) to assist in the calculation of this statistic.
http://www.internet2.edu/performance/owamp/
There's even a Java version:
http://www.av.it.pt/jowamp/
Note that packet timestamping really needs hardware support and many present generation NICs only offer millisecond resolution which may be out-of-sync with the host clock. There are MSDN articles in the DDK about synchronizing host & NIC clocks demonstrating potential problems. Timestamps in nanoseconds from the TSC is problematic due to core differences and may require Nehalem architecture to properly work at required resolutions.
http://msdn.microsoft.com/en-us/library/ff552492(v=VS.85).aspx
You can measure asymmetric latency on link by sending different sized packets to a port that returns a fixed size packet, like send some udp packets to a port that replies with an icmp error message. The icmp error message is always the same size, but you can adjust the size of the udp packet you're sending.
see http://www.cs.columbia.edu/techreports/cucs-009-99.pdf
In absence of a synchronized clock, the asymmetry cannot be measured as proven in the 2011 paper "Fundamental limits on synchronizing clocks over networks".
https://www.researchgate.net/publication/224183858_Fundamental_Limits_on_Synchronizing_Clocks_Over_Networks
The sping tool is a new development in this space, which uses clock synchronization against nearby NTP servers, or an even more accurate source in the form of a GNSS box, to estimate asymmetric latencies.
The approach is covered in more detail in this blog post.
I've been checking out using a system called ROS (http://www.ros.org) for some work.
There are lots of different types of data that get sent between network nodes in ROS.
You define a struct of data that you want to send in a message, and ROS will handle opening a specific port between the two nodes that will only send that struct of data.
So if there are 5 different messages, there will be 5 different ports.
As opposed to this scenario, I have seen other platforms that just push all the different messages across one port. This means that there needs to be a sort of multiplexing/demultiplexing (done by some sort of message parsing on the receivers end).
What I wonder is... which is better from a performance perspective?
Do operating systems switch based on ports quickly, so that a system like ROS doesn't have to do too much work to work out what is in the message and interpreting it?
OR
Is opening lots of ports going to mean lots of slower kernel calls, and the cost of having to work out and translate message types end up being more then the time spent switching between ports?
When this scales to a large amount of data at high rates and lots of different messages types there will be lots of ports. So I imagine that when scaling each of these topologies that performance will be a big factor in selecting the way to work.
I should also point out that these nodes usually exist on one small network, or most of the time on the one machine in which networking is used as a force of inter-process communication. So the transmission time is only a very small factor in the overall system timing.
ROS being an architecture for robots may have one node for every sensor and actuator, so depending on the complexity of your system we may be talking about 20-30 nodes pushing small-ish (100bytes or so) data between 10-100Hz
It depends. I do not know the specifics of ROS but in networking it comes down to the following constraints:
Distance: speed of light is fast but over a distance it starts making a difference
Protocol Overhead: connection oriented vs. connection-less
On the OS side, maintaining a list of free ports isn't such much of an overhead - of course there is a cost to it but everything is relative: if you are talking about a distributed system with long distance links, then it is easy to argue that cycling through OS network ports ranks as lower concern compared to managing communication quality.
Without a more specific question, I'll stop here.
I don't have any data on this, but it seems plausible that multiple ports might be handled more efficiently by multi-core systems, as opposed to demultiplexing within the program.
This Paper (When the CRC and TCP checksum disagree) suggests that since the TCP checksumming algorithm is rather weak, there would occur an undetected error every 16 million to 10 billion packets using TCP.
Are there any application developers out there who protect the data against such kind of errors by adding checksums at the application level?
Are there any patterns available to protect against such errors while doing EJB remote method invocation (Java EE 5)? Or does Java already checksum serialized objects automatically (additionally to the underlying network protocol)?
Enterprise software has been running on computers doing not only memory ECC, but also doing error checking within the CPU at the registers etc (SPARC and others). Bit errors at storage systems (hard drives, cables, ...) can be prevented by using Solaris ZFS.
I was never afraid of network bit errors because of TCP - until I saw that article.
It might not be that much work to implement application level checksumming for some very few client server remote interfaces. But what about distributed enterprise software that runs on many machines in a single datacenter. There can be a really huge number of remote interfaces.
Is every Enterprise Software vendor like SAP, Oracle and others just ignoring this kind of problem? What about banks? What about stock exchange software?
Follow up: Thank you very much for all your answers! So it seems that it is pretty uncommon to check against undetected network data corruption - but they do seem to exist.
Couldn't I solve this problem simply by configuring the Java EE Application Servers (or EJB deployment descriptors) to use RMI over TLS with the TLS configured to use MD5 or SHA1 and by configuring the Java SE clients to do the same? Would this be a way to get reliable transparent checksumming (although by overkill) so that I would not have to implement this at application level? Or am I completely confused network-stack wise?
I am convinced that every application that cares about data integrity should use a secure hash. Most, however, do not. People simply ignore the problem.
Although I have frequently seen data corruption over the years - even that which gets by checksums - the most memorable in fact involved a stock trading system. A bad router was corrupting data such that it usually got past the TCP checksum. It was flipping the same bit off and on. And of course, no one is alerted for the packets that in fact failed the TCP checksum. The application had no additional checks for data integrity.
The messages were things like stock orders and trades. The consequences of corrupting the data are as serious as it sounds.
Luckily, the corruption caused the messages to be invalid enough to result in the trading system completely crashing. The consequences of some lost business were nowhere near as severe as the potential consequences of executing bogus transactions.
We identified the problem with luck - someone's SSH session between two of the servers involved failed with a strange error message. Obviously SSH must ensure data integrity.
After this incident, the company did nothing to mitigate the risk of data corruption while in flight or in storage. The same code remains in production, and in fact additional code has gone into production that assumes the environment around it will never corrupt data.
This actually is the correct decision for all the individuals involved. A developer who prevents a problem that was caused by some other part of the system (e.g. bad memory, bad hard drive controller, bad router) is not likely to gain anything. The extra code creates the risk of adding a bug, or being blamed for a bug that isn't actually related. If a problem does occur later, it will be someone else's fault.
For management, it's like spending time on security. The odds of an incident are low, but the "wasted" effort is visible. For example, notice how end-to-end data integrity checking has been compared to premature optimization already here.
So far as things changing since that paper was written - all that has changed is we have greater data rates, more complexity to systems, and faster CPUs to make a cryptographic hash less costly. More chances for corruption, and less cost to preventing it.
The real issue is whether it is better in your environment to detect/prevent problems or to ignore them. Remember that by detecting a problem, it may become your responsibility. And if you spend time preventing problems that management does not recognize is a problem, it can make you look like you are wasting time.
I've worked on trading systems for IBs, and I can assure you there is no extra checksumming going on - most apps use naked sockets. Given the current problems in the financial sector, I think bad TCP/IP checksums should be the least of your worries.
Well, that paper is from 2000, so it's from a LONG time ago (man, am I old), and on a pretty limited set of traces. So take their figures with a huge grain of salt. That said, it would be interesting to see if this is still the case. However, I suspect things have changed, though some classes of errors may still well exist, such as hardware faults.
More useful than checksums if you really need the extra application-level assurance would be a SHA-N hash of the data, or MD5, etc.