TCP/IP Illustrated, an ongoing series covering the many facets of TCP/IP, brings a highly-effective visual approach to learning about this networking protocol. TCP/IP Illustrated, Volume 2 (paperback): The Implementation (Addison-Wesley Professional Read online, or download in secure PDF or secure EPUB format. Tcp Ip Illustrated Vol 2 - Free ebook download as PDF File .pdf), Text File .txt) or read Richard Stevens, TCP/IP Illustrated, Volume 2: The Implementation.
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TCP IP Illustrated, Volume 2: The implementation IP Illustrated: The Implementation. Read more · Modbus messaging on TCP-IP implementation dancindonna.info TCP IP Illustrated, Volume 2: The implementation IP Illustrated, Volume 1: The Protocols The Illustrated Encyclopedia of Hinduism (2 Volume Set). Editorial Reviews. From the Back Cover. TCP/IP Illustrated, an ongoing series covering the many facets of TCP/IP, brings a highly-effective visual approach to.
There isn't a more practical or up-to-date bookothis volume is the only one to cover the de facto standard implementation from the 4. You will learn about such topics as the relationship between the sockets API and the protocol suite, and the differences between a host implementation and a router. In addition, the book covers the newest features of the 4. Read more Collapse About the author Gary R. He is President of Connix, a Connecticut-based company providing Internet access and consulting services.
HDFS or S3. A client first acquires the lock, then reads the file, makes some changes, writes the modified file back, and finally releases the lock. The lock prevents two clients from performing this read-modify-write cycle concurrently, which would result in lost updates. The following diagram shows how you can end up with corrupted data: In this example, the client that acquired the lock is paused for an extended period of time while holding the lock — for example because the garbage collector GC kicked in.
The lock has a timeout i.
You cannot fix this problem by inserting a check on the lock expiry just before writing back to storage. Remember that GC can pause a running thread at any point, including the point that is maximally inconvenient for you between the last check and the write operation. Maybe your process tried to read an address that is not yet loaded into memory, so it gets a page fault and is paused until the page is loaded from disk.
Maybe there are many other processes contending for CPU, and you hit a black node in your scheduler tree. Your processes will get paused. This means that an application process may send a write request, and it may reach the storage server a minute later when the lease has already expired.
Even in well-managed networks, this kind of thing can happen. You simply cannot make any assumptions about timing, which is why the code above is fundamentally unsafe, no matter what lock service you use. Making the lock safe with fencing The fix for this problem is actually pretty simple: you need to include a fencing token with every write request to the storage service. In this context, a fencing token is simply a number that increases e.
This is illustrated in the following diagram: Client 1 acquires the lease and gets a token of 33, but then it goes into a long pause and the lease expires. Client 2 acquires the lease, gets a token of 34 the number always increases , and then sends its write to the storage service, including the token of Later, client 1 comes back to life and sends its write to the storage service, including its token value However, the storage server remembers that it has already processed a write with a higher token number 34 , and so it rejects the request with token Note this requires the storage server to take an active role in checking tokens, and rejecting any writes on which the token has gone backwards.
But this is not particularly hard, once you know the trick. And provided that the lock service generates strictly monotonically increasing tokens, this makes the lock safe.
However, this leads us to the first big problem with Redlock: it does not have any facility for generating fencing tokens. The algorithm does not produce any number that is guaranteed to increase every time a client acquires a lock. This means that even if the algorithm were otherwise perfect, it would not be safe to use, because you cannot prevent the race condition between clients in the case where one client is paused or its packets are delayed. The unique random value it uses does not provide the required monotonicity.
Simply keeping a counter on one Redis node would not be sufficient, because that node may fail. Keeping counters on several nodes would mean they would go out of sync.
If only incrementing a counter was simple. Using time to solve consensus The fact that Redlock fails to generate fencing tokens should already be sufficient reason not to use it in situations where correctness depends on the lock.
But there are some further problems that are worth discussing. In plain English, this means that the algorithms make no assumptions about timing: processes may pause for arbitrary lengths of time, packets may be arbitrarily delayed in the network, and clocks may be arbitrarily wrong — and the algorithm is nevertheless expected to do the right thing.
Given what we discussed above, these are very reasonable assumptions.
The only purpose for which algorithms may use clocks is to generate timeouts, to avoid waiting forever if a node is down. When used as a failure detector, timeouts are just a guess that something is wrong. Note that Redis uses gettimeofday , not a monotonic clock , to determine the expiry of keys. The man page for gettimeofday explicitly says that the time it returns is subject to discontinuous jumps in system time — that is, it might suddenly jump forwards by a few minutes, or even jump back in time e.
Thus, if the system clock is doing weird things, it could easily happen that the expiry of a key in Redis is much faster or much slower than expected. Only liveness properties depend on timeouts or some other failure detector.
In plain English, this means that even if the timings in the system are all over the place processes pausing, networks delaying, clocks jumping forwards and backwards , the performance of an algorithm might go to hell, but the algorithm will never make an incorrect decision. However, Redlock is not like this. Its safety depends on a lot of timing assumptions: it assumes that all Redis nodes hold keys for approximately the right length of time before expiring; that the network delay is small compared to the expiry duration; and that process pauses are much shorter than the expiry duration.
What happens if a clock on one of the Redis nodes jumps forward? Client 1 acquires lock on nodes A, B, C. Due to a network issue, D and E cannot be reached. The clock on node C jumps forward, causing the lock to expire. Client 2 acquires lock on nodes C, D, E.
Due to a network issue, A and B cannot be reached. Clients 1 and 2 now both believe they hold the lock. A similar issue could happen if C crashes before persisting the lock to disk, and immediately restarts. For this reason, the Redlock documentation recommends delaying restarts of crashed nodes for at least the time-to-live of the longest-lived lock. App sourceB describes how to obtain this source code.
The 4. This earlier volume is referred to throughout the current text as Volume 1. The current text also assumes a basic understanding of operating system principles. We describe the implementation of the protocols using a data-structures approach.
That is, in addition to the source code presentation, each chapter contains pictures and descriptions of the data structures used and maintained by the source code. Heavy use is made of diagrams throughout the text - there are over diagrams.
This data-structures approach allows readers to use the book in various ways. Those interested in all the implementation details can read the entire text from start to finish, following through all the source code. Others might want to understand how the protocols are implemented by understanding all the data structurestand reading all the text, but not following through all the source code. We anticipate that many readers are interested in specific portions of the book and will want to go directly to those chapters.
Therefore many forward and backward references are provided throughout the text, along with a thorough index, to allow individual chapters to be studied by themselves. The inside back covers contain an alphabetical cross-reference of all the functions and macros described in the book and the starting page number of the description.
Exercises are provided at the end of the chapters; most solutions are in Appendix A to maximize the usefulness of the text as a self-study reference. Source Code Copyright All of the source code presented in this book, other than Figures 1.
This software is publicly available through many sources Appendix B.