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A sliding window protocol is a feature of packet-based data transmission protocols. Sliding window protocols are used where reliable in-order delivery of packets is required, such as in the data link layer ( OSI layer 2 ) as well as in the Transmission Control Protocol (i.e., TCP windowing ).
Note how the algorithm is greedy, and so nothing is added to the table until a unique making token is found. The algorithm is to initialize last matching index = 0 and next available index = 1 and then, for each token of the input stream, the dictionary searched for a match: {last matching index, token}. If a match is found, then last matching ...
Some variants are commonly referred to as square-and-multiply algorithms or binary exponentiation. These can be of quite general use, for example in modular arithmetic or powering of matrices. For semigroups for which additive notation is commonly used, like elliptic curves used in cryptography , this method is also referred to as double-and-add .
An encoded match to an earlier string consists of an 8-bit length (3–258 bytes) and a 15-bit distance (1–32,768 bytes) to the beginning of the duplicate. Relative back-references can be made across any number of blocks, as long as the distance appears within the last 32 KiB of uncompressed data decoded (termed the sliding window).
Go-Back-N ARQ is a specific instance of the automatic repeat request (ARQ) protocol, in which the sending process continues to send a number of frames specified by a window size even without receiving an acknowledgement (ACK) packet from the receiver.
A stop-and-wait ARQ sender sends one frame at a time; it is a special case of the general sliding window protocol with transmit and receive window sizes equal to one in both cases. After sending each frame, the sender doesn't send any further frames until it receives an acknowledgement (ACK) signal.
All three protocols usually use some form of sliding window protocol to help the sender determine which (if any) packets need to be retransmitted. These protocols reside in the data link or transport layers (layers 2 and 4) of the OSI model .
The general algorithm involves message passing and is substantially similar to the belief propagation algorithm (which is the generalization of the forward-backward algorithm). With an algorithm called iterative Viterbi decoding , one can find the subsequence of an observation that matches best (on average) to a given hidden Markov model.