Skip to main content

Reliable User Datagram Protocol

RUDP provides a solution where UDP is too primitive because guaranteed-order packet delivery is desirable, but TCP adds too much overhead. 
In order for RUDP to gain higher Quality of Service, RUDP implements features that are similar to TCP with less overhead.

Implementations:

In order to ensure quality, it extends UDP by means of adding the following features:
  1. Acknowledgment of received packets
  2. Flow control
  3. Re-transmission of lost packets
  4. Over buffering (Faster than real-time streaming)
RUDP is not currently a formal standard, however it was described in an n 1999. It has not been proposed for standardization.

Working Example:

  1. One way to think about how RUDP types of transport work is to use a basic model where all the data is sent in UDP format, and each missing packet is indexed. 
  2. Once the main body of the transfer is done, the recipient sends the sender the index list and the sender re-transmits only those packets on the list. 
  3. As you can see, because it avoids the re-transmission of any windows of data that have already been sent that immediately follow a missed packet, this simple model is much more efficient. 
  4. However, it couldn't work for live data, and even for archives a protocol must be agreed upon for sending the index. 

Probably because of the "task-specific" nature of RUDP implementations, though, RUDP hasn't become a formal standard.

Comments

  1. so for missed packets it will follow sr or gbn protocol and only difference is in main packet size?

    ReplyDelete
  2. for missed packets it will not follow any of it...it will store the information that which packets got missed.
    And then when whole msg got received it will send the list of missing packets to sender.

    So need of SR or GBN in this scenario.

    ReplyDelete

Post a Comment

Popular posts from this blog

Goodness of Fit Test for normal and poisson distribution

Meaning of Goodness of fit test: We find out which distribution fits the sample data the most. And this is achieved using chi-square distribution (Snedecor and Cochran, 1989). How to apply: There are 4 steps to follow: State the hypothesis:  Data follows a distribution or not Criteria to reject null hypothesis: if Χ 2  > Χ 2 (k,1-α) then reject null hypothesis. Analyze sample data: Compute the chi-square value using below formula: ∑(Oi- Ei) 2 /Ei        : Oi is observed frequency and Ei is expected frequency Interpret the results: Declare the results after comparing the values of Χ 2 and Χ 2 (k,1-α), where k is degree of freedom and  α is significance level. Degree of Freedom: It is  =  n - 1 - m m: number of parameter in the distribution. So in case of normal distribution m is 2 ( μ ,α) and in case of poisson dist. m is = 1 ( λ). Example 1: Goodness of fit test for Normal Distribution Year wise d...

Bounding Rank of Fibonacci Heap

Bounding Rank of Fibonacci Heap to lgn: Before understanding the concept see below notations, tree(H)=number of nodes in the root list in below Fibonacci Heap Example rank(x)=number of children it has rank(H)=max rank(x)  Note: Black nodes are marked nodes (when one of its children is deleted it is marked if it is not already marked). We have following operation in Fibonacci Heap: Insert - O(1) Union - O(1) Decrease Key - O(1) Delete-Min - O(Rank(H)) = O(lgn) Delete - O(Rank(H)) = O(lgn) In this blog we will see how the rank is bounded to be lgn . So some assumptions I have made that you know at a time we cannot delete >1 child of any node. And after deleting child of a node we make it as Marked Node  if it is not marked already. Some Background; Merge Operation: We do merge operation when we do delete minimum. Merge operation is when rank of two nodes is same, we merge them as making minimum of them as root node and o...