To solve the problem of slow traversal speed and the low recovery efficiency of source data packets in the existing coding schemes, we study a redundant quasi-randomized network coding based data storage algorithm-QRNCDS based on the

minimum spanning tree. In the process of traverse the whole network node, by applying the

minimum spanning tree rules, QRNCDS can reduce the forwarding number of each source packet to n-1 times.

To avoid some of the biases in traditional network analyses [49], we used the

minimum spanning tree (MST) that allows for an unbiased topological interpretation of the results [50, 51].

A constrained

minimum spanning tree T of G' (figure-2.c) using Prims technique [24] is constructed, with the following critical measure [C.sub.n] and congestion factor f that decides the particular edge is added or subtracted at every iteration.

The

minimum spanning tree is a simple acyclic connected subgraph of the original weighted network that can be used to direct comparison of networks with the same number of nodes and simplifies the network characterization.

Construction of the High-Order

Minimum Spanning Tree Network

A survey on multi-objective

minimum spanning tree problem is available in [21].

In [6], the authors have also discussed adding a redundancy level to the Elastic tree by adding k parallel

Minimum Spanning Trees (MSTs) that overlap at the edge switches.

The results are analysed in section 3 where we compare the performance of the proposed algorithm with respect to a

Minimum spanning tree under a given set of protocols.

In EMST or LEMST, each node builds its overall or local

minimum spanning tree based on Euclidean distance and only keeps nodes on tree that is one hop away as its neighbors.

Constraint (1) indicates setting the

minimum spanning tree water of the water plant k water demand point range in the area as a dry pipe installation route.

From this watershed, the adjacency graph is constructed and a

minimum spanning tree is extracted.

Lines 11-14 select the minimum edge to form

minimum spanning tree and update the key (key [v]) and the parents fields ([pi] [u]) of every vertex v adjacent to u but not in the tree.