An Advanced AOI-Cast Algorithm Based on PCA

2014 ◽  
Vol 945-949 ◽  
pp. 2523-2526
Author(s):  
Yan Wang
Keyword(s):  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Undirected Graph ◽  
Gaussian Function ◽  
Fibonacci Sequence ◽  
Multicast Tree ◽  
Child Node ◽  
Efficient Manner ◽  
Simulation Results ◽  
Node Capacity

Voronoi-based Overlay Network (VON) has been proposed that promises to maintain high overlay topology consistency in a bandwidth-efficient manner. VoroCast constructs a spanning tree across all AOI neighbors based on Voronoi diagrams, while FiboCast dynamically adjusts the messaging range by a Fibonacci sequence. VoroCast improves the AOI scalability of P2P-based NVEs. However, one potential drawback of the schemes is that the child node degrees are only based on peers' positions, but not node capacities. Since each node in VoroCast has different capacity, packet loss will be unavoidable. VoroCast may lead to lower multicast efficiency in AOI. To these problems, an Advanced AOI-cast algorithm based on PCA is presented. In the algorithm, node capacity is related to node CPU (c), node bandwidth (b) and node memory (m), and the node capacity is calculated according to the PCA. An undirected graph is formed through all the nodes in the AOI and the edge weights are calculated by the Gaussian function. Through the prim algorithm, to generate the minimum spanning tree of the weighted undirected graph, and the minimum spanning tree is used as the final multicast tree. The message is delivered through the multicast tree. The simulation results show that the algorithm gains a greater improvement on multicast efficiency, and achieves better scalability.

THREE TECHNIQUES FOR PARALLEL MAINTENANCE OF A MINIMUM SPANNING TREE UNDER BATCH OF UPDATES

1996 ◽  
Vol 06 (02) ◽  
pp. 213-222 ◽  
Author(s):  
PAOLO FERRAGINA ◽  
FABRIZIO LUCCIO
Keyword(s):  
Data Structure ◽  
Parallel Algorithms ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Undirected Graph ◽  
Batch Size ◽  
Insertions And Deletions ◽  
Erew Pram ◽  
Pram Model ◽  
Proper Values

In this paper we provide three simple techniques to maintain in parallel the minimum spanning tree of an undirected graph under single or batch of edge updates (i.e., insertions and deletions). Our results extend the use of the sparsification data structure to the EREW PRAM model. For proper values of the batch size, our algorithms require less time and work than the best known dynamic parallel algorithms.

scholarly journals Automatically Produced Algorithms for the Generalized Minimum Spanning Tree Problem

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Carlos Contreras-Bolton ◽  
Carlos Rey ◽  
Sergio Ramos-Cossio ◽  
Claudio Rodríguez ◽  
Felipe Gatica ◽  
...  
Keyword(s):  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Undirected Graph ◽  
Minimum Cost ◽  
Practical Applications ◽  
Minimum Spanning Tree Problem ◽  
Generalized Minimum Spanning Tree ◽  
Np Hardness ◽  
New Algorithms

The generalized minimum spanning tree problem consists of finding a minimum cost spanning tree in an undirected graph for which the vertices are divided into clusters. Such spanning tree includes only one vertex from each cluster. Despite the diverse practical applications for this problem, the NP-hardness continues to be a computational challenge. Good quality solutions for some instances of the problem have been found by combining specific heuristics or by including them within a metaheuristic. However studied combinations correspond to a subset of all possible combinations. In this study a technique based on a genotype-phenotype genetic algorithm to automatically construct new algorithms for the problem, which contain combinations of heuristics, is presented. The produced algorithms are competitive in terms of the quality of the solution obtained. This emerges from the comparison of the performance with problem-specific heuristics and with metaheuristic approaches.

scholarly journals Automatic Distributing Schemes of Physical Cell Identity for Self-Organizing Networks

2012 ◽  
Vol 8 (10) ◽  
pp. 973713 ◽  
Author(s):  
Yao Wei ◽  
Mugen Peng ◽  
Wenbo Wang ◽  
Shijun Min ◽  
Jia Mo Jiang ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Layered Structure ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
The Self ◽  
Correlation Property ◽  
Cell Identity ◽  
Simulation Results ◽  
Physical Cell Identity ◽  
Self Organizing

This paper presents and puts forward an optimal automatic distributing of physical cell identity (ADPCI) scheme for the self-organizing network (SON). Considering the high number and the layered structure of the evolved node B (eNodeB, eNB) in the initial rollout phase, the assigning of PCI for cells would be quite complex. The PCI self-distributing problem is mapped to the well-known minimum spanning tree (MST) problem in order to optimize the PCI reuse distance and decrease the multiplexing interference. The correlation property of PCI is analyzed and taken into consideration in the assigning phase. Moreover, a suboptimal algorithm (SADPCI) is presented as it performs approximately to ADPCI but the computational complexity is lower. To demonstrate the proposal validity, performances of ADPCI and SADPCI are evaluated. Simulation results illustrate that these schemes can achieve significantly higher performance even under the condition of severe PCI deficiency.

scholarly journals Polynomial Time Approximation Schemes for the Constrained Minimum Spanning Tree Problem

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Yen Hung Chen
Keyword(s):  
Weight Function ◽  
Polynomial Time ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Undirected Graph ◽  
Minimum Cost ◽  
Approximation Schemes ◽  
Time Approximation ◽  
Minimum Spanning Tree Problem ◽  
Polynomial Time Approximation

LetG=(V,E)be an undirected graph with a weight function and a cost function on edges. The constrained minimum spanning tree problem is to find a minimum cost spanning treeTinGsuch that the total weight inTis at most a given boundB. In this paper, we present two polynomial time approximation schemes (PTASs) for the constrained minimum spanning tree problem.

scholarly journals AN APPROACH TO GENERATE MST WITHOUT CHECKING CYCLE

2005 ◽  
Vol 4 (2) ◽  
pp. 408-418
Author(s):  
Sharadindu Roy ◽  
Prof. Samar Sen Sarma
Keyword(s):  
Spanning Tree ◽  
Time Complexity ◽  
Minimum Spanning Tree ◽  
Undirected Graph ◽  
Good Time ◽  
Internet Service ◽  
Large Graphs ◽  
Real World Applications ◽  
Np Hard Problem ◽  
Better Than

Abstract: A minimum spanning tree of an undirected graph can be easily obtained using classical algorithms by Prim or Kruskal. MST generation is a NP hard problem. Now this paper represents an algorithm to find minimum spanning tree without checking cycle. Good time and space complexities are the major concerns of this algorithm. Running Time (complexity) of this algorithm = O(E*log V) (E = edges, V = nodes),which is obviously better than prim’s algorithm(complexity- E +Vlog V) .  This algorithms operate at O(E * log(V)) time, though Prim’s can be optimized to O(E + V log V) by using specialized data structures(heap). For large graphs, these algorithms can take significant amount of time to complete. This algorithm is important in many real world applications. One example is an internet service provider determining the best way to install underground wires in a neighbourhood in order to use the least amount of wire and dig the least amount of ground.

AN EREW PARM ALGORITHM FOR UPDATING MINIMUM SPANNING TREES

1999 ◽  
Vol 09 (01) ◽  
pp. 111-122 ◽  
Author(s):  
SAJAL K. DAS ◽  
PAOLO FERRAGINA
Keyword(s):  
Data Structure ◽  
Spanning Tree ◽  
Spanning Trees ◽  
Minimum Spanning Tree ◽  
Undirected Graph ◽  
Substantial Improvement ◽  
Minimum Spanning Trees ◽  
Single Edge ◽  
Sequential Approach ◽  
Work Complexity

We propose a parallel algorithm for the EREW PRAW model that maintains a minimum spanning tree (MST) of an undirected graph under single edge insertions and deletions. For a graph of n nodes and m edges, each update requires O( log n) time and O(m 2/3 log n) work. This is a substantial improvement over the known bounds on the work complexity. Our algorithm uses a partition of the MST, similar to the sequential approach due to Frederickson [6], and also employs a novel data structure for efficiently managing edge insertions in parallel.

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