List of Articles Spanning Tree

• Open Access Article
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  1 - Load Balanced Spanning Tree in Metro Ethernet Networks
  Ghasem Mirjalily Samira Samadi
  10.7508/jist.2014.02.007
  Spanning Tree Protocol (STP) is a link management standard that provides loop free paths in Ethernet networks. Deploying STP in metro area networks is inadequate because it does not meet the requirements of these networks. STP blocks redundant links, causing the risk of More

  Spanning Tree Protocol (STP) is a link management standard that provides loop free paths in Ethernet networks. Deploying STP in metro area networks is inadequate because it does not meet the requirements of these networks. STP blocks redundant links, causing the risk of congestion close to the root. As a result, STP provides poor support for load balancing in metro Ethernet networks. A solution for this problem is using multi-criteria spanning tree by considering criterions related to load balancing over links and switches. In our previous work, an algorithm named Best Spanning Tree (BST) is proposed to find the best spanning tree in a metro Ethernet network. BST is based on the computation of total cost for each possible spanning tree; therefore, it is very time consuming especially when the network is large. In this paper, two heuristic algorithms named Load Balanced Spanning Tree (LBST) and Modified LBST (MLBST) will be proposed to find the near-optimal balanced spanning tree in metro Ethernet networks. The computational complexity of the proposed algorithms is much less than BST algorithm. Furthermore, simulation results show that the spanning tree obtained by proposed algorithms is the same or similar to the spanning tree obtained by BST algorithm. Manuscript profile
• Open Access Article
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  2 - A New Algorithm Based on Distributed Learning Automata for Solving Stochastic Linear Optimization Problems on the Group of Permutations
  mohammadreza mollakhalili meybodi masoumeh zojaji
  In the present research, a type of permutation optimization was introduced. It is assumed that the cost function has an unknown probability distribution function. Since the solution space is inherently large, solving the problem of finding the optimal permutation is com More

  In the present research, a type of permutation optimization was introduced. It is assumed that the cost function has an unknown probability distribution function. Since the solution space is inherently large, solving the problem of finding the optimal permutation is complex and this assumption increases the complexity. In the present study, an algorithm based on distributed learning automata was presented to solve the problem by searching in the permutation answer space and sampling random values. In the present research, in addition to the mathematical analysis of the behavior of the proposed new algorithm, it was shown that by choosing the appropriate values of the parameters of the learning algorithm, this new method can find the optimal solution with a probability close to 100% and by targeting the search using the distributed learning algorithms. The result of adopting this policy is to decrease the number of samplings in the new method compared to methods based on standard sampling. In the following, the problem of finding the minimum spanning tree in the stochastic graph was evaluated as a random permutation optimization problem and the proposed solution based on learning automata was used to solve it. Manuscript profile