Proving distributed algorithms for mobile agents: Examples of spanning tree computation in dynamic networks

2015 ◽  
Author(s):  
Mouna Ktari ◽  
Mohamed Amine Haddar ◽  
Ahmed Hadj Kacem ◽  
Mohamed Mosbah
Keyword(s):  
Distributed Algorithms ◽  
Mobile Agents ◽  
Spanning Tree ◽  
Dynamic Networks

scholarly journals Maintenance of a Spanning Tree For Dynamic Graphs by Mobile Agents and Local Computations

2017 ◽  
Vol 51 (2) ◽  
pp. 51-70
Author(s):  
Mouna Ktari ◽  
Mohamed Amine Haddar ◽  
Mohamed Mosbah ◽  
Ahmed Hadj Kacem
Keyword(s):  
Mobile Agent ◽  
Mobile Agents ◽  
Distributed Algorithm ◽  
Spanning Tree ◽  
Dynamic Networks ◽  
Communication Channels ◽  
Dynamic Graphs ◽  
Computing Environment ◽  
Computation Model ◽  
Local Computation

The problem of constructing and maintaining a spanning tree in dynamic networks is important in distributed systems. Trees are essential structures in various communication protocols such as information broadcasting, routing, etc. In a distributed computing environment, the solution of this problem has many practical motivations. To make designing distributed algorithm easier, we model this latter with a local computation model. Based on the mobile agent paradigm, we present in this paper a distributed algorithm that maintain a hierarchical spanning tree in dynamic networks. We study all topological events that may affect the structure of the spanning tree: we address the appearance and the disappearance of places and communication channels.

Distributed Algorithms for Delay Bounded Minimum Energy Wireless Broadcasting

2010 ◽  
pp. 1677-1697
Author(s):  
Serkan Çiftlikli ◽  
Figen Öztoprak ◽  
Özgür Erçetin ◽  
Kerem Bülbül
Keyword(s):  
Distributed Algorithms ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Minimum Energy ◽  
Transmission Power ◽  
Message Complexity ◽  
Delay Constraint ◽  
Delay Bound ◽  
Lower Power ◽  
Tree Expansion

In this article, we investigate two different distributed algorithms for constructing a minimum power broadcast tree with a maximum depth ? which corresponds to the maximum tolerable end-to-end delay in the network. Distributed Tree Expansion (DTE) is based on an implementation of a distributed minimum spanning tree algorithm in which the tree grows at each iteration by adding a node that can cover the maximum number of currently uncovered nodes in the network with minimum incremental transmission power and without violating the delay constraint. In Distributed Link Substitution (DLS), given a feasible broadcast tree, the solution is improved by replacing expensive transmissions by transmissions at lower power levels while reserving the feasibility of the tree with respect to the delay bound. Although DTE increases the message complexity to O(n3) from O(n2?) in a network of size n, it provides up to 50% improvement in total expended power compared to DLS.

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