Investigation of the Bellman-Ford Algorithm Enhanced for Remote Execution

This paper discusses several improvements for the Bellman-Ford algorithm that increase its performance. Following the trends, centralization becomes more and more popular. The most common applications today are located in Cloud environments. This work is a fraction of the big issue: intelligent cont...

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Published in2019 3rd International Conference on Advanced Information and Communications Technologies (AICT) pp. 204 - 208
Main Authors Faychuk, Valentyn, Lavriv, Orest, Klymash, Mykhailo, Zhebka, Viktoriia, Shpur, Olga
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2019
Subjects
algorithm complexity
Bellman-Ford
cluster
Clustering algorithms
Complexity theory
CPU
IoT
JSON
Python
RAM
Random access memory
Routing
Sensors
Topology
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DOI10.1109/AIACT.2019.8847727

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Summary:This paper discusses several improvements for the Bellman-Ford algorithm that increase its performance. Following the trends, centralization becomes more and more popular. The most common applications today are located in Cloud environments. This work is a fraction of the big issue: intelligent control over the IoT clusters. The partial solution for performing the control can be reached through adjusting the routing policy in a cluster remotely. And, finally, the routing policy of finding the shortest in a Hop count context paths can be established using the Bellman-Ford algorithm. The efficiency of this algorithm is a key point for performing pat control over changes in the clusters. Throughout the research, we have developed two versions of the Bellman-Ford algorithm: classical and enhanced. Although we have examined both versions experimentally and studied the total gain from using the enhanced version instead of the plain one.
DOI:10.1109/AIACT.2019.8847727