Performance Evaluation of Routing Protocols for BIG Data Application

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Abstract

In the last years, the rapid growth in network communications necessitates the deep knowledge of the process called routing. To be more specific, routes of information (packets) are held on the device called router, which is responsible for the optimal transmission of pieces of data (packets) from the source to the destination by using the routing protocols and routing algorithms, which cooperate for the search and the selection of the best path. There are two different types of routing process: static routing, which is done manually by the administrator of the network and dynamic routing, which is done automatically through the usage of routing protocols. Static routing protocol is used when the network architecture is simple, while dynamic routing protocols are used when the architecture complexity increases. There are various types of dynamic routing protocols being widely used. The three categories of dynamic routing protocols are the distance-vector protocols like RIP, which uses the Bellman-Ford algorithm, the link-state routing protocols like OSPF, which uses the Dijkstra algorithm, and a hybrid type of routing protocol like EIGRP, which uses an algorithm called Dual. In this paper, we will not only illustrate a comparative analysis of the characteristics and the metrics of dynamic routing protocols, but we will also compare the performance of different Interior Gateway routing protocols, like EIGRP, OSPF, and RIP, in real-time applications big data, video conferencing, and VoIP, based on end-to-end packet delay, network convergence duration, packet delay variation, and Jitter of VoIP by using Riverbed Modeller simulator. Our aim is to show how dynamic routing protocols perform in real-time applications, while some failures happen on different network links.

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Balasas, E., Psannis, K. E., & Roumeliotis, M. (2019). Performance Evaluation of Routing Protocols for BIG Data Application. In Springer Proceedings in Business and Economics (pp. 75–87). Springer Science and Business Media B.V. https://doi.org/10.1007/978-3-319-95666-4_6

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