Abstract
Background: Because of some inherent characteristics of MANETs such as infrastructural instability, limitations and shortcomings, multi-hop communication, wireless media and dynamic topology, routing has emerged as the most important challenge in these networks. This prompted a wealth of research which attempted to improve the routing quality through focusing on various qualitative criteria.
Objective: However, these researches have not adequately addressed the applied characteristics of MANETs as the most important capability of such networks. In other words, application of these networks in different fields have warranted the development of different services with varying Quality-of-Service requirements. This requires the network to support the quality of various services in proportion with the varying qualitative requirements of transaction services.
Methods: In order to efficiently address this issue, this research introduces an enhanced protocol dubbed MMSR-AOMDV based on the development of basic AOMDV protocol and reaping the benefits of Fuzzy Logic. MMSR-AOMDV is a double-step protocol that attempts to enable distinguishing transaction services and supporting the various services associated with the specific demands and requirements of each service based on the performance in each step. For this, MMSRAOMDV has been developed in a way to enable in the first step the assessment of qualitative indicators which are associated with the requirements of the services sent via utilizing multi-route routing and classification techniques, while the second step has been dedicated to offering effective support for multi-service routing quality thanks to the merits of Fuzzy Logic features.
Results and Conclusion: The simulation of the proposed protocol using OPNET simulator revealed that in terms of end-to-end delays, packet lost, network throughput and data reception rate, MMSR-AOMDV significantly outperformed other corresponding methods.
Keywords: MANETs, routing protocol, quality-of-service, transaction services, fuzzy logic, AOMDV.
Graphical Abstract
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