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2021, Volume 22, Issue 9

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Frontiers of Information Technology & Electronic Engineering >> 2021, Volume 22, Issue 9 doi: 10.1631/FITEE.2000260

A cooperative heterogeneous vehicular clustering framework for efficiency improvement

Affiliation(s): Department of Computer Science and Information Technology, Mirpur University of Science and Technology, Mirpur-10250 (AJK), Pakistan; Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia; Department of Software Engineering, University of Kotli, AJK 11100, Pakistan; Department of Mechanical Engineering, Mirpur University of Science and Technology, Mirpur-10250 (AJK), Pakistan; Department of Mechanical Engineering, Faculty of Mechanical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia; Ingenium Research Group, University of Castilla-La Mancha, Spain; less

Received: 2020-05-31 Accepted: 2021-09-10 Available online: 2021-09-10
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Abstract

Heterogeneous ing integrates multiple types of communication networks to work efficiently for various vehicular applications. One popular form of heterogeneous network is the integration of long-term evolution (LTE) and dedicated short-range communication. The of such a network infrastructure and the non- involved in sharing cost/data are potential problems to solve. A ing framework is one solution to these problems, but the framework should be formally verified and validated before being deployed in the real world. To solve these issues, first, we present a heterogeneous framework, named destination and interest-aware clustering, for ing that integrates vehicular ad hoc networks with the LTE network for improving road traffic efficiency. Then, we specify a model system of the proposed framework. The model is formally verified to evaluate its performance at the functional level using a model checking technique. To evaluate the performance of the proposed framework at the micro-level, a heterogeneous simulation environment is created by integrating state-of-the-art tools. The comparison of the simulation results with those of other known approaches shows that our proposed framework performs better.

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