Shahzad Rizwan

Mr. Shahzad Rizwan


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 June 2023 in Sensors
Verified
Journal Article
Open access
PDF file
Farhan JavedFarhan Javed
Farhan Javed
ZKZuhaib Ashfaq Khan
Zuhaib Ashfaq Khan
SRShahzad Rizwan
Shahzad Rizwan
SSSonia Shahzadi
Sonia Shahzadi
NCNaumanRiaz Chaudhry
NaumanRiaz Chaudhry
MIMuddesar Iqbal
Muddesar Iqbal
The roadside unit (RSU) is one of the fundamental components in a vehicular ad hoc network (VANET), where a vehicle communicates in infrastructure mode. The RSU has multiple functions, including the sharing of emergency messages and the updating of vehicles about the traffic situation. Deploying and managing a static RSU (sRSU) requires considerable capital and operating expenditures (CAPEX and OPEX), leading to RSUs that are sparsely distributed, continuous handovers amongst RSUs, and, more importantly, frequent RSU interruptions. At present, researchers remain focused on multiple parameters in the sRSU to improve the vehicle-to-infrastructure (V2I) communication; however, in this research, the mobile RSU (mRSU), an emerging concept for sixth-generation (6G) edge computing vehicular ad hoc networks (VANETs), is proposed to improve the connectivity and efficiency of communication among V2I. In addition to this, the mRSU can serve as a computing resource for edge computing applications. This paper proposes a novel energy-efficient reservation technique for edge computing in 6G VANETs that provides an energy-efficient, reservation-based, cost-effective solution by introducing the concept of the mRSU. The simulation outcomes demonstrate that the mRSU exhibits superior performance compared to the sRSU in multiple aspects. The mRSU surpasses the sRSU with a packet delivery ratio improvement of 7.7%, a throughput increase of 5.1%, a reduction in end-to-end delay by 4.4%, and a decrease in hop count by 8.7%. The results are generated across diverse propagation models, employing realistic urban scenarios with varying packet sizes and numbers of vehicles. However, it is important to note that the enhanced performance parameters and improved connectivity with more nodes lead to a significant increase in energy consumption by 2%.

18 October 2019
Verified
Book Chapter
Closed access
PDF file
Tehreem AshfaqTehreem Ashfaq
Tehreem Ashfaq
MYMuhammad Ahmed Younis
Muhammad Ahmed Younis
SRShahzad Rizwan
Shahzad Rizwan
ZIZahid Iqbal
Zahid Iqbal
SMShahid Mehmood
Shahid Mehmood
Nadeem JavaidNadeem Javaid
Nadeem Javaid