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All Journal Emerging Science Journal
Satyanand Singh
School of Electrical & Electronics Engineering, Fiji National University,
Environmental Science

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Impact of Projects with Future Potential on the Global Competitiveness Index of Countries Akbota Akzambekkyzy; Laszlo Vasa; Jeffrey Yi-Lin Forrest; Shynara Sarkambayeva; Satyanand Singh
Emerging Science Journal Vol 8, No 2 (2024): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-02-012

Abstract

The concept of project success has evolved from the perspective of conforming to the project triangle to that of benefiting the environment, and then from the perspective of the following generation. Scientists increasingly assert that successful projects require a set of criteria that include such item(s) as future potential. The meaning of project success varies depending on where it is executed. The purpose of this study is to identify whether projects with future potential have a certain effect on indicators of the Global Competitiveness Index (GCI) of the Republic of Kazakhstan (RK) and what other success criteria are inherent in such projects. By using the method of descriptive analysis of data collected from 107 experts and analyzing 19 influential projects, the study revealed that projects oriented towards the future have a significant impact on the indicators of the GCI in the RK. This finding confirms the necessity of considering the long-term sustainability and social significance of projects when assessing their successes. Additionally, a specific combination of success criteria that contributes most to this impact was identified. This research provides a brand-new understanding of project success criteria in the context of their impact on the GCI and emphasizes the importance of considering future potential in project planning and evaluation. Doi: 10.28991/ESJ-2024-08-02-012 Full Text: PDF
Design and Analysis of a Bandwidth Aware Adaptive Multipath N-Channel Routing Protocol for 5G Internet of Things (IoT) Satyanand Singh; Joanna Rosak-Szyrocka; Balàzs Lukàcs
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-018

Abstract

Large numbers of mobile wireless nodes that can move randomly and join or leave the network at any moment make up mobile ad-hoc networks. A significant number of messages are delivered during information exchange in populated regions because of the Internet of Things' (IoT) exponential increase in connected devices. Congestion can increase transmission latency and packet loss by causing congestion. More network size, increased network traffic, and high mobility that necessitate dynamic topology make this problem worse. An adaptive Multipath Multichannel Energy Efficient (AMMEE) routing strategy is proposed in this study, in which route selection strategies depend on forecasted energy consumption per packet, available bandwidth, queue length, and channel utilization. While multichannel uses a channel-ideal assignment process to lessen network collisions, multipath offers various paths and balances network strain. The link bandwidth is split up into a few sub-channels in the multichannel mechanism. To reduce network collisions, several source nodes simultaneously access the channel bandwidth. The cooperative multipath multichannel technique offers several paths from a single source or from several sources to the destination without colliding or becoming congested. The AMMEE routing approach is the basis for path selection. A load- and bandwidth-aware routing mechanism in the proposed AMMEE chooses the path based on node energy and forecasts their lifetime, which improves network dependability. The outcome demonstrates a comparative analysis of various multichannel medium access control (MMAC) techniques, including Parallel Rendezvous Multi Channel Medium Access Protocol (PRMMAC), Quality of Service Ad hoc On Demand Multipath Distance Vector (QoS-AOMDV), Q-learning-based Multipath Routing (QMR), and Topological Change Adaptive Ad hoc On-demand Multipath Distance Vector (TA-AOMDV) and the proposed AMMEE method. The results show that the AMMEE approach outperforms alternative systems. Doi: 10.28991/ESJ-2024-08-01-018 Full Text: PDF
Co-Authors Akbota Akzambekkyzy Balàzs Lukàcs Jeffrey Yi-Lin Forrest Joanna Rosak-Szyrocka Laszlo Vasa Shynara Sarkambayeva