paper1

Shamsuddeen Abdullahi Mikail, Aliyu Danjuma Usman, Abdoulie Momodou Sunkary Tekanyi, Kabir AhmadAbu-bilal, Aminu Abba Muhammad, Isyaku Yau, Muazu Jibrin Musa

Keywords: Wireless charger, mobile charging, rechargeable sensor nodes, distributed algorithms, clustering, wireless energy transfer, data gathering

Abstract

Most Wireless Rechargeable Sensor Networks (WRSN) allow simultaneous energy replenishment with data gathering.These schemes suffer from high energy consumption of mobile chargers and could require new sensor design for their integration. Thus, we propose Distributed Energy Replenishment and Data Gathering (DERDG) to reduce the energy consumption of the chargers and Spatio-Temporal Non-Concurrent Data gathering and Energy replenishment (STNCDR) that are easily be integratable on the sensor nodes. In these schemes, sensor nodes are divided into clusters and requests from energy-hungry nodes are arranged based on their temporal properties in DERDG, but using their spatial and temporal properties in ST-NCDR. In ST-NCDR scheme, two mobile chargers replenish the energy of energy hungry nodes when they are not performing sensing and transmission of data, but irrespective of their operational states in DERDG scheme. Simulation results indicate the superiority of the schemes over state-of-the-art schemes in terms of energy consumption of mobile chargers and average residual energy of the nodes. Both DERDG and ST-NCDR reduced the energy consumption of the chargers, without reduction in the network lifetime, by an average of 29.45% and 73.70%, respectively, when compared to the work of Han et al. (2018), and by 71.40% and 93.80% in comparison to the work of Mikail et al. (2020). DERDG reduces data delivery delay by 95.50% in comparison to the work of Han et. al, (2018). The findings imply that ST-NCDR can be easily integrated into sensor nodes and yields a reduction in the energy of mobiles chargers use in charging the sensor nodes that translate to lower cost of network operation, in addition to improving the residual energy of nodes in WRSN. This part should state the context of the research being reported.
Rising from the outbreak of COVID-19 pandemic, all schools in Nigeria were put under lock and key, like other countries.
This was to curtail the rapid spread of the virus, while the medical practitioners were in the laboratories. But due to
longer period of shutdown to formal education, most higher institutions instantaneously keyed-in to any available social
media platform (SMP) without understudying its efficiency and effectiveness for knowledge transfer. The consequences
of this include non-satisfactory knowledge transfer, most especially, by the learners; hence, aim of knowledge impact is
jeopardized. This study therefore is aimed to fill the gap to correct the existing damage, and prevent the likelihood of notafore-put-to-test syndrome in the subsequent choice of SMP. To achieve this, University of Ilorin is chosen as the territory
survey for being the most sought-after University for admission in Nigeria. Quantitative research methods were adopted,
being the most appropriate for this study in the literature. A total of 200 respondents participated voluntarily with the
adoption of Slovin’s formula for the sampling techniques; 156 students and 44 lecturers. The data collection process was
performed through a survey comprising demographic, dichotomous, multiple choice, and open-ended questionnaire to
capture detail information for the research work. Simple descriptive statistics was employed for the analysis. Our findings
reveal that out of the seventeen SMPs put to test, zoom platform ranks the most effective and efficient for the knowledge
delivery and acquisition by the lecturers and students of the University respectively, based on the designed principles.
Therefore, making Zoom platform the most preferred for e-learning. This study recommends that choice of satisfactory
SMP for knowledge delivery should be utmost concern of all institutions before embarking on virtual learning system. reported.