This paper presents a report of a study carried out to develop a job coordination model for the active resources on a mobile wireless computational grid. This was with a view to addressing the problem of frequent disruptions in connections and high computation time for a job resulting from the mobility of the mobile resources actively processing tasks. The proposed framework is a load-balancing three tier hierarchical system configuration and scheduling policies employing mobile Agents coordinating messengers carrying data and instructions among the hierarchical structured nodes. The model achieves a remarkable performance as compared with theoretical values in that there were reduction in response times and latencies when simulated with various workloads. The proposed migration and checkpointing approach ensures that currently executing processes are not always migrated because of loss of signal only, but only with reduction in battery power of the mobile hosts within the allocated time for processing a task.
Severe outbreaks of infectious disease occur throughout the world with some reaching the level of international pandemic: Coronavirus (COVID-19) is the most recent to do so. In this paper, a mechanism is set out using Zipf's law to establish the accuracy of international reporting of COVID-19 cases via a determination of whether an individual country's COVID-19 reporting follows a power-law for confirmed, recovered, and death cases of COVID-19. The probability of Zipf's law (P-values) for COVID-19 confirmed cases show that Uzbekistan has the highest P-value of 0.940, followed by Belize (0.929), and Qatar (0.897). For COVID-19 recovered cases, Iraq had the highest P-value of 0.901, followed by New Zealand (0.888), and Austria (0.884). Furthermore, for COVID-19 death cases, Bosnia and Herzegovina had the highest P-value of 0.874, followed by Lithuania (0.843), and Morocco (0.825). China, where the COVID-19 pandemic began, is a significant outlier in recording P-values lower than 0.1 for the confirmed, recovered, and death cases. This raises important questions, not only for China, but also any country whose data exhibits P-values below this threshold. The main application of this work is to serve as an early warning for World Health Organization (WHO) and other health regulatory bodies to perform more investigations in countries where COVID-19 datasets deviate significantly from Zipf's law. To this end, this paper provide a tool for illustrating Zipf's law P-values on a global map in order to convey the geographic distribution of reporting anomalies.
In this work a model that integrates all the accounts statements and transactions of a client into a single Automated Teller Machine (ATM) access card was developed. This was with a view to address the challenges of the multiple cards carried by ATM card users operating accounts with different banks. The model harnessed the accounts of the customers using the Bank Verification Number (BVN), a unique identification code given to a customer holding at least one account with a bank. The algorithm for the model was developed and simulated using MATLAB 7.10. The results showed that the processing time and cost of maintenance for integrated card is less than that for multiple cards. The study concludes that the model will facilitate card safety, reduce the cost of issuing multiple cards by the banks and cost of maintenance of the card by the customers. Additional layer of security is also an advantage.
General TermsModel, Algorithm, Security
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