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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Charles Ndujiuba
Covenant University
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Performance Benchmarking of Key-Value Store NoSQL Databases Omoruyi Osemwegie; Kennedy Okokpujie; Nsikan Nkordeh; Charles Ndujiuba; Samuel John; Uzairue Stanley
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (941.893 KB) | DOI: 10.11591/ijece.v8i6.pp5333-5341

Abstract

Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.
Epidemic Alert System: A Web-based Grassroots Model Etinosa Noma Osaghae; Kennedy Okokpujie; Charles Ndujiuba; Olatunji Okesola; Imhade P. Okokpujie
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (816.656 KB) | DOI: 10.11591/ijece.v8i5.pp3809-3828

Abstract

Most web-based disease surveillance systems that give epidemic alerts are based on very large and unstructured data from various news sources, social media and online queries that are parsed by complex algorithms. This has the tendency to generate results that are so diverse and non-specific. When considered along with the fact that there are no existing standards for mining and analyzing data from the internet, the results or decisions reached based on internet sources have been classified as low-quality. This paper proposes a web-based grassroots epidemic alert system that is based on data collected specifically from primary health centers, hospitals and registered laboratories. It takes a more traditional approach to indicator-based disease surveillance as a step towards standardizing web-based disease surveillance. It makes use of a threshold value that is based on the third quartile (75th percentile) to determine the need to trigger the alarm for the onset of an epidemic. It also includes, for deeper analysis, demographic information.
Co-Authors Adebiyi A. Adelakun Aderemi A. Atayero Etinosa Noma Osaghae Imhade P. Okokpujie Kennedy Okokpujie Nsikan Nkordeh Olasunkanmi Ojewande Olatunji Okesola Omoruyi Osemwegie Samuel John Segun I. Popoola Uzairue Stanley