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Ibrahim Al-Oqily
Researcher at Hashemite University
Publications - 33
Citations - 238
Ibrahim Al-Oqily is an academic researcher from Hashemite University. The author has contributed to research in topics: Overlay network & Network management. The author has an hindex of 9, co-authored 32 publications receiving 190 citations. Previous affiliations of Ibrahim Al-Oqily include Al-Yamamah Private University & Ottawa University.
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Development of Temperature-based Weather Forecasting Models Using Neural Networks and Fuzzy Logic
TL;DR: This study proposes computer-based models for weather forecasting based on temperature to predict the daily temperature using two techniques, artificial neural networks and fuzzy logic, and develops different weather forecasting models based on the two techniques over different regions.
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EdgeKV: Decentralized, scalable, and consistent storage for the edge
TL;DR: In this article, the authors proposed a decentralized storage system called EdgeKV, which offers fast and reliable storage, utilizing data replication with strong consistency guarantees, with a location-transparent and interface-based design.
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SORD: A Fault-Resilient Service Overlay for MediaPort Resource Discovery
Ibrahim Al-Oqily,Ahmed Karmouch +1 more
TL;DR: A new fault-resilient service overlay for MediaPort resource discovery that allows services to be efficiently and accurately located and based on a widely studied family of chordal rings, called the optimal chordal ring is proposed.
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A Decentralized Self-Organizing Service Composition for Autonomic Entities
Ibrahim Al-Oqily,Ahmed Karmouch +1 more
TL;DR: A new service composition algorithm is proposed to deal with the problem of composing multiple autonomic elements to achieve system-wide goals using a self-organizing approach that combines composition and service discovery into one step, thereby achieving more efficiency and less latency.
Posted Content
EdgeKV: Decentralized, scalable, and consistent storage for the edge
TL;DR: Evaluation results show that EdgeKV outperforms the cloud storage setting with both local and global data access with an average write response time and throughput improvements of 26% and 19% respectively under the same settings.