Search: WFRF:(Hassan Sodhro Ali) >
A Novel Energy Opti...
A Novel Energy Optimization Approach for Artificial Intelligence-enabled Massive Internet of Things
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- Sodhro, Ali Hassan (author)
- Sukkur IBA Univ, Pakistan
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- Obaidat, Mohammad S. (author)
- Nazarbayev Univ, Kazakhstan; Univ Jordan, Jordan; Univ Sci & Technol Beijing, Peoples R China
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- Pirbhulal, Sandeep (author)
- Chinese Acad Sci, Peoples R China
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- Sodhro, Gul Hassan (author)
- Shah Abdul Latif Univ, Pakistan
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- Zahid, Noman (author)
- Sukkur IBA Univ, Pakistan
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- Rawat, Abhimanyu (author)
- Linköpings universitet,Databas och informationsteknik,Tekniska fakulteten
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(creator_code:org_t)
- ACM Digital Library, 2019
- 2019
- English.
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In: PROCEEDINGS OF THE 2019 SUMMER SIMULATION CONFERENCE (SUMMERSIM 19). - : ACM Digital Library.
- Related links:
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https://urn.kb.se/re...
Abstract
Subject headings
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- Emerging trends in Internet of things (IoT) has caught the attention of every domain e.g., industrial, business, and healthcare etc. Sensor-embedded IoT devices are the key drivers for collecting large amount of data. Managing these large datasets is one of the critical challenges to be tackled. Continuous huge information collection through sensor-enabled devices is known as the massive IoT (mIoT). Thus, there is a need of self-adaptive artificial intelligence (AI)based strategies to effectively cluster, examine and interpret the entire entities in the system. With increased data volumes and power hungry natured IoT devices it is a dire need to manage their power wisely. To fairly allot the power levels to the tiny portable devices it is important to integrate mIoT with AI-based techniques. To remedy these issues this paper proposes a novel cross-layer based energy optimization algorithm (CEOA) in mIoT system by examining the detailed features and data patterns. Experimental analysis reveals that proposed CEOA outperforms its competing counterpart i.e., Baseline in terms of efficient power management and monitoring.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
Keyword
- Energy optimization; Massive IoT; AI; CEOA; Performance Evaluation
Publication and Content Type
- ref (subject category)
- kon (subject category)
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