Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things
Internet of Things (IoT) facilitates a wide range of applications through sensor-based connected devices that require bandwidth and other network resources. Enhancement of efficient utilization of a heterogeneous IoT network is an open optimization problem that is mostly suffered by network flooding...
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MDPI AG
2020-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/1/283 |
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| author | Fawad Ali Khan Rafidah Md Noor Miss Laiha Mat Kiah Ismail Ahmedy Mohd Yamani Tey Kok Soon Muneer Ahmad |
| author_facet | Fawad Ali Khan Rafidah Md Noor Miss Laiha Mat Kiah Ismail Ahmedy Mohd Yamani Tey Kok Soon Muneer Ahmad |
| author_sort | Fawad Ali Khan |
| collection | DOAJ |
| description | Internet of Things (IoT) facilitates a wide range of applications through sensor-based connected devices that require bandwidth and other network resources. Enhancement of efficient utilization of a heterogeneous IoT network is an open optimization problem that is mostly suffered by network flooding. Redundant, unwanted, and flooded queries are major causes of inefficient utilization of resources. Several query control mechanisms in the literature claimed to cater to the issues related to bandwidth, cost, and Quality of Service (QoS). This research article presented a statistical performance evaluation of different query control mechanisms that addressed minimization of energy consumption, energy cost and network flooding. Specifically, it evaluated the performance measure of Query Control Mechanism (QCM) for QoS-enabled layered-based clustering for reactive flooding in the Internet of Things. By statistical means, this study inferred the significant achievement of the QCM algorithm that outperformed the prevailing algorithms, i.e., Divide-and-Conquer (DnC), Service Level Agreements (SLA), and Hybrid Energy-aware Clustering Protocol for IoT (Hy-IoT) for identification and elimination of redundant flooding queries. The inferential analysis for performance evaluation of algorithms was measured in terms of three scenarios, i.e., energy consumption, delays and throughput with different intervals of traffic, malicious mote and malicious mote with realistic condition. It is evident from the results that the QCM algorithm outperforms the existing algorithms and the statistical probability value “P” < 0.05 indicates the performance of QCM is significant at the 95% confidence interval. Hence, it could be inferred from findings that the performance of the QCM algorithm was substantial as compared to that of other algorithms. |
| first_indexed | 2024-04-11T11:13:05Z |
| format | Article |
| id | doaj.art-a8057b2558b545d0957026a01d51ee22 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:13:05Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-a8057b2558b545d0957026a01d51ee222022-12-22T04:27:20ZengMDPI AGSensors1424-82202020-01-0120128310.3390/s20010283s20010283Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of ThingsFawad Ali Khan0Rafidah Md Noor1Miss Laiha Mat Kiah2Ismail Ahmedy3Mohd Yamani4Tey Kok Soon5Muneer Ahmad6Department of Computer System & Technology, Faculty of Computer Science & Information Technology, University Malaya, Kuala Lumpur 50603, MalaysiaDepartment of Computer System & Technology, Faculty of Computer Science & Information Technology, University Malaya, Kuala Lumpur 50603, MalaysiaDepartment of Computer System & Technology, Faculty of Computer Science & Information Technology, University Malaya, Kuala Lumpur 50603, MalaysiaDepartment of Computer System & Technology, Faculty of Computer Science & Information Technology, University Malaya, Kuala Lumpur 50603, MalaysiaDepartment of Computer System & Technology, Faculty of Computer Science & Information Technology, University Malaya, Kuala Lumpur 50603, MalaysiaDepartment of Computer System & Technology, Faculty of Computer Science & Information Technology, University Malaya, Kuala Lumpur 50603, MalaysiaDepartment of Information System, Faculty of Computer Science & Information Technology, University Malaya, Kuala Lumpur 50603, MalaysiaInternet of Things (IoT) facilitates a wide range of applications through sensor-based connected devices that require bandwidth and other network resources. Enhancement of efficient utilization of a heterogeneous IoT network is an open optimization problem that is mostly suffered by network flooding. Redundant, unwanted, and flooded queries are major causes of inefficient utilization of resources. Several query control mechanisms in the literature claimed to cater to the issues related to bandwidth, cost, and Quality of Service (QoS). This research article presented a statistical performance evaluation of different query control mechanisms that addressed minimization of energy consumption, energy cost and network flooding. Specifically, it evaluated the performance measure of Query Control Mechanism (QCM) for QoS-enabled layered-based clustering for reactive flooding in the Internet of Things. By statistical means, this study inferred the significant achievement of the QCM algorithm that outperformed the prevailing algorithms, i.e., Divide-and-Conquer (DnC), Service Level Agreements (SLA), and Hybrid Energy-aware Clustering Protocol for IoT (Hy-IoT) for identification and elimination of redundant flooding queries. The inferential analysis for performance evaluation of algorithms was measured in terms of three scenarios, i.e., energy consumption, delays and throughput with different intervals of traffic, malicious mote and malicious mote with realistic condition. It is evident from the results that the QCM algorithm outperforms the existing algorithms and the statistical probability value “P” < 0.05 indicates the performance of QCM is significant at the 95% confidence interval. Hence, it could be inferred from findings that the performance of the QCM algorithm was substantial as compared to that of other algorithms.https://www.mdpi.com/1424-8220/20/1/283qosredundant queryinternet of thingsnetwork floodingenergy efficiency |
| spellingShingle | Fawad Ali Khan Rafidah Md Noor Miss Laiha Mat Kiah Ismail Ahmedy Mohd Yamani Tey Kok Soon Muneer Ahmad Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things Sensors qos redundant query internet of things network flooding energy efficiency |
| title | Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things |
| title_full | Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things |
| title_fullStr | Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things |
| title_full_unstemmed | Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things |
| title_short | Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things |
| title_sort | performance evaluation and validation of qcm query control mechanism for qos enabled layered based clustering for reactive flooding in the internet of things |
| topic | qos redundant query internet of things network flooding energy efficiency |
| url | https://www.mdpi.com/1424-8220/20/1/283 |
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