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. 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.

[1]  Ramjee Prasad,et al.  Proposed embedded security framework for Internet of Things (IoT) , 2011, 2011 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE).

[2]  Carynthia Kharkongor,et al.  A SDN Controller with Energy Efficient Routing in the Internet of Things (IoT) , 2016 .

[3]  Simon Fong,et al.  An adaptive meta-heuristic search for the internet of things , 2017, Future Gener. Comput. Syst..

[4]  Rowayda A. Sadek,et al.  Hybrid energy aware clustered protocol for IoT heterogeneous network , 2018, Future Computing and Informatics Journal.

[5]  Marimuthu Palaniswami,et al.  Network architecture and QoS issues in the internet of things for a smart city , 2012, 2012 International Symposium on Communications and Information Technologies (ISCIT).

[6]  Joseph Walsh,et al.  Internet of Things: A review from ‘Farm to Fork’ , 2016, 2016 27th Irish Signals and Systems Conference (ISSC).

[7]  Reza Ebrahimi Atani,et al.  A Stable Clustering Scheme Based on Adaptive Multiple Metric in Vehicular Ad-hoc Networks , 2015, J. Inf. Sci. Eng..

[8]  Y. Ahmet Sekercioglu,et al.  A Low-Cost Flooding Algorithm for Wireless Sensor Networks , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[9]  Irfan-Ullah Awan,et al.  Modelling QoS in IoT Applications , 2014, 2014 17th International Conference on Network-Based Information Systems.

[10]  D. Sakai,et al.  Genes Required for Plasmid R64 Thin-Pilus Biogenesis: Identification and Localization of Products of the pilK, pilM, pilO, pilP, pilR, and pilT Genes , 2002, Journal of bacteriology.

[11]  Krishnapriya QoS Aware Resource Scheduling in Internet of Things-Cloud Environment , 2015 .

[12]  Ling Li,et al.  QoS-Aware Scheduling of Services-Oriented Internet of Things , 2014, IEEE Transactions on Industrial Informatics.

[13]  Nafaâ Jabeur,et al.  Towards a Three-Level Framework for IoT Redundancy Control through an Explicit Spatio-Temporal Data Model , 2017, ANT/SEIT.

[14]  Yong-Hwan Lee,et al.  Achievable sum-rate analysis of correlated two-antenna uplink MIMO channels , 2009 .

[15]  Theodore Tryfonas,et al.  The Internet of Things: a security point of view , 2016, Internet Res..

[16]  Paul Fergus,et al.  M2M Rendezvous Redundancy for the Internet of Things , 2013, 2013 Sixth International Conference on Developments in eSystems Engineering.

[17]  Rajkumar Buyya,et al.  iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments , 2016, Softw. Pract. Exp..

[18]  Oliver E. Theel,et al.  Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks , 2016, Int. J. Distributed Sens. Networks.

[19]  Ahmed Nait-Sidi-Moh,et al.  Using Internet of Things Technologies for a Collaborative Supply Chain: Application to Tracking of Pallets and Containers , 2015, FNC/MobiSPC.

[20]  Mazliza Othman,et al.  A novel countermeasure technique for reactive jamming attack in internet of things , 2018, Multimedia Tools and Applications.

[21]  Mazliza Othman,et al.  Internet of Things security: A survey , 2017, J. Netw. Comput. Appl..

[22]  Low Tang Jung,et al.  On fuzzy semantic similarity measure for DNA coding , 2016, Comput. Biol. Medicine.

[23]  Low Tang Jung,et al.  From DNA to protein: Why genetic code context of nucleotides for DNA signal processing? A review , 2017, Biomed. Signal Process. Control..

[24]  Anisha Gupta,et al.  Scalability in Internet of Things : Features , Techniques and Research Challenges , 2017 .

[25]  Ellis Solaiman,et al.  End-to-End QoS Specification and Monitoring in the Internet of Things , 2016 .

[26]  Amol V. Dhumane,et al.  Routing Issues in Internet of Things : A Survey , 2016 .

[27]  Duan Yan-e,et al.  Design of Intelligent Agriculture Management Information System Based on IoT , 2011, 2011 Fourth International Conference on Intelligent Computation Technology and Automation.

[28]  Panayotis Kikiras,et al.  Enabling QoS in the Internet of Things , 2012 .

[29]  Miss Laiha Mat Kiah,et al.  Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things , 2020, Sensors.

[30]  Dhananjay Singh,et al.  Quality of Service of Routing Protocols in Wireless Sensor Networks: A Review , 2017, IEEE Access.

[31]  Hiroshi Furukawa,et al.  Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey , 2016, Sensors.

[32]  Randi Rizal,et al.  Network Forensics for Detecting Flooding Attack on Internet of Things (IoT) Device , 2018 .

[33]  Zhong Zheng,et al.  Multicast Routing for Multimedia Communications in the Internet of Things , 2017, IEEE Internet of Things Journal.

[34]  M Vellanki,et al.  Node Level Energy Efficiency Protocol for Internet of Things , 2015 .

[35]  Wil M. P. van der Aalst,et al.  Process querying: Enabling business intelligence through query-based process analytics , 2017, Decis. Support Syst..

[36]  Josephat Kalezhi,et al.  The internet of things in agriculture for sustainable rural development , 2015, 2015 International Conference on Emerging Trends in Networks and Computer Communications (ETNCC).

[37]  Low Tang Jung,et al.  A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing , 2017, Comput. Methods Programs Biomed..

[38]  Pritee Parwekar,et al.  Detection of Sinkhole Attack in Wireless Sensor Network , 2016 .