An adaboost-modified classifier using particle swarm optimization and stochastic diffusion search in wireless IoT networ
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An adaboost-modified classifier using particle swarm optimization and stochastic diffusion search in wireless IoT networks E. Suganya1 • C. Rajan2 Accepted: 11 November 2020 Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The main objective of Internet of Things (IoT) is connecting with different objects via Internet without human intervention. Wireless Sensor Networks (WSNs) which involves ubiquitous computing through which small sensors are connected to the Internet and are used for collecting data. Significant amount of information flowing in the internet is made up of sensory data. To resolve the storage issues of the huge data generated by IoT, the Hadoop Distributed File System are used that streams data to user applications as required. It is difficult to accomplish analysis of vast amount of data (big data) with existing data processing methods. To avoid redundant and irrelevant data, the data needs to be classified. This work presents the use of Support Vector Machine, and Adaboost classifiers, and modifying Adaboost classifier with Genetic Algorithm (GA), Stochastic Diffusion Search (SDS), and Particle Swarm Optimization (PSO). To avoid redundant classifiers, an ensemble algorithm is proposed in this work, PSO with Adaboost classifier and SDS-GA with Adaboost classifier, that can reinitialize attributes, thus avoiding reaching local optimum, and optimizing the coefficients of Adaboost weak classifiers. The proposed algorithms effectively classify the data gathered from WSN and IoT applications. The outcomes of the experiment showed that the proposed SDS-GA algorithm is efficient over other algorithms with respect to accuracy, precision, recall, f measure and false discovery rate. Keywords Wireless sensor network (WSN) Internet of things (IoT) Particle swarm optimization (PSO) Genetic algorithm (GA) Stochastic diffusion search (SDS) Support vector machine (SVM) and adaboost classifier
1 Introduction The IoT is an upcoming prototype which helps in collecting, communicating, processing and applying technology in various fields including manufacture, transport, surveillance of the environment, healthcare, and so on. This new networking paradigm uses RFID tags, actuators, sensors and mobile devices which can coordinate with one another and communicate using the infrastructure of Internet [1]. The IoT prototype can be considered as a system that has
& E. Suganya [email protected] C. Rajan [email protected] 1
Anna University, Chennai, Tamil Nadu, India
2
K.S.Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India
virtual, physical, or a hybrid of both and are made up of a group of a number of active sensors, cloud services, actuators, particular IoT protocols, communication layers, developers, users as well as layers of enterprise. Specific architectures play a pivotal role in the IoT infrastructure, at the same time bringing about a systematic approach even towards dissimilar components which result in soluti
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