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Author

K. Selvakumar

Other affiliations: VIT University, Sathyabama University, Anna University  ...read more
Bio: K. Selvakumar is an academic researcher from National Institute of Technology, Tiruchirappalli. The author has contributed to research in topics: Wireless sensor network & Routing protocol. The author has an hindex of 6, co-authored 21 publications receiving 186 citations. Previous affiliations of K. Selvakumar include VIT University & Sathyabama University.

Papers
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Journal ArticleDOI
TL;DR: A cognitive or intelligent model of bio-inspired approach is used to find the optimal solution of task scheduling for IoT applications in a heterogeneous multiprocessor cloud environment.

92 citations

Journal ArticleDOI
TL;DR: An adaptive IDS based on Fuzzy Rough sets for attribute selection and Allen's interval algebra is applied on network trace datasets in order to select a huge number of attack data for effective prediction of attacks in WSNs and a fuzzy and rough set based nearest neighborhood algorithm (FRNN) is proposed in this article for effective classification of network trace dataset.

67 citations

Journal ArticleDOI
TL;DR: A new and effective routing protocol named, “Intelligent Energy Aware Secured Algorithm for Routing (IEASAR)” is proposed which is secure by using a Trust based approach and is Energy efficient at the same time.
Abstract: Modern Wireless Sensor Networks (WSNs) requires special requirements in routing protocols because of nature of distribution and dynamic topology. The most important need for WSNs is energy efficient routing protocol that consumes optimal energy. It provides extension to the network’s life period. Nowadays a number of energy efficient routing protocols are proposed by various researchers in WSNs. However, security and energy efficiency in data collection and transmission in WSNs should be simultaneously considered for security challenges and to overcome limitation of WSNs. In this paper, we propose a new and effective routing protocol named, “Intelligent Energy Aware Secured Algorithm for Routing (IEASAR)” which is secure by using a Trust based approach and is Energy efficient at the same time. For this purpose, a new energy efficient protocol using Fuzzy C-means has been proposed in this paper. Moreover, a modified minimum spanning tree approach is applied here to identify the minimum distance path between the sender node and the destination node and hence an optimal and secured routing path is selected. Extensive simulations have been conducted in this work to verify the validity of our claims.

22 citations

Proceedings ArticleDOI
R. Reshma, V. Sathiyavathi, T. Sindhu1, K. Selvakumar, L. SaiRamesh1 
07 Oct 2020
TL;DR: The proposed IoT system is composed of pH sensors, Humidity and temperature sensors, Soil moisture sensors, soil nutrient sensors (NPK) probes, microcontroller/microprocessor equipped with WiFi and Cloud storage, which helps to enhance the growth using an optimized farming process.
Abstract: Agriculture aided by IoT is called Smart Agriculture and it gives rise to precision farming. Soil Monitoring combined with Internet of Things (IoT) technology aids in the enhancement of agriculture by increasing yield through gauging the exact soil characteristics such as Moisture, Temperature, Humidity, PH, and Nutrition content/Fertility. This data is then gathered in cloud storage and with the appropriate data operations; it enabled us to optimize farming strategies and helped create a trend analysis. This, then, allows us to precisely utilize resources and steer the farming methods in prudent ways to optimize yield. The proposed IoT system is composed of pH sensors, Humidity and temperature sensors, Soil moisture sensors, soil nutrient sensors (NPK) probes, microcontroller/microprocessor equipped with WiFi and Cloud storage. When the sensors are implemented, they measure the corresponding characteristics and transmit time-stamped live data to the cloud server. These sensors work together and provide wholesome data to the analyst. For the recommending system, the SVM and Decision Tree algorithm is proposed to get the crop suitable for the given soil data and helps to enhance the growth using an optimized farming process.

16 citations

Journal ArticleDOI
TL;DR: A new enhanced K-means clustering algorithm is proposed in this paper for grouping user based on their preferred Web content and their temporal constraints and uses time intervals to heighten the security and performance.
Abstract: To gain information about user interests in Web pages is needed to advance in Web security. An approach to pick up that information includes understanding the client's perusing conduct, examining the Web log records with the procedures of preprocessing and client clustering. Time spent on Web pages and the types of operations show the degree of a Web user's intention. The data set comprises of Web log files obtained by collecting the user logs during a six month period. A new enhanced K-means clustering algorithm proposed in this paper for grouping user based on their preferred Web content and their temporal constraints. The enhanced K-mean clustering calculates initial centroids instead of random choice and uses time intervals to heighten the security and performance. Utilizing this methodology, client access designs with comparable looking practices are assembled into a particular class amid a particular time interval. Also secured communication among the various users groups will be achieved through hill cipher technique.

15 citations


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Journal ArticleDOI
TL;DR: An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode and demonstrates that ISSA outperforms all baseline algorithms in terms of fitness values, accuracy, convergence curves, and feature reduction in most of the used datasets.
Abstract: Many fields such as data science, data mining suffered from the rapid growth of data volume and high data dimensionality. The main problems which are faced by these fields include the high computational cost, memory cost, and low accuracy performance. These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. In addition, the computational and memory cost of the machine learning is mainly affected by the size of the used datasets. Thus, to solve these problems, feature selection can be used to select optimal subset of features and reduce the data dimensionality. Feature selection represents an important preprocessing step in many intelligent and expert systems such as intrusion detection, disease prediction, and sentiment analysis. An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. The first improvement includes the use of Opposition Based Learning (OBL) at initialization phase of SSA to improve its population diversity in the search space. The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. To confirm and validate the performance of the proposed improved SSA (ISSA), ISSA was applied on 18 datasets from UCI repository. In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. In these experiments four different assessment criteria were used. The rdemonstrate that ISSA outperforms all baseline algorithms in terms of fitness values, accuracy, convergence curves, and feature reduction in most of the used datasets. The wrapper feature selection mode can be used in different application areas of expert and intelligent systems and this is confirmed from the obtained results over different types of datasets.

224 citations

Journal ArticleDOI
01 Mar 2021
TL;DR: This paper provides a holistic coverage of the Internet of Things in Smart Cities by discussing the fundamental components that make up the IoT based Smart City landscape followed by the technologies that enable these domains to exist in terms of architectures utilized, networking technologies used as well as the Artificial Algorithms deployed in IoTbased Smart City systems.
Abstract: Internet of Things (IoT) is a system that integrates different devices and technologies, removing the necessity of human intervention. This enables the capacity of having smart (or smarter) cities around the world. By hosting different technologies and allowing interactions between them, the internet of things has spearheaded the development of smart city systems for sustainable living, increased comfort and productivity for citizens. The IoT for Smart Cities has many different domains and draws upon various underlying systems for its operation. In this paper, we provide a holistic coverage of the Internet of Things in Smart Cities. We start by discussing the fundamental components that make up the IoT based Smart City landscape followed by the technologies that enable these domains to exist in terms of architectures utilized, networking technologies used as well as the Artificial Algorithms deployed in IoT based Smart City systems. This is then followed up by a review of the most prevalent practices and applications in various Smart City domains. Lastly, the challenges that deployment of IoT systems for smart cities encounter along with mitigation measures.

153 citations

Journal ArticleDOI
TL;DR: The proposed model sufficiently exploits advantages of edge computing and blockchain to establish a privacy-preserving mechanism while considering other constraints, such as energy cost, and improves privacy protections without lowering down the performance in an energy-efficient manner.
Abstract: Contemporarily, two emerging techniques, blockchain and edge computing, are driving a dramatical rapid growth in the field of Internet-of-Things (IoT). Benefits of applying edge computing is an adoptable complementarity for cloud computing; blockchain is an alternative for constructing transparent secure environment for data storage/governance. Instead of using these two techniques independently, in this article, we propose a novel approach that integrates IoT with edge computing and blockchain, which is called blockchain-based Internet of Edge model. The proposed model, designed for a scalable and controllable IoT system, sufficiently exploits advantages of edge computing and blockchain to establish a privacy-preserving mechanism while considering other constraints, such as energy cost. We implement experiment evaluations running on Ethereum. According to our data collections, the proposed model improves privacy protections without lowering down the performance in an energy-efficient manner.

151 citations

Journal ArticleDOI
TL;DR: A critical literature survey of recent intrusion detection protocols for IoT and WSN environments along with their comparative analysis is provided and a taxonomy of security and privacy-preservation protocols in WSN and IoT is highlighted.
Abstract: As we all know that the technology is projected to be next to humans very soon because of its holistic growth. Now-a-days, we see a lot of applications that are making our lives comfortable such as smart cars, smart homes, smart traffic management, smart offices, smart medical consultation, smart cities, etc. All such facilities are in the reach of a common man because of the advancement in Information and Communications Technology (ICT). Because of this advancement, new computing and communication environment such as Internet of Things (IoT) came into picture. Lot of research work is in progress in IoT domain which helps for the overall development of the society and makes the lives easy and comfortable. But in the resource constrained environment of Wireless Sensor Network (WSN) and IoT, it is almost inconceivable to establish a fully secure system. As we are moving forward very fast, technology is becoming more and more vulnerable to the security threats. In future, the number of Internet connected people will be less than the smart objects so we need to prepare a robust system for keeping the above mentioned environments safe and standardized it for the smooth conduction of communication among IoT objects. In this survey paper, we provide the details of threat model applicable for the security of WSN and IoT based communications. We also discuss the security requirements and various attacks possible in WSN and IoT based communication environments. The emerging projects of WSNs integrated to IoT are also briefed. We then provide the details of different architectures of WSN and IoT based communication environments. Next, we discuss the current issues and challenges related to WSN and IoT. We also provide a critical literature survey of recent intrusion detection protocols for IoT and WSN environments along with their comparative analysis. A taxonomy of security and privacy-preservation protocols in WSN and IoT is also highlighted. Finally, we discuss some research challenges which need to be addressed in the coming future.

90 citations

Journal ArticleDOI
TL;DR: A novel service orchestration and data aggregation framework (SODA) is proposed, which can orchestrate data as services and aggregate data packets to reduce data redundancy and service response delay.
Abstract: For the cloud computing based on software-defined networks (SDNs), a larger amount of data is collected to cloud for analysis, which will cause the larger amount of redundancy data and longer service response time due to the capacity-limited Internet. To solve this problem, a novel service orchestration and data aggregation framework (SODA) is proposed, which can orchestrate data as services and aggregate data packets to reduce data redundancy and service response delay. In SODA, the network is divided into three layers. 1) Data centers layer (DCL). Data centers (DCs) release software with a specific function to all devices in the network, devices orchestrate data as services and aggregate data packets using software to reduce service response delay. 2) Middle routing layer (MRL). The routing path of data packets in this layer is adjusted according to the correlation of data packets and routing distance. The correlation of data packets is higher and routing distance is short, the probability that data packets are transmitted along the same routing path is higher to reduce redundancy data. 3) Vehicle network layer (VNL). Mobile vehicles are used to transmit data packets and services among devices. A series of experiments and simulation is conducted. The results illustrate that the proposed scheme has better performance compared with the traditional scheme.

84 citations