Sankar Sennan¹, Somula Ramasubbareddy², Anand Nayyar^3,4, Yunyoung Nam^5,*, Mohamed Abouhawwash^6,7

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 351-371, 2021, DOI:10.32604/cmc.2021.017360

Abstract Energy conservation is a significant task in the Internet of Things (IoT) because IoT involves highly resource-constrained devices. Clustering is an effective technique for saving energy by reducing duplicate data. In a clustering protocol, the selection of a cluster head (CH) plays a key role in prolonging the lifetime of a network. However, most cluster-based protocols, including routing protocols for low-power and lossy networks (RPLs), have used fuzzy logic and probabilistic approaches to select the CH node. Consequently, early battery depletion is produced near the sink. To overcome this issue, a lion optimization algorithm (LOA) for selecting CH in RPL… More >

S. Nanthini^1,*, S. Nithya Kalyani², Sudhakar Sengan³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3595-3614, 2021, DOI:10.32604/cmc.2021.015038

Abstract In this paper, the energy conservation in the ununiform clustered network field is proposed. The fundamental reason behind the methodology is that in the process of CH election, nodes Competition Radius (CR) task is based on not just the space between nodes and their Residual Energy (RE), which is utilized in Energy-Aware Distributed Unequal Clustering (EADUC) protocol but also a third-degree factor, i.e., the nearby multi-hop node count. In contrast, a third-factor nearby nodes count is also used. This surrounding data is taken into account in the clustering feature to increase the network’s life span. The proposed method, known as… More >

V. Nivedhitha^1,*, A. Gopi Saminathan², P. Thirumurugan³

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 603-616, 2021, DOI:10.32604/iasc.2021.016780

Abstract Several protocols strive to improve network longevity but fail to ameliorate the uneven overhead imparted upon the sensor nodes that lead to temporal deaths. The proposed work uses a metaheuristic approach that promotes load balancing and energy-efficient data transmission using the fruit fly optimization algorithm (FFOA). The approach combines the LEACH protocol with differential evolution (DE) to select an optimum cluster head in every cluster. The algorithm is designed to provide energy-efficient data transmissions based on the smell and vision foraging behavior of fruit flies. The approach considers the compactness of nodes, energy capacity, and the distance of sensor nodes… More >

Anuj Kumar Singh¹, Mohammed Alshehri^2,*, Shashi Bhushan³, Manoj Kumar³, Osama Alfarraj⁴, Kamal Raj Pardarshani⁵

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 761-769, 2021, DOI:10.32604/iasc.2021.012806

Abstract Wireless sensor networks (WSNs) have been used in numerous delicate checking, observation, and surveillance systems that use sensitive data. When a WSN utilizes various data clustering techniques, data is moved to the cluster head (CH) of the corresponding cluster area. Cluster Head further communicates the information to the sink node. In a WSN, a network owner (NO) does not validate a sensor before connecting to the network, so faulty nodes may likely attach to the network to sense the data and attempt to release the information to unauthorized persons. Further, a malicious node may become a mobile node (MN) equipped… More >

Vijayalakshmi. K^1,*, Anandan. P²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 303-311, 2020, DOI:10.31209/2020.100000165

Abstract The advent of sensors that are light in weight, small-sized, low power and are enabled by wireless network has led to growth of Wireless Sensor Networks (WSNs) in multiple areas of applications. The key problems faced in WSNs are decreased network lifetime and time delay in transmission of data. Several key issues in the WSN design can be addressed using the Multi-Objective Optimization (MOO) Algorithms. The selection of the Cluster Head is a NP Hard optimization problem in nature. The CH selection is also challenging as the sensor nodes are organized in clusters. Through partitioning of network, the consumption of… More >

V. Manikandan^{1, *}, M. Sivaram¹, Amin Salih Mohammed², V. Porkodi³

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 753-776, 2020, DOI:10.32604/cmc.2020.010267

Abstract Wireless Sensor Networks (WSNs) comprises low power devices that are randomly distributed in a geographically isolated region. The energy consumption of nodes is an essential factor to be considered. Therefore, an improved energy management technique is designed in this investigation to reduce its consumption and to enhance the network’s lifetime. This can be attained by balancing energy clusters using a meta-heuristic Firefly algorithm model for network communication. This improved technique is based on the cluster head selection technique with measurement of the tour length of fireflies. Time Division Multiple Access (TDMA) scheduler is also improved with the characteristics/behavior of fireflies… More >

Nithya Rekha Sivakumar^{1, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 81-96, 2020, DOI:10.32604/cmc.2020.08851

Abstract In the past few decades, Energy Efficiency (EE) has been a significant challenge in Wireless Sensor Networks (WSNs). WSN requires reduced transmission delay and higher throughput with high quality services, it further pays much attention in increased energy consumption to improve the network lifetime. To collect and transmit data Clustering based routing algorithm is considered as an effective way. Cluster Head (CH) acts as an essential role in network connectivity and perform data transmission and data aggregation, where the energy consumption is superior to non-CH nodes. Conventional clustering approaches attempts to cluster nodes of same size. Moreover, owing to randomly… More >