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Wireless nanosensor networks (WNSNs) consist of nano-sized communication devices, which are equipped with nano-transceivers, nano-antennas, and other functional modules. A nanosensor is an integrated device that ranges from 10 to $100~\mu m^{2}$ in size. Due to the limited communication capabilities of WNSNs, existing localization algorithms and protocols for wireless sensor networks (WSNs) are...
In recent times the incorporation of Wireless Sensor Network (WSN) with Internet of Things (IoT) has become more conscientious for the researchers. The collection of enormous amount of homogenous sensor nodes forms the Wireless Sensor Network. These sensor nodes have restricted battery power and memory and so the limited amount of energy is considered as the major issue. To overcome this issue several...
The two-layer network structure has been widely adopted in wireless sensor networks (WSNs) for managing sensor nodes. In such a structure, the low layer nodes communicate with their cluster head, followed by the cluster-head nodes communicating with the base station operating in either a one-hop or a multi-hop manner. The main focus of node-clustering algorithms is minimizing energy consumption due...
Wireless sensing element Network may be a network distributed in universe. This one consists of big quantity of nodes that are helpful in assembly of information within the various setting. However the nodes operate on battery of adequate power. As the nodes died, the network time period is reduced. Thus raising the network time period is final issue of sensing element network. This paper proposes...
The k-means initialization technique for a wireless sensor network is a newly emerging area for researchers. There are many constraints in designing the wireless sensor network. The primary constraint is energy consumption. Clustering is used for improving the lifetime of the system by reducing the power consumption. The most popular clustering technique is k-means algorithm but it exhibits local...
Wireless sensor networks are principally categorized by insufficient energy resource. Naturally, communication between the nodes is the utmost energy consuming act that they perform. Hence, development of a well-organized clustering algorithm can play a vital part in enhancing the lifetime of network. Currently, nature inspired methodologies are very common in dealing with it. This work presents a...
Appropriate cluster head selection process in hierarchical cluster based routing algorithms is vital to make the wireless sensor networks energy efficient. This paper suggests a hybrid cluster head selection method with the parameters Location centrality and Nodes' lingering energy on the fixed clusters. The simulation outcome illustrates that the proposed algorithm is good at load balancing with...
In recent years, nonnegative matrix factorization (NMF) attracts much attention in machine learning and signal processing fields due to its interpretability of data in a low dimensional subspace. For clustering problems, symmetric nonnegative matrix factorization (SNMF) as an extension of NMF factorizes the similarity matrix of data points directly and outperforms NMF when dealing with nonlinear data...
In recent days, wireless sensor networks (WSN) are catching the spotlights in networking and other emerging fields like large data communication, artificial intelligence, automation systems etc. The major constraint wireless sensor networks are struggling with limited energy supply issues for their sensor nodes. This paper is focused to put emphasis on implementing a clustering protocol inspired from...
Energy efficiency has become a main challenge in Wireless Sensor Networks (WSNs) and their applications. Localization is one of the indispensable stages in WSN. Localization generally refers to the process of locating the position of one or more node(s) in a network. This paper develops and evaluates an improved energy aware localization algorithm in WSNs. Clustering techniques have been intensively...
Recent advances in the routing protocols of Wireless Sensor Networks (WSNs) using Machine Learning (ML) techniques immensely aid in addressing their energy depletion issue. Numerous ML solutions have been proposed to minimize the resource utilization in WSNs for prolonging the networks lifetime. In this paper, we present an efficient support vector based clustering protocol which efficiently assign...
Wireless sensor network (WSN) is a network which includes spatially distributed autonomous devices using sensors to monitor environmental or physical conditions. WSN is emerging as popular and essential ways of providing pervasive computing environments for numerous applications. The sensor nodes are constrained in terms of energy and therefore energy consumption and extending network lifetime is...
In wireless sensor networks, the limitation of energy and cache space of nodes around the base station, as well as the multi-hop transmission instability will seriously interfere the performance of traditional data collection protocols. To address this problem, a data collection mechanism by using mobile base station is proposed. Firstly, a new clustering algorithm-Time High-Overflow-Based Dominating...
Underwater Acoustic Networks and related energy based lifetime enhancement is one of the key domain of research in marine based engineering. A number of algorithms, protocols and approaches are developed so far for effective optimization of acoustic resources still a huge scope of research is there. In this research work, an effective and novel algorithm for energy harvesting is proposed using which...
In wireless sensor networks (WSNs) there is an important task of self-organizing networks. There are many different algorithms for self-organization of such networks. This choice determines the relevance of pre-emptive self-algorithm network with the additional information obtained from experts. In the article features of practical application of the analytic hierarchy process are considered to select...
Clustering is a hierarchical method to data transmission in wireless sensor networks, which has a considerable effect on energy conservation. A balanced and efficient clustering has an important role in these networks. This paper discusses an optimal clustering method in wireless sensor network. Firstly, by considering energy and distance parameters, we model the clustering problem using two techniques,...
The node localization technique as a crucial technique that affects practicality, accuracy and effectiveness of the wireless sensor networks (WSNs). Sensor nodes are often deployed nonuniformly in anisotropic WSNs with holes in many applications. The existence of holes will affect the shortest distance between nodes and result in low accuracy of node localization. In this paper, an Extended Kalman...
Target tracking with the wireless sensors networks is to detect and locate a target on its entire path through a region of interest. This application arouses interest in the world of research for its many fields of use. Wireless sensor networks, thanks to their versatility, can be used in many hostile environments and inaccessible to humans. However, with a limited energy, they cannot remain permanently...
Ensuring connectivity among mobile nodes is significantly important to the success of many critical applications, like military, where the loss of connectivity can lead to the failure of the mission and also proved to be challenging in particular when mobiles nodes have heterogeneous mobility pattern i.e., they are moving in several directions at different speeds. In this paper, we propose a new Heterogonous...
A three-level hybrid clustering routing protocol algorithm (MLHP) based on the Grey Wolf Optimizer (GWO) for wireless sensor networks is proposed in this paper. A centralized selection is proposed for Level One, in which the base station (BS) plays a great role in selecting cluster heads. In Level Two, a GWO routing for data transfer is proposed, were nodes select the best route to the BS to save...
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