Wireless sensor networks (WSN) groups specialized transducers that provide sensing services to Internet of Things (IoT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important role in power conservation for the energy constrained network. Choosing a cluster head can appropriately balance the load in the network thereby reducing energy consumption and enhancing lifetime. The paper focuses on an efficient cluster head election scheme that rotates the cluster head position among the nodes with higher energy level as compared to other. The algorithm considers initial energy, residual energy and an optimum value of cluster heads to elect the next group of cluster heads for the network that suits for IoT applications such as environmental monitoring, smart cities, and systems. Simulation analysis shows the modified version performs better than the LEACH protocol by enhancing the throughput by 60%, lifetime by 66%, and residual energy by 64%.

Wireless Sensor Networks (WSN) is a virtual layer in the paradigm of the Internet of Things (IoT). It inter-relates information associated with the physical domain to the IoT drove computational systems. WSN provides ubiquitous access to location, the status of different entities of the environment, and data acquisition for long-term IoT monitoring. Since energy is a major constraint in the design process of a WSN, recent advances have led to project various energy-efficient protocols. Routing of data involves energy expenditure in considerable amount. In recent times, various heuristic clustering protocols have been discussed to solve the purpose. This article is an improvement of the existing Stable Election Protocol (SEP) that implements a threshold-based cluster head selection for a heterogeneous network. The threshold maintains uniform energy distribution between member and cluster head nodes. The sensor nodes are also categorized into three different types called normal, intermediate and advanced depending on the initial energy supply to distribute the network load evenly. The simulation result shows that the proposed scheme outperforms SEP and DEEC protocols with an improvement of 300% in network lifetime and 56% in throughput.

Wireless sensor networks (WSNs) have a wide range of applications in various fields. One of the most recent emerging applications are in the world of Internet of Things (IoT), which allows inter‐connection of different objects or devices through the Internet. However, limited battery power is the major concern of WSNs as compared to mobile ad‐hoc network, which affects the longevity of the network. Hence, a lot of research has been focused on to minimise the energy consumption of the WSNs. Designing of a hierarchical clustering algorithm is one of the numerous approaches to minimise the energy of the WSNs. In this study, the existing low‐energy adaptive clustering hierarchy (LEACH) clustering protocol is modified by introducing a threshold limit for cluster head selection with simultaneously switching the power level between the nodes. The proposed modified LEACH protocol outperforms as compared to the existing LEACH protocol with 67% rise in throughput and extending the number of alive nodes to 1750 rounds which can be used to enhance the WSN lifetime. When compared with other energy efficient protocols, it is found that the proposed algorithm performs better in terms of stability period and network lifetime in different scenarios of area, energy and node density.

Recent developments in low-power communication and signal processing technologies have led to the extensive implementation of wireless sensor networks (WSNs). In a WSN environment, cluster formation and cluster head (CH) selection consume significant energy. Typically, the CH is chosen probabilistically, without considering the real-time factors such as the remaining energy, number of clusters, distance, location, and number of functional nodes to boost network lifetime. Based on the real-time issues, different strategies must be incorporated to design a generic protocol suited for applications such as environment and health monitoring, animal tracking, and home automation. Elementary protocols such as LEACH and centralized-LEACH are well proven, but gradually limitations evolved due to increasing desire and need for proper modification over time. Since the selection of CHs has always been an important criterion for clustered networks, this paper overviews the modifications in the threshold value of CH selection in the network. With the evolution of bio-inspired algorithms, the CH selection has also been enhanced considering the behavior of the network. This paper includes a brief description of LEACH-based and bio-inspired protocols, their pros and cons, assumptions, and the criteria of CH selection. Finally, the performance factors such as longevity, scalability, and packet delivery ratio of various protocols are compared and discussed.

Nowadays FinFETs integrated into complex circuit applications can fulfill the demand of smartphones and tablets for better performance and make chips that can compute faster. This paper studies the impact of H_Fin and W_Fin variations on various performance matrices including static as well as dynamic figures of merit (FOMs). With the help of aspect ratio (W_Fin/H_Fin), the device is branched into three parts, i.e., FinFET, Trigate, and Planar MOSFET. This unique report is a presentation of a detailed analysis about the impact of fin height (H_Fin) and width (W_Fin) on various performances including the dc as well as ac FOMs. The static or low-frequency performances like threshold voltage (V_th), on current (I_on), off current (I_off ), power dissipation, transconductance (g_m), output conductance (g_d), transconductance generation factor (TGF = g_m /I_D), early voltage (V_EA), gain (A_V), and dynamic or high-frequency performances as gate capacitance (C_gg), cutoff frequency (f_T), output resistance (R₀), intrinsic delay are systematically presented with the variation of device geometry parameters. The results presented in this paper can be of great help to device engineers in designing 3-D devices as per their requirement.