Clustering Objectives in Wireless Sensor Networks: A Survey and Research Direction Analysis

Machine learning-based coronary artery disease diagnosis: A comprehensive review.

In recent years, wireless sensor networks (WSNs) have played a major role in applications such as tracking and monitoring in remote environments. Designing energy efficient protocols for routing of data events is a major challenge due to the dynamic topology and distributed nature of WSNs. Main aim of the paper is to discuss hierarchical routing protocols in order to improve the energy efficiency and network lifetime. This paper provides a discussion about hierarchical energy efficient routing protocols based on classical and swarm intelligence approach. The routing protocols belonging to both categories can be summarized according to energy efficiency, data aggregation, location awareness, QoS, scalability, load balancing, fault tolerance, query based and multipath. A systematic literature review has been conducted for hierarchical energy efficient routing protocols reported from 2012 to 2017. This survey provides a technical direction for researchers on how to develop routing protocols. Finally, research gaps in the reviewed protocols and the potential future aspects have been discussed.

Comprehensive review for energy efficient hierarchical routing protocols on wireless sensor networks

Due to its simplicity and efficiency, a recently proposed optimization algorithm, Sine Cosine Algorithm (SCA), has gained the interest of researchers from various fields for solving optimization problems. However, it is prone to premature convergence at local minima as it lacks internal memory. To overcome this drawback, a novel Hybrid SCA-PSO algorithm for solving optimization problems and object tracking is proposed. The P b e s t and G b e s t components of PSO (Particle Swarm Optimization) is added to traditional SCA to guide the search process for potential candidate solutions and PSO is then initialized with P b e s t of SCA to exploit the search space further. The proposed algorithm combines the exploitation capability of PSO and exploration capability of SCA to achieve optimal global solutions. The effectiveness of this algorithm is evaluated using 23 classical, CEC 2005 and CEC 2014 benchmark functions. Statistical parameters are employed to observe the efficiency of the Hybrid SCA-PSO qualitatively and results prove that the proposed algorithm is very competitive compared to the state-of-the-art metaheuristic algorithms. The Hybrid SCA-PSO algorithm is applied for object tracking as a real thought-provoking case study. Experimental results show that the Hybrid SCA-PSO-based tracker can robustly track an arbitrary target in various challenging conditions. To reveal the capability of the proposed algorithm, comparative studies of tracking accuracy and speed of the Hybrid SCA-PSO based tracking framework and other trackers, viz., Particle filter, Mean-shift, Particle swarm optimization, Bat algorithm, Sine Cosine Algorithm (SCA) and Hybrid Gravitational Search Algorithm (HGSA) is presented.

A synergy of the sine-cosine algorithm and particle swarm optimizer for improved global optimization and object tracking

This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented.

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A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context.

Recent development in wireless local area networks have made them potential enough to be used in various applications such as Voice Over Internet Protocol (VoIP), Voice Over Wireless Local Area Network (VoWLAN) and many more. Power saving protocols are used in order to conserve energy. This is addressed at medium access control layer so that wireless radio can be turned on (wake state) and off (sleep state). Here we are using IEEE 802.11 ac systems. Here, multiple groupings, namely, power level, type of service, channel status and type of service per user, have been considered to implement the power saving mechanism. Depending on various parameters within the groups, the energy consumption and delay at the stations has been computed. The proposed grouping based power saving technique reduces the energy and delay as compared to existing protocols such as IEEE 802.11 and S-MAC.

Performance analysis of an improved adaptive power saving technique for IEEE 802.11 ac systems

In this paper, a novel heterogeneous swastika structured hexagonal photonic crystal ring resonator for the realization of universal logic gates is designed using two dimensional photonic crystals. The proposed structure has square lattice of 16× 16 hexagon-shaped chalcogenide glass rods embedded in an air substrate with a refractive index of 3.1. The choice of chalcogenide in the realization of optical logic gates benefits from wide optical windows in the mid-infrared region. Through plane wave expansion method, the contrast ratio for the proposed structures, namely, NAND, NOR, EX-OR, and EX-NOR gate is 22.6 dB, 17.20 dB, 18.3 dB, and 12.78 dB, respectively. Moreover, the footprint of the proposed structure is 9.24μm × 9.24μm.

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Design of Universal Optical Logic Gates Using Heterogeneous Swastika Structured Hexagonal Photonic Crystal Ring Resonator

Wireless sensor network consists of a number of power constrained sensor nodes that sense data from the environment. The collected data is directed to the base station in a harmonized way. Under such circumstances, the foremost challenges of sensor networks are limited energy, system lifetime, latency, quality of information, and limited communication bandwidth. Clustering methods enable to reuse the bandwidth and better resource allocation in order to maintain stable power control. In this paper the election of cluster head among the region cluster members is carried out through Adaptive Buffering with Fuzzy based Multilevel clustering (ABFMC). The proposed algorithm facilitates all nodes to communicate with the base station through a unique number of buffer nodes. Here, the decision based on distance factor is made by the selection of transmission through cluster head. Simulation results show that the proposed ABFMC algorithm provides better network lifetime and efficient energy distribution among the nodes.

Adaptive Buffering and Fuzzy Based Multilevel Clustering for Energy Efficient Wireless Sensor Network

In the recent years there is a drastic improvement in the communication systems. The discovery of Orthogonal Frequency Division Multiplexing technique (OFDM) plays a major role in the high data rate communication system. However, the main drawback of OFDM systems is high Peak to Average Power Ratio (PAPR). Many of the existing PAPR reduction methods have drawbacks such as high complexity, increased Bit Error Rate (BER) and excess redundant information. Recently, precoding techniques has been investigated for PAPR reduction. Due to its low complexity and reduced cost of implementation this technique is an attractive emerging method that yields a substantial reduction of PAPR. In this paper, a novel precoding based on Hadamard Selected Mapping (HSLM) method and genetic algorithm (GA) has been proposed for PAPR reduction in OFDM systems.

A. Rajesh

Papers

Performance analysis of an improved adaptive power saving technique for IEEE 802.11 ac systems

Design of Universal Optical Logic Gates Using Heterogeneous Swastika Structured Hexagonal Photonic Crystal Ring Resonator

Adaptive Buffering and Fuzzy Based Multilevel Clustering for Energy Efficient Wireless Sensor Network

Hadamard based SLM using genetic algorithm fo PAPR reduction in OFDM systems

Design and analysis of multi-channel drop filter using dual L defected hexagonal photonic crystal ring resonator