A. Rajesh

Bio: A. Rajesh is an academic researcher from VIT University. The author has contributed to research in topics: Wireless sensor network & Node (networking). The author has an hindex of 7, co-authored 40 publications receiving 336 citations. Previous affiliations of A. Rajesh include Pondicherry Engineering College.

Clusterhead selection using Huffman coding algorithm for Wireless Sensor Networks

Abstract: Energy efficiency is a major concern in WSNs due to the use of small sized batteries which can neither be replaced nor be recharged Hence the energy consumption must be as low as possible One of the traditional approaches used is clustering Clusters are formed for efficient energy utilization and improving the network performance In the proposed algorithm, cluster heads are chosen depending on the Huffman coding algorithm The nodes having the least weight are chosen to be cluster heads The result obtained is compared with LEACH and the performance is increased by 30% than LEACH

Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe

Abstract: Underwater Wireless Sensor Networks (UWSNs) have recently established themselves as an extremely interesting area of research thanks to the mysterious qualities of the ocean. The UWSN consists of sensor nodes and vehicles working to collect data and complete tasks. The battery capacity of sensor nodes is quite limited, which means that the UWSN network needs to be as efficient as it can possibly be. It is difficult to connect with or update a communication that is taking place underwater due to the high latency in propagation, the dynamic nature of the network, and the likelihood of introducing errors. This makes it difficult to communicate with or update a communication. Cluster-based underwater wireless sensor networks (CB-UWSNs) are proposed in this article. These networks would be deployed via Superframe and Telnet applications. In addition, routing protocols, such as Ad hoc On-demand Distance Vector (AODV), Fisheye State Routing (FSR), Location-Aided Routing 1 (LAR1), Optimized Link State Routing Protocol (OLSR), and Source Tree Adaptive Routing—Least Overhead Routing Approach (STAR-LORA), were evaluated based on the criteria of their energy consumption in a range of various modes of operation with QualNet Simulator using Telnet and Superframe applications. STAR-LORA surpasses the AODV, LAR1, OLSR, and FSR routing protocols in the evaluation report’s simulations, with a Receive Energy of 0.1 mWh in a Telnet deployment and 0.021 mWh in a Superframe deployment. The Telnet and Superframe deployments consume 0.05 mWh transmit power, but the Superframe deployment only needs 0.009 mWh. As a result, the simulation results show that the STAR-LORA routing protocol outperforms the alternatives.

Performance analysis of an improved CSI feedback technique for LTE-A system with Femtocell Interference

Abstract: The major challenge in Long Term Evolution Advanced (LTE-A) based 5G network is to improve the cell capacity and cell coverage of indoor users. To fulfill these demands, low power Femto Base stations are deployed at homes and company premises. Such heterogeneous network introduces interference due to both Femtocell and microcell users, especially for cell edge users as the frequencies are reused intrusively. In this Paper, we are introduce a modified dirty paper coding technique to mitigate the effect of inter-cell interference. To reduce the effect of interference, each user feedback quantize CSI to base station and then appropriate precoding is done on transmitted signal. Here, we are compare the sum rate of the Modified Dirty Paper Coding and Zero-Forcing technique. Simulation results shows that sum rate of Modified dirty paper coding is 23% more than Zero-Forcing technique.

Localization of Co-operative Sensor Network and UAV using Bio-inspired Optimization Technique

Abstract: Localization plays an important role in wireless sensor network since sensor nodes are distributed all over the place for sensing and collection of data, so it is mandatory for a node to identify its location. In most of the cases sensor nodes sense the information without knowing its current location which is not a useful one. Installing GPS device on each node in a large network is not possible since it is very cost expensive. Deploying many anchor nodes in a network is also an expensive one. These issues can be handled by deploying movable Unmanned Aerial Vehicle in the network. Techniques have been developed to find out the location of sensor nodes. In this paper localization is carried out using range based technique such as Received signal strength indicator. Signal strength can be measured by the received signal strength indicator, but it produces high localization error. To solve high localization error, new algorithm named as Spider monkey optimization is used in this paper.

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

Abstract: 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.

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

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

Abstract: 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.