International Journal of Wireless and Ad Hoc Communication

In this paper, we introduce the design of a digital frequency modulation receiver using FPGA. The main component in the design is digital phase locked loop (DPLL) which compensate any changes between the frequency and phase of the input modulated signal and the frequency and phase of numerically controlled oscillator.    The input to the receiver is 8-bit represents the sampled discrete time signal from the analog modulated received frequency modulation signal. The receiver is designed using Xilinx system generator and implemented on the FPGA board (Xilinx Vitrex-7 XC7VX550t board), works with 350 MHz and consumes 120 mW. 

Internet of Things (IoT) is a technological innovation that defined interaction and computation of latest period. The objects of Internet of Things would empower by embedded gadgets whose limited sources has to be managed effectively. IoT usually means a network of devices connected through wireless network and interacts through internet. Resource management, particularly energy management, becomes a serious problem while devising IoT gadgets. Numerous researchers stated that routing and clustering were energy effectual solutions for optimum resource management in IoT setting. This study introduces a Modified Flower Pollination Algorithm based Resource Management (MFPA-RMM) model for Clustered IoT Environment. The presented MFPA-RMM model majorly focuses on the clustering the IoT devices in such a way that the resources are proficiently managed. The MFPA-RMM model is derived based on the fuzzy c-means (FCM) with FPA. The FPA approach is called heuristic algorithm has benefits of global optimization and faster convergence, therefore it was incorporated to FCM system for resolving the advantages and disadvantages of FCM method termed FCM-FPA mechanism. The result analysis of the MFPA-RMM model reported the enhanced performance of the MFPA-RMM model over other well-known techniques like LEACH and TEEN.

Wireless communication inculcates transfer of information not having any physical connection among two or more points. The significant operation of a sensor network becomes collecting and forwarding data to destiny. It is highly crucial to have an awareness regarding the place of collected data. This data is acquired by leveraging localization method in wireless sensor networks (WSNs). Localization is a way of determining the sensor nodes (SNs) location. Localization of SNs turns out to be an exciting research area, and several studies were performed till now. It is very favourable to model scalable, effectual, and low-cost localization systems for WSNs. This study develops a Leopard optimization based Node Localization Technique for Wireless Communication (LONLT-WC). The goal of the LONLT-WC model is to recognize the location of the nodes involved in the network. The LONLT-WC model involves the design of snow leopard optimization (SLO) algorithm, inspired from the characteristics of snow leopards.  The presented LONLT-WC approach computes the unidentified location of the nodes utilizing anchor nodes in the network with the accomplishment of least error rate. The experimental analysis of the LONLT-WC model involves a series of simulations and the results highlighted the betterment of the presented technique.

Charging points on islands are becoming highly essential due to growing environmental concerns and an increase in the number of electric ships that need to be recharged. Site choice is the first step, but there is not enough research on island photovoltaic charging station site selection (IPVCS). To select the best IPVCS site, a multi-criteria decision-making framework (MCDM) is proposed. As a result of this structure, a new set of criteria for evaluating ships is formed, and current criteria are used to suggest two new ones: "Likelihood of adverse weather" and "Charging distance of the ship." Simultaneously time, the correlation among criteria is shaky at best. Therefore, the weight of the criteria is determined first. Then the rank of the alternatives is computed by the simultaneous evaluation of criteria and alternatives (SECA). Multi-criteria techniques like SECA may be used to objectively and accurately determine the weights of criteria. The best alternative is PVC3 followed by PVC1 then PVC2 then PVC4.

Largescale IoT applications with thousands of geo distributed IoT gadgets making huge volumes of data impose immense challenges to designing transmission mechanisms that offer data transfer has less latency and great scalability. In this work, an investigation of a hierarchical Edge-Cloud publishes or subscribe brokers method was performed with the help of an effective two-tier routing structure for alleviating such problems whenever sending event notices in large scale IoT mechanisms. In this technique, IoT gadgets use the benefits of nearby edge brokers deliberately positioned in edge network for data supplying services for minimizing latency. This manuscript introduces a Novel Metaheuristic Optimization based Clustering with Routing Scheme for IoT Mobile Edge Computing Platform, named MOCRS-IoTMEC model. The projected MOCRS-IoTMEC model is mainly concentrated on the identification of optimal routes in the IoT assisted MEC environment by the use of pigeon inspired optimization (PIO) algorithm. Also, the LEACH protocol is applied to initially cluster the IoT devices. The PIO algorithm is applied to determine the fitness function to choose optimal routes. To depict the enhanced performance of the MOCRS-IoTMEC model, a detailed comparison study is made. The experimental outcomes reported the enhanced execution of the MOCRS-IoTMEC method over other approaches.

This research proposes a novel procurement process for road traffic analysis by using the information error-based Pythagorean fuzzy cloud (PFC) method. First, a 20-factor assessment index method for road traffic was developed. The notion of PFCs was devised to represent the assessment information of an indication. Concurrently, the PFC-weighted Bonferroni mean (PFCWBM) operator was created to aggregate the evaluation data of multiple indications. Then, a method for evaluating and selecting road traffic based on the PFCWBM operator was developed. Furthermore, an application for demonstrating the efficacy of the suggested method was provided. Finally, the effectiveness of the proposed method was evaluated. Results demonstrate that our algorithm can define and assess complicated data with relatively high susceptibility and environmental adaptation.