FFRP: Dynamic firefly mating optimization inspired energy efficient routing protocol for internet of underwater wireless sensor networks

Energy-efficient and reliable data gathering using highly stable links in underwater wireless sensor networks (UWSNs) is challenging because of time and location-dependent communication characteristics of the acoustic channel. In this paper, we propose a novel dynamic firefly mating optimization inspired routing scheme called FFRP for the internet of UWSNs-based events monitoring applications. The proposed FFRP scheme during the events data gathering employs a self-learning based dynamic firefly mating optimization intelligence to find the highly stable and reliable routing paths to route packets around connectivity voids and shadow zones in UWSNs. The proposed scheme during conveying information minimizes the high energy consumption and latency issues by balancing the data traffic load evenly in a large-scale network. In additions, the data transmission over highly stable links between acoustic nodes increases the overall packets delivery ratio and network throughput in UWSNs. Several simulation experiments are carried out to verify the effectiveness of the proposed scheme against the existing schemes through NS2 and AquaSim 2.0 in UWSNs. The experimental outcomes show the better performance of the developed protocol in terms of high packets delivery ratio (PDR) and network throughput (NT) with low latency and energy consumption (EC) compared to existing routing protocols in UWSNs

QoSRP: A cross-layer QoS channel-aware routing protocol for the internet of underwater acoustic sensor networks

Quality of service (QoS)-aware data gathering in static-channel based underwater wireless sensor networks (UWSNs) is severely limited due to location and time-dependent acoustic channel communication characteristics. This paper proposes a novel cross-layer QoS-aware multichannel routing protocol called QoSRP for the internet of UWSNs-based time-critical marine monitoring applications. The proposed QoSRP scheme considers the unique characteristics of the acoustic communication in highly dynamic network topology during gathering and relaying events data towards the sink. The proposed QoSRP scheme during the time-critical events data-gathering process employs three basic mechanisms, namely underwater channel detection (UWCD), underwater channel assignment (UWCA) and underwater packets forwarding (UWPF). The UWCD mechanism finds the vacant channels with a high probability of detection and low probability of missed detection and false alarms. The UWCA scheme assigns high data rates channels to acoustic sensor nodes (ASNs) with longer idle probability in a robust manner. Lastly, the UWPF mechanism during conveying information avoids congestion, data path loops and balances the data traffic load in UWSNs. The QoSRP scheme is validated through extensive simulations conducted by NS2 and AquaSim 2.0 in underwater environments (UWEs). The simulation results reveal that the QoSRP protocol performs better compared to existing routing schemes in UWSNs

CBI4.0: a cross-layer approach for big data gathering for active monitoring and maintenance in the manufacturing industry 4.0

Industry 4.0 (I4.0) defines a new paradigm to produce high-quality products at the low cost by reacting quickly and effectively to changing demands in the highly volatile global markets. In Industry 4.0, the adoption of Internet of Things (IoT)-enabled Wireless Sensors (WSs) in the manufacturing processes, such as equipment, machining, assembly, material handling, inspection, etc., generates a huge volume of data known as Industrial Big Data (IBD). However, the reliable and efficient gathering and transmission of this big data from the source sensors to the floor inspection system for the real-time monitoring of unexpected changes in the production and quality control processes is the biggest challenge for Industrial Wireless Sensor Networks (IWSNs). This is because of the harsh nature of the indoor industrial environment that causes high noise, signal fading, multipath effects, heat and electromagnetic interference, which reduces the transmission quality and trigger errors in the IWSNs. Therefore, this paper proposes a novel cross-layer data gathering approach called CBI4.0 for active monitoring and control of manufacturing processes in the Industry 4.0. The key aim of the proposed CBI4.0 scheme is to exploit the multi-channel and multi-radio architecture of the sensor network to guarantee quality of service (QoS) requirements, such as higher data rates, throughput, and low packet loss, corrupted packets, and latency by dynamically switching between different frequency bands in the Multichannel Wireless Sensor Networks (MWSNs). By performing several simulation experiments through EstiNet 9.0 simulator, the performance of the proposed CBI4.0 scheme is compared against existing studies in the automobile Industry 4.0. The experimental outcomes show that the proposed scheme outperforms existing schemes and is suitable for effective control and monitoring of various events in the automobile Industry 4.0

Energy efficient and reliable data gathering using internet of software-defined mobile sinks for WSNs-based smart grid applications

The smart grid is an emerging concept that introduces innovative ways to handle the power quality and reliability issues for both service provider and consumers. The key aims of the smart grid (SG) in smart cities (SCs) is to preserve a certain level of residents’ life quality and support the entire spectrum of their economic activities. In this paper, we present a novel Energy Efficient and Reliable Data Gathering Routing Protocol (ODGRP) for wireless sensor networks (WSNs)-based smart grid applications. The developed scheme employs a software-defined centralized controller and multiple mobile sinks for energy efficient and reliable data gathering from WSNs in the SG. The extensive simulation results conducted through the EstiNet 9.0 show that the designed scheme outperforms existing approaches and achieves its defined goals for event-driven applications in the SG

A Multiobjective, Lion Mating Optimization Inspired Routing Protocol for Wireless Body Area Sensor Network Based Healthcare Applications

The importance of body area sensor networks (BASNs) is increasing day by day because of their increasing use in Internet of things (IoT)-enabled healthcare application services. They help humans in improving their quality of life by continuously monitoring various vital signs through biosensors strategically placed on the human body. However, BASNs face serious challenges, in terms of the short life span of their batteries and unreliable data transmission, because of the highly unstable and unpredictable channel conditions of tiny biosensors located on the human body. These factors may result in poor data gathering quality in BASNs. Therefore, a more reliable data transmission mechanism is greatly needed in order to gather quality data in BASN-based healthcare applications. Therefore, this study proposes a novel, multiobjective, lion mating optimization inspired routing protocol, called self-organizing multiobjective routing protocol (SARP), for BASN-based IoT healthcare applications. The proposed routing scheme significantly reduces local search problems and finds the best dynamic cluster-based routing solutions between the source and destination in BASNs. Thus, it significantly improves the overall packet delivery rate, residual energy, and throughput with reduced latency and packet error rates in BASNs. Extensive simulation results validate the performance of our proposed SARP scheme against the existing routing protocols in terms of the packet delivery ratio, latency, packet error rate, throughput, and energy efficiency for BASN-based health monitoring applications

Arsenic in the Soil-Plant-Human Continuum in Regions of Asia: Exposure and Risk Assessment

In this review article, a comprehensive meta-analysis based on available literature information has been undertaken to make a relative comparison of total arsenic in rice grain. This involves analyzing the findings of various peer-reviewed studies that examined arsenic-contaminated Asian regions. Also, this article highlights the regional-level human health risks caused by the consumption of arsenic-contaminated rice in the three regions of Asia. Deriving such information at the continental level is of major importance in view of the need for proper monitoring and alleviating serious and continually emerging human health issues in arsenic-contaminated areas. One aim of this paper is to highlight the potential of a viable modeling approach for appraising the danger posed by arsenic in soil-plant-human system. There is an urgent need to fix the safe limit of bioavailable arsenic in soil because total arsenic in soil is not a good index of the arsenic hazard. Our hypothesis is finding out whether the modeling approach can be used in establishing a safe limit of bioavailable arsenic in soils with reference to human health. To achieve the above-mentioned objectives, we have selected reported rice grain arsenic content data from Asian countries following the PRISMA guidelines. Carcinogenic and non-carcinogenic risk was calculated following the US EPA’s guidelines. It emerged that adults in Asian countries are prone to a high risk of cancer due to their consumption of arsenic-contaminated rice. South Asia (SA), South East Asia (SEA), and East Asia (EA) exceeded the US EPA-prescribed safe limit for cancer risk with ~ 100 times higher probability of cancer due to rice consumption. The hazard quotient for the ingestion of arsenic containing rice was 4.526 ± 5.118 for SA, 2.599 ± 0.801 for SEA, and 2.954 ± 2.088 for EA. These figures are all above the permissible limit of HQ of 1. The solubility free ion activity model can predict arsenic transfer from soil to rice grain based on easily measurable soil properties and be used to fix the safe limit of bioavailable arsenic in paddy soils. The methods and findings of this review are expected to be useful for regional-level policymaking and mobilizing resources to alleviate public health issues caused by arsenic

An insight into microbes mediated heavy metal detoxification in plants : a review

In this era of rapid industrialization and modernization, contamination of the environment with heavy metals from natural and anthropogenic sources without proper disposal treatment is a global concern. Huge amounts of toxic heavy metals (HM) released through industrial, agricultural, and military practices into the environment lead to pernicious effects on soils, water, and air. Deposited toxic HM beyond certain permissible limits is producing an obnoxious effect not only on the soil but also on human and animal health. Application of physical and chemical processes for HM remediation is expensive, laborious, and non-sustainable. Under metal stress, soil microbes have developed various mechanisms to cope with metal toxicity. They can accumulate, alter, or detoxify HM. Therefore, the exploitation of microbes acquiring metal detoxifying traits in addition to plant beneficial attributes make the metal remediation process eco-friendly and cost-effective. Plant–microbe interactions aiming at HM stress may provide a new way to existing phytoremediation and rhizoremediation uses. This review includes a brief insight into heavy metal pollution, their effect on plant biology, and metal-microbe association and highlights the various mechanisms of microbes mediated heavy metal detoxification in plants