In a wireless local area network (WLAN), 802.11ac protocol is commonly accepted due to its fast communication technology at 5GHz. For effective design of WLAN system, previously, we have studied link speed estimation model of 802.11n links that estimates the link speed among an AP and a client PC in the network field. However, it does not assume the shadowing effect which has great influence on the Received Signal Strength (RSS), especially in a complex network environment. In shadow fading, the RSS fluctuates due to the reflection, refraction, and scattering, which is characterized as small scale fading. Therefore, to achieve more accuracy in link speed estimation, it is crucial to consider shadow fading effect in link speed estimation model. In this paper, we present modification of link speed estimation model by considering shadow fading factor. First, we show the RSS and link speed measurement results of 802.11ac MIMO link to derive estimation model parameters including shadow fading factor. Then, by considering this shadow fading parameter we modify estimation model. Finally, we show the link speed estimation results which reveal that our modified model provides better accuracy than previous model.

Agriculture plays a significant role in every nation's economy by producing crops. Plant disease identification is one of the most important aspects of maintaining an agriculturally developed nation. The timely and efficient detection of plant diseases is essential for a healthy and productive agricultural sector and to prevent wasting money and other resources. Various diseases that could affect a plant cause crop farmers to lose a substantial sum yearly. Deep learning can play a crucial role in helping farmers prevent crop failure by early disease detection in plant leaves. In the experiment, we examined CNN, VGG-16, VGG-19 and ResNet-50 models on plant-village 10000 image dataset to detect crop infection and got the accuracy rate of 98.60%, 92.39%, 96.15%, and 98.98% for CNN, VGG-16, VGG-19 and ResNet-50 respectively. The study indicates that ResNet-50 outperforms the other models with an accuracy of 98.98%. So, the ResNet50 model was chosen to be developed into a smart web application for real-life crop disease prediction. The proposed web application aims to assist farmers in identifying diseases of plants by analyzing photos of the plant leaves. The proposed application uses the ResNet50 transfer learning model at its heart to distinguish healthy and infected leaves and classify the present disease type. The goal is to help farmers save resources and prevent economic loss by detecting plant diseases early and applying the appropriate treatment.

Bangladesh has been using fossil fuel sources for the last years to generate electricity.The electricity power generation capacity of Bangladesh must enlarge to support the increasing electricity demand nowadays.As the conventional fuel resources are limited on the earth, renewable resources (ex: PV, wind) must be used in the future.The aim of this study is to design a hybrid electricity and hydrogen production system with the photovoltaic, wind turbine, hydro, diesel generator, electrolyzer, and reformer using Hybrid Optimization Model for Electric Renewable (HOMER) software under the study area Delduar, Tangail, Bangladesh (24 0 8.5 / N, 89 0 54.1 / E).This research focuses on maximum electricity generation using renewable energy sources with a minimum cost of energy (COE).According to the Homer optimization model, the levelized cost of energy (COE) based on a PV-wind-hydro-diesel generator-electrolyzerreformer-battery hybrid electricity generation system is $0.281, the net present cost is $3.22 million, and operating cost $60,401 with 99.5% renewable fraction respectively.Furthermore, the analysis confirms that hybrid PV-wind-hydrodiesel generator-hydrogen power plant construction in Delduar, Tangail area is economically feasible.

Cotton is known as ‘white gold’ in the agricultural industry. Agriculture is the primary source of economic income in Bangladesh and the country's economy is heavily dependent on agriculture. The soil and water resources of our country are fertile and the climate is moderate. But numerous diseases affect crop production and cause enormous crop losses, endangering the lives of helpless farmers. A previous report showed that about 70–80% of cotton diseases were leaf diseases and 30–20% were pest diseases. Experts typically use bare eyes to find and identify such plant diseases and pests which may result from lower accuracy of the identification. As a result, early detection of cotton disease using AI-based systems may help to increase the production of cotton by detecting the leaf disease significantly. In this research, we proposed a DL-based cotton leaf disease detection approach using fine-tuning Transfer Learning (TL) algorithms by tuning the layers and parameters of the existing TL algorithms. We also investigated the performance of several fine-tuning TL models such as VGG-16, VGG-19, Inception-V3 and Xception on the publicly available cotton dataset for cotton disease prediction. The investigations found that the Xception model provides the highest accuracy rate of 98.70% and was selected to develop a web-based smart application for real-life cotton disease prediction in farming to increase cotton production. Hence, our model can accurately diagnose cotton leaf diseases and will provide a new window for the automatic leaf disease diagnosis of other plants.

The escalating demand for swift and dependable wireless internet access has spurred the development of various protocols within 802.11 WLANs. Among them, the 802.11ac protocols have gained widespread acceptance over the past few years, offering enhanced data transfer rates compared to the 802.11n standard. However, the persistent congestion of wireless IoT devices, particularly in densely populated areas, remains a significant challenge. To tackle this issue, IEEE 802.11 has advanced IEEE 802.11ax as the successor to 802.11ac, introducing critical enhancements at the PHY/MAC layers to improve throughput in dense scenarios. Additionally, modelling and simulating these protocols are vital for WLAN researchers and designers to anticipate link characteristics effectively, fostering high-performance WLAN design. The need for such tools led to the creation of diverse network simulation programs, and NS-2 is widely accepted as an open-source program that has achieved remarkable success in research. In this paper, we focus on various connection properties of 802.11ax WLANs through NS-3 simulations, including MCSs, bonded channels, GI, data encoding, antennas, data rates, link distance, Tx/Rx power, gain, and payload size. We also compare their performance against 802.11ac, which demonstrates that NS-3 accurately supports most 802.11ax capabilities and outperforms 802.11ac in various scenarios.

In Mobile Ad-hoc Network (MANET), portable devices like smartphones, or laptop PC can join together to make provisional networks without any infrastructure The objective of multicast or unicast protocols is to ensure an efficient route formation and flow control mechanism which is a very challenging issue for many group computing services in MANETs. MANETs can support several real-time applications like emergency rescue, and disaster relief operations which require minimum Quality of Service (QoS) to handle high traffic. Providing QoS for multimedia and group-oriented computing in MANETs becomes a real challenge due to the wireless medium and the mobility of operating nodes. Therefore, an investigation of routing protocols for one-to-many or many-to-many computing is important that supports acceptable QoS in MANETs. Numerous QoS metrics have been considered for the assessment like packet delivery ratio, latency, packet loss rate, control overhead, and throughput. By considering different network topologies and scenarios with different performance parameters, the primary goal of this study is to explore the challenges and factors for QoS services in MANET’s multicast communication. The outcomes of investigation can be used to design the future MANET protocol for multimedia applications. The performance results indicate that the increasing number of sending/receiving nodes may increase the overhead or latency of the network but capable of providing higher network throughput, carried out in NS-2. The results also indicate although MANETs can induce errors and packets are lost as part of the normal operating context, multicast AODV practice superior to the unicast protocol to various QoS in a wide range of scenarios with less overhead.

For an efficient design of wireless local-area networks (WLANs), the simulation tools are important to accurately estimate the IEEE 802.11n/ac link features for WLANs. However, this true simulation of network behavior is critical in designing high-performance WLANs. Through testing, analysis, and modeling of the proposed scheme repetitively, the design of the WLAN can be enhanced with a small budget before making its practical implementation. Many network simulation tools have been established to give solutions for this request and ns-3 is the most widely used tools among them by the research industry as an open-source network simulator. In this paper, we examine the various link features of the 802.11n WLANs under several conditions. We investigate the effects of 802.11n WLAN modulation and coding schemes (MCSs), 20MHz single channel or 40 MHz bonded channel, guard intervals (GI), frame aggregation, data encoding, number of antennas and their data rate, and link distance features of 802.11n WLAN in ns-3 when only a unique host connects with the access point (AP) and generates data traffic. Besides, the performance for an enterprise scenario proposed by the IEEE 802.11ax study group is evaluated when several hosts are simultaneously creating traffic with their associated APs. The results demonstrate that ns-3 support most of the link features of the 802.11n protocol with significant accuracy.

In the era of "big data," a huge number of people, devices, and sensors are connected via digital networks and the cross-plays among these entities generate enormous valuable data that facilitate organizations to innovate and grow. However, the data deluge also raises serious privacy concerns which may cause a regulatory backlash and hinder further organizational innovation. To address the challenge of information privacy, researchers have explored privacy-preserving methodologies in the past two decades. However, a thorough study of privacy preserving big data analytics is missing in existing literature. The main contributions of this article include a systematic evaluation of various privacy preservation approaches and a critical analysis of the state-of-the-art privacy preserving big data analytics methodologies. More specifically, we propose a four-dimensional framework for analyzing and designing the next generation of privacy preserving big data analytics approaches. Besides, we contribute to pinpoint the potential opportunities and challenges of applying privacy preserving big data analytics to business settings. We provide five recommendations of effectively applying privacy-preserving big data analytics to businesses. To the best of our knowledge, this is the first systematic study about state-of-the-art in privacy-preserving big data analytics. The managerial implication of our study is that organizations can apply the results of our critical analysis to strengthen their strategic deployment of big data analytics in business settings, and hence to better leverage big data for sustainable organizational innovation and growth. This article is categorized under: Commercial, Legal, and Ethical Issues > Security and Privacy Fundamental Concepts of Data and Knowledge > Big Data Mining Fundamental Concepts of Data and Knowledge > Data Concepts

Nowadays, the wireless local-area network (WLAN) has been deployed everywhere as a common access medium to the Internet. In WLAN, the network configuration should be optimized according to traffic demands and network environments which will change dynamically. Therefore, we have studied the active AP configuration algorithm for the elastic WLAN system to achieve the elasticity of WLAN. However, this algorithm requires a long CPU time in the large search space when numerous APs are deployed in the field. In this paper, we propose a preprocessing stage for the AP configuration algorithm to reduce the CPU time by limiting the number of APs in advance. Both the exhaustive and heuristic approaches are adopted, where either one should be used depending on the network topology. Through extensive simulations using the WIMNET simulator, the effectiveness of the proposal is verified.

As a flexible and cost-efficient internet access network, the IEEE 802.11 wireless local-area network ( WLAN ) has been broadly deployed around the world. Previously, to improve the IEEE 802.11n WLAN performance, we proposed the four-step minimax access-point ( AP ) setup optimisation approach : 1) link throughputs between the AP and hosts in the network field are measured manually; 2) the throughput estimation model is tuned using the measurement results; 3) the bottleneck host suffering the least throughput is estimated using this model; 4) the AP setup is optimised to maximise the throughput of the bottleneck host. Unfortunately, this approach has drawbacks: 1) a lot of manual throughput measurements are necessary to tune the model; 2) the shift of the AP location is not considered; 3) IEEE 802.11ac devices at 5 GHz are not evaluated, although they can offer faster transmissions. In this paper, we present the three enhancements: 1) the number of measurement points is reduced while keeping the model accuracy; 2) the coordinate of the AP setup is newly adopted as the optimisation parameter; 3) the AP device with IEEE 802.11ac at 5 GHz is considered with slight modifications. The effectiveness is confirmed by extensive experiments in three network fields.

—Recently, Raspberry Pi has become popular around the world as an inexpensive, small, and powerful computing device. We have studied its use as the software access-point (AP) for the IEEE 802.11n wireless local-area network (WLAN), where the channel bonding (CB) can increase the throughput by bonding two channels into one. However, the built-in wireless network interface card (NIC) adapter fails to support the CB. Thus, we have configured the CB using external NIC adapters, and investigated the throughput performance and estimation model for only one link between a PC host and a Raspberry Pi AP. In this paper, we present the throughput measurement for concurrent communications of multiple links with up to three APs under different adapters and channels with 11 and 13 partially overlapping channels (POCs) at 2.4GHz. Besides, we extend the throughput estimation model by introducing the throughput drop factor to consider interferences between the links. This factor can be derived from the CB use and the assigned channels for the links. The effectiveness of the proposal is verified by comparing the estimated throughput with the measured one.

To design an efficient wireless local-area network (WLAN), we have studied the throughput estimation model for the IEEE 802.11n link both in indoor and outdoor environments. This model first estimates the received signal strength (RSS) at the receiving node using the log distance path loss model. Then, it converts RSS to the throughput using the sigmoid function. The parameters in these functions are optimized by applying the parameter optimization tool to measurement results. In this paper, we examine the throughput estimation model for the Multiple Input Multiple Output (MIMO) link in IEEE 802.11n. MIMO link can increase the transmission capacity using multiple streams. First, throughput measurements for MIMO links are conducted using commercial devices and software in three network fields. Then, using the results, the parameters in the model are optimized by the tool. The evaluation results show that this model can estimate throughputs with considerably high accuracy in any field when compared with the ns-3 network simulator. Besides, the model is modified to improve the accuracy when multiple hosts are communicating with one access point (AP) simultaneously.

The active AP configuration algorithm has been proposed to optimize the configuration of the elastic WLAN system that dynamically changes the topology depending on traffic demands and environments. The multiple-input multiple-output (MIMO) is the technology to enhance the transmission capacity by adopting multiple antennas. It is common for access-points (APs) but is still rare for hosts. Thus, the location optimization for MIMO hosts in the field appears to be a contributing factor in improving the performance. In this paper, we study the MIMO host location optimization as an extension of the active AP configuration algorithm. The concurrent communications of multiple hosts with a single AP offer different throughput features from the single communication, which is considered. The effectiveness is verified through simulations and simple testbeds.

Recently, a wireless local-area networks (WLANs) has become prevalent around the world due to the low-cost and flexible internet access by wireless communications between user hosts and access points (APs) in the network. Previously, we proposed the active AP configuration algorithm for the elastic WLAN system that dynamically optimises the network configuration by activating/deactivating APs and assigning the channels and associated hosts depending on network situations. However, it assumed that only single-input-single-output (SISO) links are used, although multiple-input-multiple-output (MIMO) links have become popular for fast communications. Currently, most commercial APs can use MIMO, while a subset of hosts can use it, referred as MIMO hosts in this paper. Then, by optimising the locations of MIMO hosts, the performance of the network is expected to be improved. In this paper, we present the MIMO host location optimisation as the extension of the active AP configuration algorithm. Through simulations in two network topologies using the WIMNET simulator, the throughput improvements by this proposal are confirmed.

Recently, Wireless Local Area Networks (WLANs) have increased popularity around the world, where users can easily access to the Internet through associations with access points (APs) using mobile devices like smart phones, tablets, and laptops. In a WLAN, it is common that the number of users is always changing by time and users are not evenly distributed in the field. To optimize the number of active APs and the host associations in the network depending on traffic demands from users, previously, we proposed the AP configuration algorithm for the elastic WLAN system. Unfortunately, this algorithm can find the solution for the fixed user state in the network, although users often repeat joining and leaving the network. In this paper, we propose the extension of the AP configuration algorithm to deal with this dynamic nature. Here, as practical situations, this extension considers that at most one host may join or leave at the same time, and any communicating AP cannot be suspended and any communicating host cannot change its associated AP. Through numerical experiments using the WIMNET simulator in two network instances, the effectiveness of the proposal is demonstrated. Furthermore, it is implemented in the elastic WLAN system testbed using Raspberry Pi for the AP. The performance of this implementation is verified through experiments in four scenarios.

Nowadays, various types of access-points (APs) and hosts such as dedicated APs, laptop personal computers, and mobile terminals have been used in IEEE802.11 wireless local-area networks (WLANs). As a result, the optimal assignment of holding APs into the network field depending on the host type distribution has become very important to improve the network performance. In this paper, we formulate this holding access-point assignment problem as a combinatorial optimization problem and propose its heuristic algorithm. Because plural non-overlapping channels are available in IEEE802.11 WLANs, we extend the algorithm to finding the channel assignment to the APs such that the total interference among them is minimized. The effectiveness of our proposal is verified through simulations in three instances.