International Journal of Sensors Wireless Communications and Control - Volume 12, Issue 2, 2022

The Internet of Things (IoT) has become a rising and dynamic research area. It is the integration of numerous objects (things) to communicate information without human beings' intervention. Inappropriately, because of the qualities resource-constrained and limited communication range, it significantly relies upon the Cloud as outsourcing to store and compute the data. This reconciliation of IoT with the Cloud has brought new issues and poses difficulties regarding protection and security threats. The necessity for the wide arrangement of cloud-based IoT is rapidly expanding with significant security-related issues. This work plots existing security methodologies and vulnerabilities near to a portion of the current security strategies by a total review of existing work in the field of security in cloud-based IoT. This paper concentrated on security and protection in terms of privacy by investigating some potential difficulties and risks that should be resolved. The Cloud of Things (CoT) architectures and present applications have been explored and focused on the middleware layer's attacks. Furthermore, this paper outlines a concise scientific classification of the current security threats in cloudbased IoT, plans, and communication. Finally, a few captivating open issues are given with promising designs to trigger more research community research attempts.

A wireless body area network (WBAN) consists of several sensors implanted inside a body or placed on a body that help in the continuous monitoring of health conditions such as heart rate. The sensor nodes transmit the data to a central controller, which serves as a gateway to transmit this information to medical servers and then finally to the hospitals for medical attention. Due to multiple body area networks operating in the same frequency band, inter-interference takes place. The WBAN’s working in a small sphere cause inter-interference resulting in packet-loss and performance degradation. Hence, interference is a complex and challenging problem. Interference mitigations are receiving immense attention from the research community but are far from creating a complete solution. Usage of game theoretic approach to address the interference issues is very promising. This survey paper presents a comparative analysis of the existing game theoretic solutions designed to mitigate interference. As per our knowledge, this is the first survey work based on the usage of the game theory approach for interference mitigation in WBANs.

Aim and Background: The aim of this study is the application of novel deep learning technique of capsule networks for device behavior fingerprinting. Device behavior fingerprinting emerged as an important means to characterize the network behavior of connected devices due to the dynamic nature of smart systems. The study of device behavior fingerprinting strategies gave us an insight into the strengths and weaknesses of different machine learning techniques. It also led us to some research questions that we incorporated in the proposed framework. Firstly, we explored the means to improve the efficiency of passive device fingerprinting techniques. Secondly, we needed to address the privacy concerns that arise from the creation and maintenance of device fingerprints. Objective: To our best knowledge, this is the first time that device for fingerprints had been generated in the form of images. The use of device fingerprints in image form best utilized the object recognition capabilities of capsule networks. Method: We designed a novel method to classify and save the network behaviour of IoT devices that are connected to a network. The proposed model was based on a two-fold innovation of the generation of unique images based on packet parameters of device transmissions, and the design of a model that could carry out efficient and accurate classification of device vendors based on their network behavior. Results and Conclusion: The generation of unique images offered a big advantage of saving the memory of the system. While a packet capture file may take around 150kb or more, the generated images were as small as the order of 2kb. For a smart system made up of thousands of devices, the order of memory space saved would become significant. Furthermore, since the algorithm of image generation could be customized by the network administrators, the images cannot be reverse- engineered by potential attackers, thereby assuring a secure way to save device behavior fingerprints. The developed model has compiled over 500 epochs that roughly translated to 100 minutes and gave the accuracy of the order of 92%. This was the first time that device network behaviour has been translated into an image and tested through classification using capsule networks. The translation of captured packet flows to black and white images not only saved on memory space but also provided a safeguard against reverse engineering by potential attackers. There is a vast scope to further use of this strategy to develop more complex device fingerprinting methods.

Background: The concern with the IoT node is energy since nodes are depleted as their energy utilization is incrementally reduced with the reduction in far off nodes. The nodes will consume energy when it senses the data, followed with the computation, and further for transmission.

Methods: We proposed the phases for energy-saving at nodes by Enhanced Agglomerative Clustering, Dynamic Selection of Leader, disposal of faraway sensor, and B * tree cloud storage and retrieval. In a typical IoT system, the nodes are deployed in the environment initially. Nodes are clustered using Enhanced Agglomerative Clustering Algorithm. A far node elimination will be implemented for the nodes not in the cluster region.

Results: By eliminating the need of far-off sensors, we can reduce the energy used. This in turn can also improve the life of sensors. When appropriate, sensitive data are moved from IoT devices and stored in the cloud.

Conclusion: This paper also proposes an approach to fetch the data from IoT by using the Query Predicate method. This research work proposes a unique choice of grouping by estimating the parameters as energy, separation, thickness and portability.

Background and Objectives: The present issues faced by the transport systems include enormous traffic jams and congestion, unexpected road accidents, unwanted time delays, pedestrians' crossings on main roads, wastage of fuel, and many more. ITS and some other technologies work together to overcome such factors contributing to a much more desirable transport system. This paper aims to identify the security measures that could increase the security of the routing protocol and improve the performance of the DSR routing protocol. If the number of establishing links is frequently broken, then the performance of the DSR routing protocol is not very good. A new modified DSR algorithm has been designed that would help in reducing the network overhead and increase the network quality. A comparison between the performances of both algorithms has also been studied, and the results show that improved DSR routing protocol has better efficiency in parameters like end-to-end network load delays and packet delivery ratio. Methods & Materials: The paper mainly focuses on securing the Dynamic Source routing algorithm by designing its modified version and simulating it. We have Proposed Modified DSR and discussed so far that the basic functionality of the DSR algorithm, its advantages and disadvantages. The main drawbacks include the end-to-end Delay, network overhead and packet delivery ratio. Following is a modified version of the dynamic source routing algorithm, which tries to overcome all the limitations of the basic algorithm at a certain level. In the Dynamic Source Routing algorithm, the Route Maintenance phase is used for the successful propagation of the packet within the network. The nodes that are involved in the transmission acknowledge the receiving of the packet to the preceding node. Results and Discussion: The present study aims at modifying the existing algorithm and designing a new modified algorithm that has less routing overhead, less Delay in packet transmission and high network quality. Modified DSR routing algorithm is examined on the parameters like E-2-E delay, Normalize Routing Overhead, PDR. When we compare the performance of the proposed method with the Existing protocol AODV, and DSR at a number of nodes equal to 50 then we get the Proposed DSR, which has the least end-to-end delay among all the three protocols. Conclusion: In this paper, acomparison of Exiting DSR and Modified DSR in terms of end-to-end Delay, routing load and packet delivery ratio is made. After studying the readings, the conclusion drawn was that there is less network overhead and a high delivery ratio in modified DSR as compared to the existing DSR algorithm. The corrupted and destroyed packets are detected by the receiver, and in DSR, the mobility of mobile nodes is moderate. Under certain conditions, bidirectional and unidirectional links can be accepted. DSR routing protocols are highly dependent on the parameters such as area size, packet size, packet type, and others.

Aims & Objectives: The fast depletion of fossil fuels and the growing awareness of environmental protection have become a concerning topic. Because of this fact, the researchers are working for a long time to generate electrical energy sources due to the intermittent nature of unconventional energy sources such as solar, wind geothermal, tidal, and biomass as a sustainable, cost-effective, and environmentally friendly alternative for conventional energy sources. These systems are interconnected and fulfill demands as well as energy storage, which subsequently formed a complex hybrid renewable energy system. Hence, forecasting of energy generationand sizing of the equipment are essential for the economic feasibility of a complex hybrid system, and also necessary for the design analysis. Methods: In this research article, the proposed Functional Link Convolutional Neural Network (FLCNN) is applied to forecast the energy generation from the hybrid solar and wind energy system. Also, the Jaya algorithm has been applied to find the optimal sizing of the solar and wind-based hybrid renewable energy system. Results & Discussion: The proposed method is simple in design and implementation, and it also reduces computational complexity and time. The proposed FLCNN technique has been compared with various other Machine Learning (ML) methodology, such as Convolutional Neural Network (CNN), Random Forest (RF), and Xg-Boost. In sizing, Jaya is compared with other heuristic techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Cat Swarm Optimization (CSO). Conclusion: The proposed FLCNN and Jaya optimization techniques successfully applied for tasks like energy forecasting and sizing of the renewable energy system.

Background: The massive amount of deployment of Internet of Things (IoT) devices via wireless communications has presented a new paradigm in next-generation mobile networks. The rapid growth in the deployment of IoT devices can be linked to the diverse use of several IoT applications for home automation, smart systems, and other forms of innovations in businesses and industry 4.0. Methods: There is a need for a robust network infrastructure to actualize the huge traffic demand of IoT communications in this new paradigm across the globe, including rural and remote areas. However, due to technical and economic constraints, the terrestrial network infrastructure is not able to fulfill this requirement. Hence, the need for satellite network infrastructure. This solution will be of immense benefit to the provision of remote health care, disaster management, remote sensing, and asset tracking, and environmental monitoring, to name a few. While this remains an interesting solution, packet scheduling, which is one of the key radio resource management functions, is still a challenging issue that remains undefined, especially in a satellite network scenario that has its peculiarities and challenges. Results: Hence, the goal of this research work is to design a new packet scheduling scheme suitable for machine-type communications and also mixed-use case scenarios in satellite network scenarios. The performance evaluation of the proposed packet scheduler is conducted through simulations. Conclusion: The newly proposed packet scheduling scheme provides an improvement of approximately 7 Mbps and 0.5 bps/Hz in terms of throughput and spectral efficiency performances, respectively, in mixed-use case scenarios, when compared to known throughput optimal packet schedulers, without serious compromise to other performance metrics.