ABSTRACT This paper introduces an innovative Light‐Weight Consensus model for Context‐Sensitive Side Chains (abbreviated as LWC2S2C) to enhance the efficiency of consensus mechanisms within blockchain networks. The proposed model adopts a multifaceted approach, taking into account many intricate parameters including the number of blocks within the sidechain, the architecture of each block, the performance metrics of individual miners, and the complicated interplay between source nodes and miner nodes. These various metrics are combined to give each miner a unique rank, which affects their chances of being chosen for the important block validation process. The consequential discoveries derived from this comprehensive analysis reveal that the LWC2S2C model eclipses its contemporary counterparts in consensus mechanisms. Through the meticulous examination of performance benchmarks, including mining delay, energy consumption, and throughput, within diverse application scenarios, namely Electronic Health Records (EHR), Internet of Medical Things (IoMT), and Enterprise Resource Planning (ERP), the LWC2S2C consistently manifests an enviable supremacy. Remarkably, it outpaces the Practical Byzantine Fault Tolerance (PBFT) by an impressive 10.5%, surpasses the Proof of Practicality and Trust (PoPT) by a striking 14.6%, and leaves the Improved Proof of Trust (IPoT) behind by an astonishing 18.4% in the context of mining delay. Furthermore, in the case of energy efficiency, the LWC2S2C model consumes 6.2% less energy compared to PBFT, 10.5% less energy compared to PoPT, and a substantial 16.8% less energy when contrasted with IPoT. These findings emphatically underscore the scalability, efficiency, and low energy footprint that the LWC2S2C model brings to the fore. The obtained results demonstrate that LWC2S2C reaches highly awarding inference tailored to the exigencies of sidechain‐based applications.

This study presents a hybrid multi-generation energy system designed to overcome solar intermittency while meeting the global demand for integrated delivery of electricity, water, cooling, and sustainable fuels in the transition to decarbonization. The engineering application integrates solar thermal and wind energy with a modified Brayton cycle, a Steam Rankine Cycle (SRC), and a Thermoelectric Generator (TEG) to simultaneously produce electricity, fresh water via Reverse Osmosis (RO), hydrogen and oxygen via Proton Exchange Membrane Electrolyzer (PEME), and cooling (via absorption chiller) within a unified optimization framework. The system was modeled using Engineering Equation Solver (EES) and optimized via Response Surface Methodology (RSM) based on 11 decision variables. To address the complexity of optimization, a second phase applied Artificial Intelligence (AI) techniques: Adaptive Boosting (AdaBoost) for predictive modelling and Particle Swarm Optimization (PSO) for global optimization. Under optimal conditions, the Response Surface Methodology yielded an exergy efficiency of 45.8 % with a cost rate of 576.76 United States Dollars per hour (USD/h), while AI reduced costs to 211.2 USD/h with a moderate efficiency trade-off. Simulation of the optimized configuration across eight diverse climates identified Quebec as most viable, generating 22,629.6 Megawatt-hours per year (MWh/year) of electricity and avoiding 4616.4 tons of Carbon Dioxide (CO 2 ) emissions annually. Integration of wind energy stabilizes solar variability, enhancing performance. AI contributes to optimizing complex interactions, nonlinear constraints, and multiple conflicting objectives. The methodology offers a scalable, generalizable framework for designing intelligent, climate-resilient infrastructures. Future research includes AI-enabled real-time control, experimental validation, and broader deployment strategies.

Digital Image Processing (DIP) is the ability to manipulate digital photographs via algorithms for pattern detection, segmentation, enhancement, and noise reduction. In addition, the Internet of Things (IoT) acts as the eye and system for all DIP in various applications. It can possess a camera or another image sensor in order to capture real-time data from its environment. All vital data is processed by image processing in such a way that it recognizes the object, detects an anomaly, and automatically decides in real-time. In addition, in an IoT system, the median filter is the technique used for noise reduction by substituting the value of the pixel with the central value of the surrounding pixels. It provides speed and efficiency for quick analysis in all IoT systems. However, the images can get corrupted, especially in resource-constrained IoT devices with small cameras, because of random glitches. Moreover, using new quantum technology like atomic-scale silicon dangling bond (DB) logic circuits, which have advanced in fabrication and become a strong contender for field-coupled nano-computing, can solve previous problems in IoT systems. In this paper, we propose a unique quantum CSM based on two new proposed Mux and De-mux. The proposed CSM can be used for computational circuits like median filter circuits (MFC) in a wide range of digital circuits, specifically IoT devices. The proposed design is verified and validated using the powerful SiQAD tool. When comparing CSM to the newest designs, the suggested quantum circuit uses 85% less energy and takes up 61% less area.

Summary Internet of Things (IoT) is a new phenomenon that proposes novel business opportunities. IoT allows the world to be programmable and might provide several benefits for organizations. Based on the IoT survey, cyber‐security issues are among the most extensive and complicated challenges faced by IoT devices. Threat detection is considered a preventive measure against malware threats, ransomware, and attacks, which become more serious each year because of the dramatic rise in malware attacks. This article investigates threat detection techniques that fall into three categories: malware detection, attack detection, and ransomware detection, published from 2017 to August 2021. We examine solutions, techniques, features, classifiers, and tools proposed by IoT researchers. Some questions are proposed, and answering the questions may help the researchers suggest a more efficient solution in future works. Furthermore, the achievement and disadvantages of each study are discussed. Finally, based on the reviewed studies, some open challenges and practical measures to future directions are suggested, worth further studying and researching threat detection techniques in the IoT.

Abstract The growth of the world's population, especially that of the elderly, along with the outbreak of infectious diseases such as COVID‐19 have caused hospitals and healthcare centres to become full, and even economical treatments cost a lot. On that account, the conjunction of wireless body area networks (WBAN) and Internet of Things (IoT) for healthcare and medical diagnosis has become really important, and is accordingly one of the most popular and attractive areas of the Internet of Things (IoT). In such an IoT, a wireless body area network (WBAN) consists of a miniature sample of the Internet of Medical Things (IoMT) that can be either implanted in the human body or wearable. Nowadays, IoT has made healthcare evaluation possible. Instead of the patient being constantly hospitalized for treatment, the condition of the person is sent to the health centre by the IoMT over the Internet. IoT enables wireless communication between smart devices on one side and almost anything on the other. Since this network deals with medical and critical conditions, data must be sent to a physician or practitioner in the prescribed period; this indicates that routing is one of the most critical issues. Thus, routing is considered a very important challenge in WBANs. The present study describes thermal (temperature)‐aware routing protocols in WBANs. Routing protocols in WBANs are divided into thermal (temperature)‐aware, QoS‐aware, security‐aware, cluster‐based, cross‐layered, postured‐based, cost‐effect, link‐aware, and opportunistic ones. In a WBAN, temperature rise in implant nodes can damage body tissues, which is dangerous for the patient. Accordingly, here, those algorithms were considered which are presented in thermal (temperature)‐aware protocols. This paper first introduces IoT‐based WBANs, their routing mechanism and challenges, after which it provides a detailed description of thermal (temperature)‐aware algorithms. Finally, the advantages and disadvantages of these algorithms are presented.

In the world of the Internet of Things (IoT), wireless sensor networks (WSNs) are an impressive technology. These networks are extremely resource constrained and require the design of energy-efficient routing techniques. The clustering and location prediction routing method based on multiple mobile sinks (CLRP-MMSs) for the Mobile Internet of Things (MIoT) is presented in this article. Recently, mobile sinks are used in routing more durability and energy saving in WSN. In this work, first, the entire nodes are divided into clusters, and then each cluster selects a cluster head (CH) by calculating the CH choosing function (CHCF). When clustering runs on networks with moving nodes, the possibility of disconnecting the nodes from CH nodes will cause a lot of data loss. It will change the amount of energy and rate of data received, but the amount of wasted energy is reduced by predicting the location and reducing the sink and CH nodes' distance. The simulation results using NS-2 clearly showed that the proposed method improves energy consumption at least 28.12% and increases throughput at least 26.74% compared to energy efficient routing algorithm with mobile sink support and high-available and location-predictive data gathering scheme using mobile sink methods.

Information and communication technology (ICT) is one of the sectors that have the highest energy consumption worldwide. It implies that the use of energy in the ICT must be controlled. A software‐defined network (SDN) is a new technology in computer networking. It separates the control and data planes to make networks more programmable and flexible. To obtain maximum scalability and robustness, load balancing is essential. The SDN controller has full knowledge of the network. It can perform load balancing efficiently. Link congestion causes some problems such as long transmission delay and increased queueing time. To overcome this obstacle, the link load balancing strategy is useful. The link load‐balancing problem has the nature of NP‐complete; therefore, it can be solved using a meta‐heuristic approach. In this study, a novel energy‐aware dynamic routing method is proposed to solve the link load‐balancing problem while reducing power consumption using the multi‐objective artificial bee colony algorithm and genetic operators. The simulation results have shown that the proposed scheme has improved packet loss rate, round trip time and jitter metrics compared with the basic ant colony, genetic‐ant colony optimisation, and round‐robin methods. Moreover, it has reduced energy consumption.

Summary Query optimization is considered as one of the main challenges of query processing phases in the cloud environments. The query optimizer attempts to provide the most optimal execution plan by considering the possible query plans. Therefore, the execution cost of a query can be affected by some factors, including communication costs, unavailability of resources, and access to large distributed data sets. In addition, it is known as NP‐hard problem and many researchers are focused on this problem in recent years. Some techniques are proposed for solving this problem. Deterministic and non‐deterministic methods are two main categories to study these techniques. The deterministic and non‐deterministic query optimization methods can be further divided into three subcategories, cost‐based query plan enumeration, multiple query optimization, and adaptive query optimization methods. Moreover, this paper presents the advantages and disadvantages of the algorithms for solving the query optimization problems in the cloud environments. Moreover, these techniques are compared in terms of optimization, time, cost, efficiency, and scalability. Finally, some key areas are offered to improve the cloud query optimization mechanisms in the future.

Summary WhatsApp Messenger is a popular instant messenger among Iranian users. The WhatsApp status feature provides the possibility of posting desired content without restrictions in terms of type with the capability of being managed by users. Status can be considered as a potential place to express users' feelings, opinions, and thoughts. However, special attention should be paid to the privacy of users and the information published in this manner because access to the content of a user's status by unauthorized friends and interpretations of the user's status content may violate his/her privacy. This study investigates the privacy issues associated with information shared through status. The data of this study were gathered via access to the status content of 4000 Iranian users and via telephone interviews conducted with 350 of them. In this study, a combination of quantitative and qualitative methods has been used to analyze the data. This study focuses on the extraction of patterns in users' status content, determination of their polarity, and examination of the factors affecting users' privacy concerns. During the research, 10 general themes were extracted from users' content. The results showed that user privacy concerns influenced the type of theme selected. In addition, the theme selected under different circumstances may include a type of feeling that, in this study, is called polarity. Polarity is affected by the users' privacy concerns. Moreover, the demographic characteristics of users (age and gender) have a significant relationship with the type of theme used and their privacy concerns.

The application of residue number system (RNS) to digital signal processing lies in the ability to operate on signed numbers. However, the available RNS-to-binary (reverse) converters have been designed for unsigned numbers, which means that they do not produce signed outputs. Usually, some additional circuits are introduced at the output of the reverse converter to map the unsigned generated output into a signed number representation. This paper proposes a novel method to design reverse converters with signed output for a class of RNS moduli sets of composite form {2k, 2P-1}. The structure of the modulo adder used in the last stage of the proposed converters is modified in order to reuse the internal circuits to produce the signed output. This adder component is especially designed for achieving reverse converters with signed output, imposing very low area and delay overheads compared with unsigned converters. The proposed approach is applied to design reverse converters for different moduli sets and to implement application specific integrated circuits. Experimental results show that for a 4-moduli converter, the proposed design can outperform the traditional method to obtain signed outputs by improving the delay, chip-area, and energy consumption by up to 9%, 21%, and 35%, respectively.

This paper presents a new method for mutual authentication in centralized cognitive radio networks. In doing so, we analyzed the proposed scheme in terms of security and performance. As for securit...

Abstract Radio frequency identification grouping proof authentication protocol is an approach to identify a set of tagged objects simultaneously. Over the past decade, several protocols in this domain have been presented, but each was weak with flawed attributes. It is essential that a grouping proof protocol be both scalable and affordable, considering its use for applications with large quantities of tags and the high level of security. In this paper, we present a secure and scalable grouping proof protocol by utilizing an encryption method that is called authenticated encryption. This encryption method provides both confidentiality and message integrity simultaneously. In addition, it can satisfy the resource limitation of passive tags. The proposed protocol eliminates the dependency among the tags' responses and provides the scalability with minimum message broadcasting. We evaluate the proposed protocol based on formal and informal security methods, and the results prove that it is robust against radio frequency identification attacks and suitable for low‐power and low‐cost devices. Copyright © 2017 John Wiley & Sons, Ltd.

Abstract Wireless sensor networks have been established for a wide range of applications in adversarial environments, which makes secure communication between sensor nodes a challenging issue. To achieve high level of security, each pair of nodes must share a secret key in order to communicate with each other. Because of the random deployment of sensors, a set of keys must be pre‐distributed, so that each sensor node is assigned a set of keys from a key pool before the deployment. The keys stored in each node must be carefully selected to increase the probability of key share between two neighboring nodes. In this paper, we consider a hybrid key pre‐distribution scheme based on the balanced incomplete block design. We present a new approach for choosing key pool in the hybrid symmetric design that improves the connectivity and scalability of the network. We also introduce an extension to the proposed approach to detract memory usage and improve resilience. Experimental results verify the performance and applicability of our approach. Copyright © 2014 John Wiley & Sons, Ltd.

In this brief, the implementation of residue number system reverse converters based on well-known regular and modular parallel-prefix adders is analyzed. The VLSI implementation results show a significant delay reduction and area × time2improvements, all this at the cost of higher power consumption, which is the main reason preventing the use of parallel-prefix adders to achieve high-speed reverse converters in nowadays systems. Hence, to solve the high power consumption problem, novel specific hybrid parallel-prefix-based adder components that provide better tradeoff between delay and power consumption are herein presented to design reverse converters. A methodology is also described to design reverse converters based on different kinds of prefix adders. This methodology helps the designer to adjust the performance of the reverse converter based on the target application and existing constraints.