Search

Particularly, for real time monitoring-IOT has just evolved to support massive capacity Cellular LTE networks. The fundamental issue is the constrained bandwidth that NB-IOT channels allow. Therefore, goal of paper is to enhance the capacity of the NB-IOT physical layer shared channels for uplink and down links. The primary objective of this article is to improve the efficiency of an LTE-OFDM framework for NB-IOT-WAN via BER and BLER assessment. The proposed approach improves performance by selecting suitable cyclic prefix sampling with FFT size. It is planned to adopt M-QAM for increased data transmission capacity and reducing OFDM BER. In order to enhance the capacity approach of diversity reception is considered along with the modified modulation parameters. Increased FFT size is offered for OFDM capacity enhancement for narrowband physical downlink shared channel (NPDSCH) and narrowband physical uplink shared channel (NPUSCH) transceivers. The block error rate (BLER) is used as the performance evaluation parameters for the LTE-OFDM based NB-IOT system. The impact of the higher block transmission length is assessed for the improvement in the BLER rates. It is proposed to use M-QAM for NPUSCH which may offer better capacity of data transmission. The performance is compared with the standard QPSK modulation. For the uplink design under AWGN and frequency selective channels are considered for evaluation. The numbers of receiver antenna are increased for offering the better diversity reception to further enhance the channel capacity. The optimal design parameter selection might improve the performance of the NB-IOT cellular networks. The BLER is evaluated for different case of uplink and downlink designs against the wide range of the SNR. The entire document takes into account all factors in order to get the greatest system efficiency, and it offers capacity enhancement. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks are attaining popularity to its highest currently, as the users need wireless connectivity regardless of their geographical location. Threats of security attacks are growing on the Mobile Ad-hoc Networks (MANETs). MANETs must require a secure mode for communication and transmission which is rather challenging and vigorous issue. With the aim of providing secure transmission and communication, researcher worked explicitly on the security concerns in MANETs. Several secure protocols and security methods within the networks were projected but utmost of the security measures in their designs are not ruminated. Hence, a novel scheme is proposed in this paper for the secure and reliable data transmission in MANETs under black hole attack constructed on amended Ad hoc On-demand Multipath Distance Vector (AOMDV) protocol of our base scheme. This paper comprises AOMDV protocol for the multiple route discoveries along with K-Nearest Neighbor (KNN) for nearest neighbor node selection and use False key-build Advanced Encryption Standard (FAES) encryption scheme for cryptography method. FAES algorithm is used with the aim of securing the IoT devices and data from the hardware and network attacks. Also, the interaction of the scheme with the IoT based concepts making our work even smarter to the users. The proposed scheme performance is stable with higher throughput while that of base scheme. The quality of the proposed scheme is measured in terms of energy consumption, EE-delay and throughput. The results of simulation show that the Variance, EE-delay, energy consumption and throughput of proposed FAES-AOMDV protocol is lower than the original AOMDV protocol. FAES-AOMDV protocol ensures the secure transmission of data with least energy consumption in the presence of malicious nodes. [ABSTRACT FROM AUTHOR]

This paper provides a theoretical model for the computation of the probability density function of multi-hop broadcast latency when using probabilistic broadcasting schemes in Wireless Sensor Networks. In this paper, a novel probabilistic approach is presented for directed data transmission without route discovery. In our model, we require each message can reach the BS successfully with a certain success probability and nodes which are located nearer to the base station relay messages with a certain relay probability. The relationship between the number of intermediate nodes and relay probability is analyzed and the condition for relay probability to guarantee a certain success probability of messages is obtained. This approach is robust, adaptive to change of topology of the sensor network and energy efficient. Implementation of this approach is discussed. Simulation helps to illustrate the main results obtained by analysis and shows that this approach is very energy efficient. [ABSTRACT FROM AUTHOR]

The Underwater Acoustic (UWA) wireless communication system is considered one of the most challenging systems for data transmission. The Orthogonal Frequency Division Multiplexing (OFDM) system promises numerous benefits, including high spectrum efficiency and inter-Symbol interference mitigation. But, it is very sensitive to Carrier Frequency Offset (CFO). The implementation of the OFDM necessitates the use of orthogonal transforms such as the Inverse Discrete Fourier Transform (IDFT)/DFT. On the other hand, the Multiple-Input-Multiple Output (MIMO) configuration is affected by co-channel interference. In this paper, we look at another type of co-interference known as the co-CFO. The Linear Zero Forcing (LZF) equalizer suffers from noise enhancement and high computational complexity due to the direct matrix inversion. The Linear Minimum Mean Square Error Equalizer suffers from the noise enhancement problem at high values of the Signal-to-Noise Ratio (SNR), and requires the estimation of the operating SNR to work properly, besides the high computational complexity of the implementation. In this paper, we propose a Joint Low Complexity Regularized LZF equalizer for the UWA-OFDM communication system. The proposed equalizer is driven and takes the effect of the UWA co-channel effect, the noise, and the co-CFO. Simulation results show the important role of the proposed equalizer in configuring the UWA-OFDM communication system. [ABSTRACT FROM AUTHOR]

Modern text encryption is mostly based on symmetric encryption. Its efficient and safe encryption method greatly improves the application of intelligent transportation system (ITS), and effectively solves the security problems in data communication and sharing. In symmetric encryption, the stream cipher uses the key stream generated by the key to encrypt the message. Due to the simple implementation and fast encryption and decryption speed, the efficiency of this method is generally higher than other symmetric encryption methods. And because of its one-time pad feature, stream ciphers can effectively resist chosen plaintext attacks. In this paper, a new stream cipher encryption algorithm is proposed, which alternately encrypts plaintext using ratio of the circumference of a circle to its diameter (PI), which can effectively prevent fast correlation attacks. More importantly, as an irrational number, PI not only has good random number characteristics, but also can be quickly generated mathematically, and has stronger security and lighter efficiency performance than existing algorithms. In addition, in terms of speed, each round of iteration produces twice the number of bits than the previous round, which makes the iterative complexity of the proposed scheme lower than the linear growth complexity. On this basis, by using linear feedback shift registers (LFSR), our method conforms to the characteristics of light weight, fast transmission and robust security, which is very suitable for ITS applications. [ABSTRACT FROM AUTHOR]

During the last few decades, digital communication has played a vital role in various sectors such as healthcare departments, banking, information technology companies, industries, and other fields. Nowadays, all data are transmitted over the Internet, which needs high protection for transmitting the original data from source to destination. In order to secure digital communication, cryptography and steganography methods are used to achieve data security over insecure and open networks like the Internet. Cryptography is the method of encrypting secret information in an unreadable structure. Based on the cryptography method, the original message can be distorted before data transmission. On the other hand, steganography covers secret data such as audio, image, text, and video. It can hide the message while transmitting the original information from one end to another. The data combines images, texts, audio and videos, which are communicated worldwide through the Internet. This review paper gives an analysis based on the concept of cryptography and steganography. It also presents a comparative approach using several encryption algorithms with several factors such as block size, key size, encryption speed, memory usage, and security level. [ABSTRACT FROM AUTHOR]

This paper addresses congestion avoidance using enhanced blue algorithm (EBA) for data transferring in a network. The congestion of data always affects the data transmission on the internet for various applications. For developing data transmission performance, the congestion of data is a challenging task. Although, different approaches have been used to avoid data congestion, yet we have considered a data transmission framework for better performance compare to existing approaches. Thus, we considered the advanced Blue Algorithm which is used to determine the node's capacity with middle path and it prevents congestion by monitoring of data during data transmission. The role of gateway is considered to supervise status of congestion for both data sending and receiving based on positive or negative acknowledgment as well as data size. The gateway is also used for a congestion notification system to alleviate congestion and enhance throughput. During experimental analysis, we have taken comparative performance between existing and our proposed model. For example, in Enhanced Ad hoc On-demand Distance Vector (EAODV), during the packet size of 10, the average end-to-end delay is 32.63 ms whereas in proposed advanced Blue algorithm, the average delay is only 19.11 ms. Thus, the proposed model using Blue algorithm is performed better than existing method. [ABSTRACT FROM AUTHOR]

In order to solve the problem of hot spot caused by uneven energy consumption of nodes and reduce the network energy consumption, a novel Cluster Routing algorithm for ring based wireless sensor networks using Particle Swarm Optimization (PSO) and Lion Swarm Optimization (LSO) is proposed in this paper, which is called CRPL. In CRPL, the optimal cluster heads (CHs) of each ring are determined by using LSO whose fitness function considers not only energy, number of neighbor nodes, number of cluster heads but also distance. Moreover, PSO with a multi-objective fitness function considering distance, energy and cluster size is used to find the next hop relay node in the process of data transmission for each CH, so the optimal routing paths are obtained, which can alleviate the hot spot problem as well as decrease the energy consumption in the routing process. The simulation results show that, compared with the existing correlative cluster routing algorithms, CRPL has better effects in balancing the energy consumption and prolonging the lifespan of the network. [ABSTRACT FROM AUTHOR]

The date palm is a high-value fruit crops but unfortunately, the date production are in danger because of the Red Palm Weevil or Rhynchophorus Ferrugineus. The Rhynchophorus Ferrugineus can excavate holes in the trunks of palm tree up to 3.3ft long, thereby weakening and eventually killing the host plant. The aim of the present paper is use of wireless sensor network for automatic detection and tracking Rhynchophorus Ferrugineus. Since the energy of sensor nodes is limited, considering their energy level for enhancing network lifetime is of high significance. Data transmission can consume a great deal of energy. Hence, it is essential that a new method be designed for data transmission so as to enhance network lifetime. The method proposed in this paper is aimed at improving energy consumption of target-detecting applications in WSNs via data mining and Q-learning. The experiments and simulations are carried out on Opnet simulator. The simulation results indicate that using data mining and Q-learning can reduce energy consumption, data transmission delay and maintain load balance notably better than IEEE 802.15.4. [ABSTRACT FROM AUTHOR]

Due to overlapping coverage areas of nodes, traditional data encryption methods for sensor networks fail to consider the logical correlation between common nodes and transmission paths, resulting in low data capture efficiency, low data communication after encryption, and poor data sensitivity extraction effect. Therefore, this paper proposes an automatic encryption method for sensor network capture data based on symmetric algorithm. Based on the analysis of WSN architecture and sensor node structure, symmetric algorithm encryption flow is designed; The network attack model is established, and the multi-path transmission security is analyzed according to the symmetric algorithm, the probability of successful eavesdropping is calculated, and the sensor network capture data is encrypted accordingly. In order to verify the performance of network capture data encryption, a comparative experiment is designed. The results show that the data recall rate is as high as 99.0%, the data communication volume can reach 6.97 × 104byte, and the extraction accuracy of sensitive information can reach 97.9%. This method can effectively solve the problems existing in traditional methods and lay a foundation for the development of sensor network data encryption. [ABSTRACT FROM AUTHOR]

Link quality is important and can greatly affect the performance of wireless transmission algorithms and protocols. Currently, researchers have proposed a variety of approaches to implement link quality estimation. However, the estimated result of link quality is not accurate enough and the error is large, so they may lead to the failure of routing algorithm and protocol. In this paper, a novel method is proposed to achieve the more accurate estimation of link quality than before. This method employs Bernoulli sampling-based algorithm to complete the estimation of link quality. The problem is modeled as calculation of estimators based on Bernoulli sampling data. The authors further prove that the calculation results are accurate by probability theory. Furthermore, according to link quality estimation, the authors also provide a centralized routing algorithm and a distributed improvement algorithm in order to switch the data transmission on the better quality link. Finally, the extensive experiment results indicate that the proposed methods obtain high performance in terms of energy consumption and accuracy. [ABSTRACT FROM AUTHOR]

Seamless handoff is crucial for wireless body area network (WBAN) data's transmission, it may avoid the death resulted from sudden diseases, especially for the elder people who suffer from chronic diseases. Therefore, a vertical handoff algorithm that conforms to the characteristics of body area network is urgent. Different from the traditional service types in telecommunications, service types in wireless body area network have their own characteristics. How to reasonably divide these service types according to their requirement of the internet is very important. In addition, we need to study the rationality of different weighting and network selection algorithms for body area network users. In view of the lack of vertical handoff algorithms to meet the characteristics of wireless body area networks, this paper first analyzes the service types in body area network, and reasonably divides the service types in body area network into four types. For these four services types, we comprehensively and systematically analyze the weight determination and network selection algorithms suitable for them. In addition, in wireless body area network environment, there may be situations when multiple users need to transmit information at the same time. For these situations, we propose a broadcast mechanism to prevent network congestion caused by group switching. The simulation results show that the combination of using Analytic hierarchy process to determine the weight and using Technique for Order Preference by Similarity to Ideal Solution as the network selection method is most suitable for vertical handoff in WBAN. The proposed broadcast mechanism can solve the network congestion problem caused by group handoff. [ABSTRACT FROM AUTHOR]

Underwater wireless sensor network (UWSN) is one of the effective methods to acquire ocean observation data, and research on underwater routing technology has become a hot spot. However, the lifetime of UWSN is an important factor affecting the overall performance of routing protocols. Due to the uncertain underwater environment and poor link quality, it will affect data integrity and network survival ability. Cooperative communication is an excellent technique for solving such problems. In this communication, the source node forwards data through a cooperative path to improve network throughput, while the destination node receives data packets that do not contain obvious errors. Therefore, this paper provides a cooperative communication method to solve the packet loss problem and lifetime of UWSN. The underwater-layered routing network structure is adopted to divide the network nodes into clusters for energy balance. Compared with the traditional layered protocol, the cooperative communication can better guarantee the link quality of the underwater channel. The k-means algorithm is also used to cluster nodes, and conditional probability can select cluster heads. During data transmission, relay nodes will amplify the signal and backup the data packets to avoid dropping packets. The proposed protocol is simulated and compared with non-cooperative protocols (LDBR and MLCEE), the results show that the proposed protocol outperformed the other protocols in terms of network lifetime, throughput, energy consumption and end-to-end delay. [ABSTRACT FROM AUTHOR]

Resource allocation is most needed in the next generation of Cognitive radio networks these techniques are used to increase the Cognitive radio network's performance. But, it is difficult to accomplish these techniques in real-time performance wireless. In this paper, a resource allocation technique based on artificial neural networks (ANN) is proposed which helps to reduce the power consumption in the network. The goal of the proposed scheme is to secure data transmission and to increase the uplink and downlink speed with less bit error rate. From the Simulation results, it can be observed that the proposed technique based on ANN is efficient in terms of the computation time related to the other resource allocation techniques. To increase the security of the data transmission in networks Location-based key management system is used. This paper is implemented by NS2. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new clustering, encryption and trust modeling based energy aware routing secured algorithm for performing secured data communication in Wireless Sensor Networks For this purpose, an Elliptic Curve Cryptography based encryption scheme is proposed in this work where the key generation scheme of Elliptic curve cryptography and the strength of the keys used in it for encryption are enhanced by pre-concatenation and post-concatenation of values obtained from the Euler's phi function value and Gamma function values based on the user identifier values for 'n' different users. This proposed technique performs secured routing by encrypting the messages before they are routed to the destination through the network. In this scheme, only one pairing computation with a loop is necessary to encrypt a single message which is to be communicated to 'n' different receivers by forming 'n' different cipher texts using the proposed elliptic curve group theory based encryption algorithm. The proposed secured routing algorithm has been modeled in this work by performing the encryption of the plain text message before it is sent in the network. Moreover, this proposed system uses a trust model to check for any attempt by intermediate nodes for decrypting the encrypted messages during routing in order to enhance the security of communication. The proposed encryption scheme reduces the computation cost by computing the keys for all the receivers in one attempt. Performance analysis of this proposed scheme shows that computation time is for key formation, encryption and decryption are less in the proposed scheme when it is compared with the existing ECC based schemes for encryption and decryption. In addition, the secured routing algorithm proposed in this paper that uses the proposed encryption technique and trust modeling for enhancing the security of communication increases the packet delivery ratio, security and the overall network performance and it also decreases the delay and energy consumption by avoiding the security attacks efficiently. [ABSTRACT FROM AUTHOR]

The aim of this paper is to create an autonomous reconfigurable radio communication system that can produce an adequate transmission rate according to propagation medium fluctuation while maintaining a higher quality of service (QoS). In this work, we have achieved an experimental implementation of adaptive modulation technique using SDR platforms as USRP B210, RTL-SDR and HackRF One. The implemented system provides a real time data communication equipped by an adaptive modulation techniques. The system autonomously chooses the most suitable modulation among BPSK, QPSK and 8-PSK based on the estimation of link quality measured by the signal to noise ratio (SNR). [ABSTRACT FROM AUTHOR]

During the past decades, Wireless Sensor Networks (WSNs) have become extensively used due to their prominent number of applications. The use of WSNs is a domineering need for future radical areas commencing from smart home to military surveillance in which hundreds or thousands of sensor nodes are positioned. The usage of mobile sink in those large scale WSNs, for data aggregation amends the functioning of the network by bringing down the energy conservation, amending the network lifetime and data transmission time lag between the nodes. In this paper Center of Energy -Reinforcement Learning based On-Demand Transition State Update algorithm (CERL-ODTST) is proposed to dynamically update mobile sink traversal path. Initially cluster formation and cluster head election for large scale WSNs are done by novel center of energy method. Clustering and data aggregation techniques are applied to reduce the amount of data transmission hence decreasing the energy consumption in the network. In this context cluster heads aggregates data from cluster members which are collected by mobile sinks. The amount of data transmission can be significantly reduced by using Machine Learning algorithms like neural networks and swarm intelligence and also using the distributive features of the network. It offers a reasonable study of the functioning of diverse methods to support the engineers for projecting suitable machine learning based results for grouping the nodes and data aggregation applications. Compared to traditional methods, in the proposed CERL-ODTST, reinforcement learning is used for intra cluster data aggregation to improve aggregation efficiency in the whole network. The implementation results show that proposed CERL-ODTST performs well in terms of overall tour length, energy efficiency and reduces the transmission delay hence increases network lifetime. [ABSTRACT FROM AUTHOR]

There are some pain points in the current translation services industry. For example, mechanisms of market operations need to be further improved; conflicts among stakeholders frequently occur; translation quality is hard to be evaluated because of asymmetric information; and data resources in this industry are not fully utilized. In this paper, it is proposed that blockchain technology can be applied into the translation services industry concerning data transmission, privacy protection, and a service evaluation system. Then, according to actual requirements, the application of consortium blockchain in the translation services industry is also put forward. In addition, in the case of the coexistence of numerous nodes, a deployment model with the assistance of edge computing can address issues regarding data verification and high-speed transmission. This model is conducive to building an optimum credit system of "clients—translation companies— translators—regulatory agencies" as a whole, meeting requirements for real-time business processing, and improving service quality and business capabilities. By the development of specific applications, the effectiveness of the application of blockchain and the efficiency and stability of system performance are validated. [ABSTRACT FROM AUTHOR]

Wireless Sensor Network (WSN) consists of several Sensor Nodes (SN) for monitoring various applications and sensing the environmental data. The WSN gathers and compiles the detected data before sending it to the Base Station (BS). The nodes have limited battery power, so efficient data transmission techniques and data collection methods are required to enhance the sensor network lifetime. In this paper, the Particle Swarm Optimization (PSO) method is utilized to form the cluster, and a Fuzzy based Energy Efficient Routing Protocol (E-FEERP) is proposed using average distance of SN from BS, node density, energy and communication quality to transmit data from cluster head to the BS in an optimal manner. The proposed protocol used parallel fitness function computing to quickly converge to the best possible solution with fewer iterations. The protocol used PSO-based clustering algorithm that recognize how birds act when they are in a flock. It is an optimization strategy that uses parallel fitness function computing to get to an optimal solution quickly and with a small number of iterations. Fuzzy is combined with PSO to increase coverage with reduced computational overhead. The proposed E-FEERP improves network performance in terms of packet delivery ratio, Residual Energy (RE), throughput, energy consumption, load balancing ratio, and network lifetime. [ABSTRACT FROM AUTHOR]

Because of the heavy data and communication advances, the utilization of Internet of Things (IoT) gadgets has expanded dramatically. In the improvement of IoT, Wireless Sensor Network (WSN) plays out a crucial part and involves easy keen gadgets for data gathering. In any case, such savvy gadgets have requirements regarding calculation, preparing, memory, and energy assets. Alongside such requirements, the major difficulties for WSN are to accomplish dependability with the security of communicated information in a weak climate alongside pernicious nodes. This paper intends to build up an Anomalous Intrusion Detection Protocol and Intrusion Prevention Protocol for interruption evasion in IoT dependent on WSN to expand the network time frame and information reliability. The proposed framework makes dissimilar energy-efficient groups dependent on the natural characteristics of nodes. Also, in view of the (k, n) limit related Shamir mystery sharing plan, the unwavering quality also, the security of the tangible data within the Base Station and group head are accomplished. The proposed security conspires demonstrates a trivial answer to adapt to interruptions produced by malignant nodes. The trial results utilizing the network test system Network Simulator-2 show that the proposed directing convention accomplished improvement as far as network lifetime, end-to-end delay as 24%, packet delay ratio as 30%, when contrasted and the current work under unique network characteristics. [ABSTRACT FROM AUTHOR]

Many errors in data communication cause security attacks in Internet of Things (IoT). Routing errors at network layer are prominent errors in IoT which degrade the quality of data communication. Many attacks like sinkhole attack, blackhole attack, selective forwarding attack and wormhole attack enter the network through the network layer of the IoT. This paper has an emphasis on the detection of a wormhole attack because it is one of the most uncompromising attacks at the network layer of IoT protocol stack. The wormhole attack is the most disruptive attack out of all the other attacks mentioned above. The wormhole attack inserts information on incorrect routes in the network; it also alters the network information by causing a failure of location-dependent protocols thus defeating the purpose of routing algorithms. This paper covers the design and implementation of an innovative intrusion detection system for the IoT that detects a wormhole attack and the attacker nodes. The presence of a wormhole attack is identified using location information of any node and its neighbor with the help of Received Signal Strength Indicator (RSSI) values and the hop-count. The proposed system is energy efficient hence it is beneficial for a resource-constrained environment of IoT. It also provides precise true-positive (TPR) and false-positive detection rate (FPR). [ABSTRACT FROM AUTHOR]

In wireless sensor networks, ensuring data confidentiality and integrity is paramount, particularly in sensitive environments. However, existing encryption methods encounter challenges, including key maintenance in symmetric encryption and lower security levels in asymmetric encryption. To address these issues, this paper proposes a novel security protocol employing a hybrid encryption approach, combining both symmetric (AES) and asymmetric (RSA) cryptographic techniques. The protocol introduces a two-phase cryptographic technique utilizing AES for robust encryption in Phase 1 and RSA for efficient key management in Phase 2. Experimental results demonstrate enhanced efficiency in encryption, decryption, and total execution time compared to existing algorithms, marking a significant advancement in cryptographic protocols for improved security in data transmission and management. Key contributions include the division of plaintext for simplified cryptographic processing, AES encryption for Phase 1, RSA encryption for Phase 2, and a seamless decryption process ensuring data integrity and security against attacks. [ABSTRACT FROM AUTHOR]

A wireless sensor network is comprised of a large number of sensors that are frequently used for data collection and tracking applications. When nodes are deployed in inaccessible places, energy efficiency becomes critical, which routing protocols can address. Because data transmission occurs across wireless networks, security continues to be a challenge in WSN. Recently, DNA computing has been found to be beneficial in enhancing the security of data or networks. Additionally, trust management is critical for developing an ideal and secure relay node for effective data transfer. This paper introduces a novel Quantum Chimp Optimization with DNA Sequence-based Multihop Secure Routing (QCODNAS-MSR) protocol for WSNs in this regard. The QCODNAS-MSR protocol combines QCO design with a DNA sequence technique for route selection, efficiently balancing real-time and non-real-time traffic on diverse routes with enhanced energy and throughput characteristics. Additionally, the QCODNAS-MSR protocol has deduced an objective function from a variety of input characteristics, including QoS, trust, and connection. The inclusion of a trust factor in the route selection process enables the most secure routes to be selected ideally. The QCODNAS-MSR model is capable of balancing the needed performance factors, resulting in near optimal routes for routing real-time traffic data. To show the QCODNAS-MSR algorithm's better performance, a number of simulations were run under a variety of attack types. The comparative study found that the QCODNAS-MSR model outperformed the other approaches on a variety of measures. [ABSTRACT FROM AUTHOR]

Nowadays, the adoption of the Internet of Things (IoT) framework in various healthcare industries has increased rapidly in recent years. The IoT devices generate vast amounts of sensitive data, such as personal health information. It is mandatory to protect medical records from unauthorized access and use. However, the finite resources nature of these devices can make it hard to implement robust security measures, such as encryption and authentication. A blockchain is a propitious approach for the secure management of medical records in an immutable way. This problem can be resolved with ciphertext-policy attribute-based encryption (CP-ABE), which permits granular access control in IoT. The local gateways that are directly interfaced with the Ethereum blockchain-based smart contract platform are utilized to create and implement a distributed and dependable user authentication and an access control mechanism for IoMT. In this paper, a DBC-based CP-ABE approach offers a secure and decentralized solution for secure communication and data protection and provides a more secure and trustworthy system. The system works on the concept of an Elliptical Curve Cryptography-based CP-ABE method to reduce complexity and provide data security in remote patient monitoring. On the other hand, blockchain-based smart contracts offer a dynamic, optimal, and self-adjusted access control in smart healthcare systems. It lowers the overhead of conducting resource-intensive authentication procedures and blockchain communications at IoT devices. The result provides the efficiency of the proposed work in computation as well as processing time and its resistance to various security intrusions over existing schemes. [ABSTRACT FROM AUTHOR]

Data communication is part of life now and its security is of utmost importance. Cryptographers provide new methods for security and intruders always want to break them. In modern scenario, the need of the hour is to develop easy to use security methods which can provide high level of security as well. In this paper, a new method of data communication is proposed using the properties of wavelet transform. The embedded data does not create any visible change in the carrier image. A rigorous security analysis is also provided in order to prove that the method is resistive against various security attacks and very efficient for implementation point of view. [ABSTRACT FROM AUTHOR]

This paper proposes channel prediction algorithms, based on the vector Prony method, tackling the channel state information (CSI) acquisition problem in fast time-varying uplink and downlink channels of the time division duplex (TDD) in massive multiple-input, multiple-output (MIMO) systems. For the uplink system, we show that the CSI obeys the Prony equation in theory, and we aim to overcome the instability of solving the Prony equation via iterating the Prony coefficients based on CSI re-estimated from signals received during data transmission. For the downlink system, a method to generate precoders is constructed based on the prediction of downlink CSI. Experiments are performed according to the fast fading full-dimensional multiple-input multiple-output (FD-MIMO) channel model of 3GPP Standards. The results demonstrate that performance is improved remarkably in uplink transmissions and approaches the theoretical optimal scheme in downlink transmissions. [ABSTRACT FROM AUTHOR]

The device was invented to sense the variations in the deployed Environment, which takes different dimensions in its functionality. The basic operation does not change; it is the same surveillance, gathering and alert. Human intervention in all places is not possible and efficient monitoring in all circumstances cannot be done manually. Wireless Sensor Networks give the solution for the above-specified problem, continuous efficient monitoring and alerting on time without human intervention in any circumstances. Deploying WSNs and extracting efficient performance requires a strong technology backup. However, it's a machine in logical connectivity that may face several technical issues while transferring the gathered data. It has to be rectified, and efficient service to be provided in the deployed application. Finding the safest and fastest path is one of the critical tasks in the WSN. To achieve that, Bio-Inspired Computing will be used as a tool for designing the protocol to attain the fastest reliable network, even if it deals with the other problems in WSN, such as efficient energy utilization from the battery. In such a way, the Paper is proposed based on the exceptional and exciting behavior of one of the living things, which shook the entire world for almost two years in all aspects, and even a few countries are still seeking a way to come back from its impact, the reason for global lockdown, born with the crown, founder of social distancing, which is popularly known as "Corona" the virus. [ABSTRACT FROM AUTHOR]

In this paper, balanced grouping scheme (BGS) for efficient clustering is proposed for routing problem in wireless sensor network with multilevel heterogeneity. The scheme builds over the existing protocols and tries to improve upon the drawbacks of the protocols. The major problem is with average energy of previous round in Efficient and dynamic clustering scheme protocol which require a lot of time to the selection of cluster heads. It causes delay and interrupted data transmission which is resloved by BGS. BGS divides the nodes into groups by using the double mean method by which lesser energy nodes can be saved for later rounds. Based on the groups, complete exclusion of a certain number of low energy nodes from being selected as cluster heads has been carried out. The simulation with BGS protocol shows its suitability over other clustering protocols in which 44 % improvement in stability period and 8 % improvement in packet delivery has been achieved. It results in improvement of stability period, network lifetime, and packet delivery. [ABSTRACT FROM AUTHOR]

In Wireless Sensor Network (WSN), the consumption of energy is high due to the data transmission in the sensing region. The Optimized Distributed Voronoi-based Collaboration (ODVOC) optimizes data delivery and it suffers from huge energy consumption. To overcome this drawback, a data aggregation scheme is introduced to expand the lifetime of the network and to minimize the energy utilization. Data aggregation is a significant approach that preserves the unwanted usage of energy during data transmission. In this paper, the Optimized Distributed Voronoi-based Cooperation scheme with Energy-aware Dual-path Geographic Routing (DAOHS-ODVOC-EDGR) is proposed which incorporates the polydisperse aggregation scheme and it aggregates the indispensable data in the intermediary nodes. The effective data aggregation is achieved by the estimation of the waiting time of the data at every intermediary node and cost function that is used for electing the next-hop node. In the proposed protocol, the buffer value of every node is divided to retain diversified kinds of flow for effective and fair delivery of data. The rate of transmission at the source and intermediary node is altered during the congestion. The proposed DAOHS- ODVOC-EDGR protocol is tested via simulation scheme. The result of the simulation exposes that DAOHS-ODVOC-EDGR outperforms the TESDA and DVOC protocol in terms of network lifetime, energy efficiency, and hop count delay. [ABSTRACT FROM AUTHOR]

The growth and adoption of Internet of Things (IoT) have been increasing at a rapid pace over the past few years. IoT is a network of huge number of connected devices which are mobile and constrained in nature. These IoT devices communicate and transmit data over the Internet. This huge amount of transmission causes congestion in the network, resulting in packet delivery delay and high packet loss. Handling the problem of congestion requires transmission of data effectively in a congestion-aware manner. This paper proposes an approach for congestion-aware data transmission in mobile and constrained IoT networks. In this study, we have performed hop-to-hop communication and the process of next hop selection considers the multiple parameters to make it congestion-aware and effective. The proposed method uses the Analytic Hierarchy Process (AHP) to perform multiparameter based decision making to pick the best suitable next hop. The proposed method is ideal for the environment where nodes have limited resources, high traffic and need timely delivery of data packets. The results are compared with state-of-the-art methods, and the performance of the proposed method was better in terms of throughput by 6%, packet delivery rate by 7.5%, and reduced average delay by 4% as well as buffer overflow condition by 2%. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has created an emergency across the globe. The number of corona positive and death cases is still rising worldwide. All countries' governments are taking various steps to control the infection of COVID-19. One step to control the coronavirus's spreading is to quarantine. But the number of active cases at the quarantine center is increasing daily. Also, the doctors, nurses, and paramedical staff providing service to the people at the quarantine center are getting infected. This demands the automatic and regular monitoring of people at the quarantine center. This paper proposed a novel and automated method for monitoring people at the quarantine center in two phases. These are the health data transmission phase and health data analysis phase. The health data transmission phase proposed a geographic-based routing that involves components like Network-in-box, Roadside-unit, and vehicles. An effective route is determined using route value to transmit data from the quarantine center to the observation center. The route value depends on the factors such as density, shortest path, delay, vehicular data carrying delay, and attenuation. The performance metrics considered for this phase are E2E delay, number of network gaps, and packet delivery ratio, and the proposed work performs better than the existing routing like geographic source routing, anchor-based street traffic aware routing, Peripheral node based GEographic DIstance Routing. The analysis of health data is done at the observation center. In the health data analysis phase, the health data is classified into multi-class using a support vector machine. There are four categories of health data: normal, low-risk, medium-risk, and high-risk. The parameters used to measure the performance of this phase are precision, recall, accuracy, and F-1 score. The overall testing accuracy is found to be 96.8%, demonstrating strong potential for our technique to be adopted in practice. [ABSTRACT FROM AUTHOR]

Orthogonal frequency division multiple access (OFDMA) is a multi-carrier, multiple access (MA) technique, which is widely adopted in contemporary wireless standards. Single carrier-frequency division multiple access (SC-FDMA) is a modified version of OFDMA which employs single carrier transmission by pre-coding the data symbols using discrete Fourier transform (DFT). However, these systems are highly vulnerable to the adverse effects arising in the channel, carrier frequency offset (CFO) and in-phase/quadrature phase (I/Q) imbalances. In the uplink communication scenario, the signal received at base station is the superposition of signals from all the active users. Even though the adverse effects caused by the communication channel and CFOs are addressed in the related literature extensively, the effect of I/Q-imbalances at the transmitter and the receiver is rarely considered. The effect of I/Q-imbalances will make the equalization process at the base station more complex. It is because the overall effective channel with radio impairments must be included in the system modelling. Hence the receiver processing should contain the equalization for effect of the channel, CFOs and I/Q imbalances. In this paper, we propose a novel technique based on the oblique projection (OP) technique for equalizing the channel, radio imbalances and synchronization errors caused by both transmitter (TX) and receiver (RX) for OFDMA/SC-FDMA uplink systems. We also propose an equalization technique with reduced computational complexity to overcome the adverse effects caused by I/Q imbalances and CFOs. The results of the simulation studies illustrate that the proposed techniques can compensate all the above-mentioned effects and they offer very good performance under both TX and RX I/Q imbalances. [ABSTRACT FROM AUTHOR]

Mobile Ad hoc Networks (MANETs) provides transmission of data between the nodes in an infrastructure less atmosphere. Nodes are highly mobile and dynamic which distresses the QoS in MANET. It is important to use suitable position allocator to allocate the nodes in MANET. The network's performance is influenced by the environment type as well as a proper routing protocol, mobility model, and position allocators. For highly dynamic environment, it is advisable to use appropriate mobility model along with the position allocator. This paper gives a brief overview about the existing position allocators used for simulation in NS-3. We have designed and implemented Rectangular-3D Position Allocator for NS-3 using the concept of existing Grid Position Allocator. We have done simulation analysis with the proposed allocator with the Random Box position allocator in static network and dynamic (stable and unstable) network on routing protocols AODV and DSDV by considering throughput, delay, and PDR as the QoS metrics. It has been determined that the Rectangular-3D position allocator performs better in static network for different values of parameters like number of nodes, packet size, simulation time and simulation area with QoS parameters like PDR, delay, and throughput for both AODV and DSDV routing protocols. It is also examined that the stable network gives better performance in comparison to unstable network for different parameters for both the routing protocols. When comparing the three QoS metrics, it is found that AODV performs much better than DSDV. [ABSTRACT FROM AUTHOR]

This paper presents the design and implementation of a microcontroller system for the measurement of various environmental parameters such as temperature, humidity, luminosity, air quality, pressure, etc. We target application scenarios that need the deployment of such systems in the open without the availability of an electrical power grid. For this purpose, we put a strong emphasis on the energy efficiency and the development of an autonomous environment-friendly power supply consisting of solar panels and an ultracapacitor. The sensor data transmission is done over the license-free radio frequencies around 433 MHz or 868 MHz. On the software side, a lot of attention is paid to the reliability and the security of the data transmissions by the development of a custom data transmission protocol. Overall, we aim at keeping the production and deployment costs of our system economically feasible for small and medium-sized businesses. The experimental results prove that our approach has much potential and that our systems can be successfully used to build autonomous sensor data gathering networks. [ABSTRACT FROM AUTHOR]

Today's access networks are in high demand to fulfill the high bandwidth requirement because of extensive improvement in high transmission rate applications for cloud computing, big data analytics, and other next-generation 5G smart applications. This exponential growth of high capacity and broadband access technologies comprise an essential trend in the development of a passive optical network (PON) access network. In this paper, 80/80 Gbps time wavelength division multiplexing PON (TWDM-PON) incorporating polarization division multiplexing (PDM) based Mach–Zehnder modulator (MZM) and electroabsorption modulator (EAM) techniques have been proposed. The performance of the system consisting of different polarized multiplexed modulation techniques is investigated in both downstream and upstream data transmission for variable transmission distance and received optical power in terms of bit error rate (BER), eye diagrams, power budget (PB) and receiver sensitivity. The results show that the 4 × 20/20 Gbps PDM-EAM modulated signals over 100 km fiber distance at − 60 dBm RS and 70 dB PB are successfully transmitted under fiber non-linearities. The proposed TWDM-PON system provides a next-generation long-reach access network from urban to rural areas. [ABSTRACT FROM AUTHOR]

The orthogonal frequency division multiplexing (OFDM) technology is employed in the fourth-generation mobile communication. It has two disadvantages. The first is high peak-to-average power ratio, and the second is high out-of-band radiated power. With the advent of the fifth generation of mobile communications, it needs large data transmission rate, short time delay and flexible waveforms. In the future communication applications, the diversified scenarios such as Internet of Things, inter-machine communication and telemedicine make the fourth-generation mobile communication no longer applicable. The generalized frequency division multiplexing has a pulse-shaping filter, which has less out-of-band radiated power and peak-to-average power ratio and fewer cyclic prefixes than OFDM. In order to meet high- data-transmission rate, it is an inevitable trend to install massive multi-input multi-output (massive MIMO) antennas. As the number of antennas increases, so does its complexity. This paper employs time reversal technology to reduce the computational complexity. Although the number of base station antennas has increased to eliminate interference, there is still residual interference. In order to eliminate the interference one step further, we deploy a zero forcing equalization (ZF equalization) after the time reversal combination. [ABSTRACT FROM AUTHOR]

A network of wireless sensor (WSNs) is formed by connecting thousands of miniature nodes. They are capable of sensing, communicating wirelessly and computing parameters. The life of a wireless sensor node depends upon its energy. Thus a main technical challenge in WSN is energy saving in the network. The principal needs of any wireless sensors network is its energy efficiency and security which could be influenced by presence of various malicious nodes. The major limiting constraint for sensor nodes is its limited energy required to transmit every data packet. LEACH PEGASIS, DEC and SEP are the several WSN probabilistic routing protocols to save energy throughout data transmission. The prime goals of the protocol implementation are the energy saving and heterogeneity maintenance. The contribution of paper is to describe the fundamentals of all mentioned protocols and basic structure of WSN and a homogeneous efficient DEC based novel election probability based multitier random probability protocol or agricultural wireless sensors network is proposed. It is found that modifications are capable of selecting the cluster heads homogeneously. Due to its better distribution capacity the protocol is energy efficient. The comparative analysis of performance matrices of above protocol is accomplished. [ABSTRACT FROM AUTHOR]

Security techniques based on conventional cryptography assume keys are disseminated prior to secure communications in traditional security mechanisms. The essential function of transmitting and sharing a secret key between two entities is the safe key management technique, which is the most important components to be concerned about when incorporating cryptographic activities into any system. If the key management procedures are ineffective, the system will be vulnerable to vulnerabilities and potentially lethal outsider attacks. Quantum cryptography is a method of securely encrypting information sent between parties while also detecting intruders attempting to listen in on the discussion. Quantum cryptography holds promise as a solution to these and other issues. In this paper,we discuss the Quantum key distribution (BB84 protocol) and how when integrated with conventional cryptography algorithms it increases security in data transmission to a remarkably high level. We also compare the cryptography algorithms for different file sizes and measure their performance by calculating the Encryption,decryption,throughput and Avalanche effect of the algorithms with and without QKD. The elapsed time of the conventional algorithm with QKD achieve 56.8%, 58.6% and 54.3% less time than AES, 3DES and Blowfish respectively. [ABSTRACT FROM AUTHOR]

Today's internet world is moving to cloud computing to maintain their public data privately in a secure way. In cloud scenarios, many security principles are implemented to maintain the secure transmission of data over the internet. And still, the main concern is about maintaining the integrity of our own data in the public cloud. Mostly, research works concentrate on cryptographic techniques for secure sharing of data but there is no such mentioned works available for data integrity. In this paper, a data masking technique called obfuscation is implemented which is used to protect the data from unwanted modification by data breaching attacks. In this work, enhanced Vigenere encryption is used to perform obfuscation that maintains the privacy of the user's data. Enhanced Vigenere encryption algorithm combined with intelligent rules to maintain the dissimilarity between the data masking to perform encryption with different sets of rules. This work mainly concentrates on data privacy with reduced time complexity for encryption and decryption. [ABSTRACT FROM AUTHOR]

The distinctive characteristic of the UWSNs environment presents novel challenges for network communication. Due to the harsh environment, extreme energy loss is carried out and nodes of networks expire early which reduces the life of the network. Cluster-based strategies can support UW communication because instead of all nodes only the cluster head (CH) collect and transmit data to the sink, rather than every node sending data by itself. Round base clustering strategies work in three phases: cluster setup, steady-state, and data transmission to the sink. The first phase only provides a setup and does not take part in communication while being a contributor to network energy consumption. Many of the researchers have proposed cluster-based protocol for underwater communication and considered it cursorily or not cogitate it. This paper presents the simulation and analysis of this cluster setup phase and shows that the cluster setup phase is the main phase of the clustering strategy and consumes the network energy called surplus energy consumption. It is determining by the simulation that a maximum of 13.2% network surplus energy consume during thirty three percent of cluster head formation. It is also shown that 5% CH formation is most suitable for the network to minimize surplus energy to 9.5%. [ABSTRACT FROM AUTHOR]

Wireless sensor networks are one of the drastically growing networks in recent times. It supports a greater number of applications in real time industries and automation sectors. All the applications of WSN comprises of numerous numbers of sensor nodes where they are deployed in a manner according to the application needs. Sensor nodes sense, monitor, record, receive and transmit any kind of data based on its manufacturing motivation. Sensors are cheap in cost, small in size and restricted in energy efficiency. Owing to their remote deployment and small size, they are provided with limited battery power. When the energy drains out, it becomes dead and thus causes a bottleneck in the communication process. Subsequent failure of nodes due to inefficient routing methods tends to degrade the network lifetime and overall performance. Several earlier research methods were used for improving the network lifetime and reliability of node's connection and communication. Most of the methods were not able to provide optimal performance towards enhancing overall QoS which happens to be a collective attribute. This paper proposes a novel Graph Theory Clustering method (GTC) to do node clustering, data aggregation and load balancing in WSN. The entire process of GTC has three modules or stages. First stage focuses on clustering and cluster head selection. Second stage focuses on distance computation. The third stage focuses on shortest path calculation for finding shortest route to do data transmission where it reduces the energy level, delay, packet loss, and load balancing. The proposed GTC is simulated in NS2 software, and the performance compared against existing benchmark methods. Various metrics have been computed and analyzed and superior performance of proposed GTC is observed in each case. [ABSTRACT FROM AUTHOR]

Now-a-days, with the augmenting accident statistics, the Vehicular Ad-hoc Networks (VANET) are turning out to be more popular, helping in prevention of accidents in addition to damage to the vehicles together with populace. In VANET, message can well be transmitted within a pre-stated region to attain system's safety and also improve its efficacy. Ensuring authenticity of messages' is a challenge in such dynamic environment. Though few researchers worked on this, security level is very less. Hence enhanced communication security on the VANET environment utilizing the American Standard Code for Information Interchange centred Elliptic Curve Cryptography (ASCII-ECC) is proposed in this paper. The network design is defined initially. Subsequently, the entire vehicles get registered to the Trusted Authority (TA); similarly, all vehicle users are registered with their On-Board Unit (OBU). This is followed by Median-centred K-Means (MKM) performs the cluster formation together with Cluster Head Selection (CHS). Next, TA takes care of the verification procedure. Modified Cockroach Swarm Optimization (MCSO) calculates the shortest path and the ASCII-ECC carries out the secure data communication if the vehicle is an authorized one. If not, TA sends the alert message for discarding the request. The system renders better performance when it was weighed against the top-notch methods. [ABSTRACT FROM AUTHOR]

An accurate localization technique is considered as the significant entity in vehicular ad hoc networks (VANETs) for facilitating emergency message data transmission in diversified critical safety applications. In VANETs, the system of global positioing is generally used for estimating the position of the vehicles in the network for attaining neighborhood awareness in the event of warning message dissemination. However, the existence of green foliages, buildings, indoor parking lots and urban streen canyons introduces NLOS situation that introduces unwanted errors that crumbles the degree of data dissemination in emergency situations. In this paper, spotted hyena and simulated annealing optimization algorithm (SHSAOA)-based positioning scheme was proposed for precise estimation of NLOS nodes. İt included the advantages of improved simulated annealing (SA) integrated into SHOA for establishing better balance between the process of exploitation and exploration in the search space. This positioning approach generated candidate solutions by deriving the merits of the trajectory-based charateristics of SA throughout the algorithmic development process in order to improve the local optimization process. This proposed SHSAOA utilized the distance infotmation that are associated with the vehicle trajectory, number of vehicles and error in distance information for assessing the precise location of the NLOS nodes in the network. The simulation results of the proposed SHSAOA scheme confirmed minimized localization error with maximized accuracy in transmission, warning message transmission rate, channel utilization degree and neighborhood awareness degree with different vehicular density and NLOS nodes. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSN) is an increasingly growing field, due to its enormous applications. In WSNs, energy conservation is the most important design challenge. In WSNs, unequal clustering can be classified as the best data transmission method that saves energy, where the size of the cluster changes in proportion to the cluster head's (CH's) distance from the base station (BS), so as to prevent energy holes/hot-spots from being formed. We have developed GA-UCR in this paper, a "Genetic Algorithm based Unequal Clustering and Routing Protocol for Wireless Sensor Networks". For CH election, genetic algorithm (GA) has been utilized with three fitness functions- remaining energy of CH nodes, distance between CH and BS/sink, and inter-cluster separation. For inter-cluster multi-hopping, to route the data towards BS, again GA is utilized due to the NP-Hard nature of the problem, with three fitness functions-residual/remaining energy of next hop nodes, CH to next hop node distance and number of hops. Simulation outcomes and analysis show that with reference to energy consumption, network lifetime and scalability, the proposed algorithm exceeds the existing algorithms such as Direct propagation, LEACH, TL-LEACH, GCA, EAERP and GAECH. [ABSTRACT FROM AUTHOR]

Cluster head (CH) selection is a critical function in Internet of Things (IoT) networks as it has a crucial role in determining the energy efficiency and security of data transmission. In this research work, a new Energy and Security-Aware Data Transmission in IoT is introduced with the assistance acquired from clustering model and meta-heuristic optimization algorithm. The proposed model includes two major phases: (a) clustering head selection and clustering and (b) optimal path-based data transmission. Initially, the IoT's sensor nodes are grouped together (i.e., clustered). A cluster head (CH) oversees each cluster and has the ability to broadcast messages to all sensors in the clusters as well as to other clusters. Among the available CHs, the optimal CH is chosen using a new multi-objective hybrid optimization strategy. The multi-objectives including energy, delay, execution time, distance (Euclidean distance between nodes and distance to sink node), residual energy of the nodes is taken into consideration for selecting the optimal CH. Additionally, the Chimp optimization and Spiral Dynamics optimization algorithms are combined called as Spiral Chip Dynamics Optimizer (SCDO) to choose the best sensor node (optimum CH) out of those that satisfy the multi-objective function. SCDO is an optimization algorithm that uses mathematical models to optimize the selection of cluster heads in an IoT network. By using this algorithm, the energy consumption of the network can be reduced while also ensuring secure data transmission. The algorithm takes into account various factors such as the distance between devices, the energy level of devices, and the security requirements of the network. The proposed approach is evaluated through PYTHON software, which demonstrate its effectiveness in enhancing security and lowering energy usage in IoT networks. The findings demonstrate that in terms of energy efficiency and security, the suggested methodology performs better than the alternatives. The paper provides a valuable improvement in the domain of IoT networks by addressing the important issue of balancing energy efficiency and security in data transmission. It provides a promising solution for improving the performance of IoT networks through optimal cluster head selection. [ABSTRACT FROM AUTHOR]

In a variety of applications like military, healthcare, and industrial monitoring, Internet of Things (IoT) centered Wireless Sensor Networks (WSNs) are broadly utilized. The data is transmitted from the source Sensor Nodes (SNs) to the destination SNs. These are likely to be done in a secure way; also, in less time. In this paper, via proposing a Mutation grounded Multi-Layer Perceptron (MUMLP), energy and secure aware optimal routing are executed to provide secure data transmission along with reducing the transmission time. For Data Aggregation (DA), by proposing the Boltzmann Selection Probability-centric Gravitational Search Algorithm (BSP-GSA), the optimal Cluster Heads (CHs) are selected. These are done after node initialization in the network. After that, the non-cluster members are combined with an adjacent CH to form a cluster. The data are gathered by the CHs as of the non-cluster members; also, the gathered data, which are encrypted utilizing the Improved Elliptical Curve Cryptography (IECC) mechanism, are secured. Through the optimal route selected by a Deep Learning (DL) algorithm (MUMLP) with the consideration of a novel fitness function, the encrypted data is then dispatched to the Base Station (BS). For user access, the data in the BS is stored in a cloud server. The BlockChain (BC)-enabled authentication, which permits only the authorized user for data access, is executed to prevent unauthorized access. To evaluate the proposed approach's efficiency, simulations are performed. The outcomes display that when analogized to the prevailing mechanisms, the presented algorithm performs data transmission in a secure as well as energy-aware manner. [ABSTRACT FROM AUTHOR]

Adhoc network expansion to FANET has attracted researchers and different companies to think of it as a trade and let users use it as per their needs. Mobility, in contrast to the mobile revolution, has led to its implementation on different networks. FANET is a case where mobility is inculcated with flying nodes where UAVs are deployed in real-time scenarios linked together-operating cooperatively in the best possible coordination for successful data transmission to a base station. The operational efficiency of such networks is in different rapidly changing missions, from line-of-sight to beyond-line-of-sight. Mission applicability ranging from rescue, disaster relief, army, surveillance, delivery of goods, agriculture, 3D mapping, and many others necessitates the development of a competent routing protocol that takes into account the nature of the application and amenities for positioning UAVs. Routing in UAVs has serious questions owing to its fast mobility, sometimes static and, at the same time, static with dynamic. According to recent studies, directed transmission and reception can achieve significant throughput improvements over omnidirectional transmission and reception. Numerous routing protocols are proposed, but each has its pros and cons for such dynamic flying networks. This paper presents the simulation-based performance of the OLSR routing protocol in various propagation models for FANET with directional antenna in different scenarios and considerations (parameters). [ABSTRACT FROM AUTHOR]

In this era, we need to make everything about us more smartly and communicating. Hence, the popularity of Internet of Thing (IoT) is increasing quickly across industries. In such networks, the sensors represent the eyes of the IoT that collect data about different environments and states, while the sink node forms the brain of the network that must analyze the collected data and take decisions. However, the big amount of data collected by the sensors leads, from one hand, to consume the limited energy of the sensor and, from another hand, to complicate the exploitation of the data at the sink for decision making. In this paper, we propose a multi-tier prediction mechanism in order to handle big data collected by sensor networks based on the clustering scheme. The prediction model uses the least squares approximation method which is applied at both tiers of each cluster: sensors and cluster-heads (CHs). At the first tier, each sensor applies the prediction model in order to send a reduced set of data to its appropriate CH; At the second tier, the CH combines data coming from sensors and provides a predictive model to the sink, representing data for all sensors of the cluster. Extensive simulations on real sensor data collected from several applications demonstrated that our mechanism can efficiently reduce the data transmission and save the network energy, while maintaining an acceptable data accuracy level. [ABSTRACT FROM AUTHOR]

The quantity of Telemetry Data (TD) is rapidly augmenting because of a large extent of involved parameters in addition to the use of higher sampling frequencies. Therefore, to enhance the transmission efficiency as well as lessen the load on spacecraft resources, effectual Data Compression approaches in space TD are required. Further, the TD is suffered as of some faults. Therefore, to identify that fault data and render secure Data Transmission, the fault-analysis and data security techniques are needed onboard. It is challenging to attain higher Compression Ratios together with higher accuracy in lossless compression together with fault analysis. This paper designs an effective lossless TD compression as well as fault analysis scheme to trounce all these challenges. This scheme comprises:— (i) compression, (ii) encryption and (iii) classification. In the compression stage, the 2SMLZ compress the redundancy removed TD. In the encryption stage, the EECC algorithm encrypts the compressed data, so that the encrypted data can well be transmitted securely to the Ground Station (GS). In the GS, for recovering the original data, the decryption, as well as the decompression process, are carried out. Conversely, the CMOW-DLNN classifier identifies the fault data on the fault analysis stage. The proposed techniques effectively compress the data, as well as securely transmit the data and accurately recognize the fault data, which are experimentally proved by contrasting it with existing techniques. [ABSTRACT FROM AUTHOR]

Cognitive radio network (CRN) has been recognized by researchers to solve the spectrum shortage problem, where the unlicensed users opportunistically exploit the idle licensed channels for data transmission. Prior to the data transmission, the SUs should rendezvous on an available idle licensed channel to establish a link or to exchange control information without causing interference to the co-located licensed channels. However, the dynamic behavior of channels and its availability make the rendezvous more challenging. A blind rendezvous on the available channels without any centralized unit, or a common control channel is preferable to address issues like long-time blocking, control channel saturation, and scalability in a congested network. In this paper, a blind rendezvous for a specific CRN is proposed, where a Role-Based Channel Hopping is introduced to achieve guaranteed rendezvous in an asynchronous environment. Analytical study shows that for N available channels, the maximum time to rendezvous is N + ⌊ N 2 ⌋ , degree of rendezvous is N, maximum conditional time to rendezvous is N 2 and Channel loading is 1 N . [ABSTRACT FROM AUTHOR]