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The hybrid wireless sensor network is made up of Wireless Body Area Network (WBAN). Generally, many hospitals use cellular networks to support telemedicine. To provide the treatment to the patient on time, for this, an early diagnosis is required, for treatment. With the help of WBANs, collections and transmissions of essential biomedical data to monitor human health becomes easy. Compressor Sensing (CS) is an emerging signal compression/acquisition methodology that offers a protruding alternative to traditional signal acquisition. The proposed mechanism reduces message exchange overhead and enhances trust value estimation via response time and computational resources. It reduces cost and makes the system affordable to the patient. According to the results, the proposed scheme in terms of Compression Ratio (CR) is 18.18% to 88.11% better as compared to existing schemes. Also in terms of Percentage Root-Mean-Squared Difference (PRD) value, the proposed scheme is 18.18% to 34.21% better than with respect to existing schemes. The consensus for any new block is achieved in 24% less time than the Proof-of-Work (PoW) approach. The shallow CPU usage is required for the leader election mechanism. CPU utilization while the experiment lies in the range of 0.9% and 14%. While simulating a one-hour duration, the peak CPU utilization is 21%.

Sixth-generation (6G) wireless networking studies have begun with the global implementation of fifth-generation (5G) wireless systems. It is predicted that multiple heterogeneity applications and facilities may be supported by modern wireless communication networks (MWCNs) with improved effectiveness and protection. Nevertheless, a variety of trust-related problems that are commonly disregarded in network architectures prevent us from achieving this objective. In the current world, MWCN transmits a lot of sensitive information. It is essential to protect MWCN users from harmful attacks and offer them a secure transmission to meet their requirements. A malicious node causes a major attack on reliable data during transmission. Blockchain offers a potential answer for confidentiality and safety as an innovative transformative tool that has emerged in the last few years. Blockchain has been extensively investigated in several domains, including mobile networks and the Internet of Things, as a feasible option for system protection. Therefore, a blockchain-based modal, Transaction Verification Denied conflict with spurious node (TVDCSN) methodology, was presented in this study for wireless communication technologies to detect malicious nodes and prevent attacks. In the suggested mode, malicious nodes will be found and removed from the MWCN and intrusion will be prevented before the sensitive information is transferred to the precise recipient. Detection accuracy, attack prevention, security, network overhead, and computation time are the performance metrics used for evaluation. Various performance measures are used to assess the method’s efficacy, and it is compared with more traditional methods.

This article focuses on implementing wireless sensors for monitoring exact distance between two individuals and to check whether everybody have sanitized their hands for stopping the spread of Corona Virus Disease (COVID). The idea behind this method is executed by implementing an objective function which focuses on maximizing distance, energy of nodes and minimizing the cost of implementation. Also, the proposed model is integrated with a variance detector which is denoted as Controlled Incongruity Algorithm (CIA). This variance detector is will sense the value and it will report to an online monitoring system named Things speak and for visualizing the sensed values it will be simulated using MATLAB. Even loss which is produced by sensors is found to be low when CIA is implemented. To validate the efficiency of proposed method it has been compared with prevailing methods and results prove that the better performance is obtained and the proposed method is improved by 76.8% than other outcomes observed from existing literatures.

The process of incorporating robotic technology and autonomous vehicles are increasing in all applications where for all real-time application developments time and energy can be saved for every single movement transfer as compared to human classifications. Thus, considering the advantage of autonomous process without any presence of an individual, the supply chain management can be designed using robotic technology. The robotic technology provides an informal route where all goods can be transported to different places within a short span of time, and any false identification in transfer of goods can also be easily identified. To drive the autonomous vehicle towards correct location, a precise protocol is chosen, which is termed common industrial protocol (CIP) where proper solutions can be achieved for all control applications using time synchronization model. Further, the data monitoring process is trailed using an online contrivance which is termed as internet router (IR) where short distance can be identified using corresponding addressing scheme.

The Mobile Adhoc Network (MANET) is a wireless network model for infrastructure-less communication, and it provides numerous applications in different areas. The MANET is vulnerable to a Black-hole attack, and it affects routing functionality by dropping all the incoming packets purposefully. The Black-hole attackers pretend that it always has the best path to the destination node to mislead the source nodes. Trust is the critical factor for detecting and isolating the Black-hole attackers from the network. However, the harsh channel conditions make it difficult to differentiate the Black-hole routing activities and accurate trust measurement. Hence, incorporating the consensus-based trust evidence collection from the neighbouring nodes improves the accuracy of trust. For improving the accuracy of trust, this work suggests Consensus Routing and Environmental DIscrete Trust (CREDIT) Based Secure AODV. The CREDIT incorporates Discrete and Consensus trust information. The Discrete parameters represent the specific characteristics of the Black-hole attacks, such as routing behaviour, hop count deviation, and sequence number deviation. The direct trust accurately differentiates the Black-hole attackers using Discrete parameters, only when the nodes perform sufficient communication between the nodes. To solve such issues, the CREDIT includes the Consensus-based trust information. However, secure routing against the Black-hole attack is challenging due to incomplete preferences. The in-degree centrality and Importance degree measurement on the collected consensus-based trust from decisionmakers solve the incomplete preference issue as well as improves the accuracy of trust. The performance of the proposed scheme is evaluated using Network Simulator-2 (NS2). From the simulation results, it is proved that the detection accuracy and throughput of the proposed CREDIT are substantially high and the proposed CREDIT scheme outperforms the existing work.

In this paper, we represent the effect of Black Hole attack in AODV routing protocol in MANET is analyzed. We also compare the network performance of standard AODV against Black Hole attack on AODV routing protocol. Simulation is carried out using NS-2.35. It depicts that PDR percentage and Average Throughput decrease and End to End Delay (EED) increases due to the presence of malicious nodes in the Mobile Ad-Hoc Network.