Reliable communication is critical for multi-unmanned surface vehicle systems operating in dynamic maritime environments. When a communication link fails, the affected unmanned surface vehicle must make reliable decisions to re-establish connectivity and maintain coordinated operations. However, relying on a single metric for candidate evaluation often leads to unstable or suboptimal reconnections. To address this issue, we propose a multi-factor decision model that integrates distance, formation deviation, link stability, and redundancy. A Kalman filter-based mechanism is introduced to estimate link stability, enabling robust assessment under noisy and time-varying conditions. Three performance metrics are used to compare the proposed method with greedy and received signal strength indicator-based algorithms. Simulation results demonstrate that the proposed approach achieves lower formation deviation and higher link stability than baseline methods, highlighting its effectiveness in maintaining reliable connectivity.
In recent times, healthcare data security has become the major constrained as the data collected from Body Area Networks (BAN) and other medical networks need to be effectively leveraged for legitimate medical research and data analysis purposes. This is mainly because of the reason that any compromise in healthcare data security can adversely impact the quality of medical predictive models, acceleration of new medical research and the effectiveness of the data-driven medical treatments. To overcome these constraints, this paper presents a secure and privacy preserving mutual authentication scheme for cloud-assisted multi-tenant healthcare systems. The proposed approach enables secure verification of communicating healthcare entities and to establish the secure data transmission without the compromise of the original identities. Further, the proposed approach makes use of Physically Unclonable Functions (PUF) and chained hash function to make the system more secure and efficient. This approach is implemented using Automated Validation of Internet Security Protocols and Applications (AVISPA) tool and various parameters such as network performance, storage cost, communication cost, and computational complexity measures are used for the evaluation purpose. It is observed from the experiment that the proposed approach provides significantly improved results than the conventional approaches.
A Mobile Ad-hoc Network (MANET) is a wireless network where mobile devices communicate directly without centralized infrastructure. However, node mobility causes topological changes, impacting performance and necessitating route detection. This study proposes a Mobility Addressing Algorithm (MAA) to enhance MANET routing protocol efficiency. MAA enables informed message-discarding decisions based on factors such as distance, speed, and residual energy, reducing link breakages and broadcast challenges. The algorithm's effectiveness is evaluated using metrics like Alternate End-to-End Delay (AETED), Packet Delivery Ratio (PDR), throughput, and routing overhead. MAA is particularly suited for highly mobile node scenarios, ensuring robust communication in dynamic routing environments.
Nowadays modern developments in communication technologies attained more reputation by utilizing the idea of the Internet of Things (IoT). In Wireless Sensor Network (WSN) assisted IoT environment constructed with more number of independent sensor nodes. These sensing nodes monitor the atmosphere robotically, gather details, and deliver the collected information to the paired base control stations. On the other hand, in WSN-assisted IoT models power exhaustion and faults in hardware lead to system failures. Thus it collapses the data communication. The clustering technique is utilized for reducing the network traffic over the network, while the multipath system ensures path dependability. For achieving efficient and secure data communication and energy-preserved cluster head selection, this research introduces a Puzzle Jellyfish Search Optimization (PJSO) algorithm for WSN-assisted IoT networks. The proposed PJSO is devised by integrating the Puzzle Optimization Algorithm (POA) and the Jellyfish Search Optimization (JSO) algorithm. Initially, the WSN-IoT nodes are simulated in which the energy model and trust models are constructed. Further, the selection of CH and secure communication through the optimal routing path is done using PJSO by considering energy, distance, trust factors, delay, and throughput of the node. Finally, the routing is carried out using same PJSO; the newly devised PJSO for secure routing and CH selection model obtained the obtained energy as 0.432 J, distance as 0.267 m, delay as 0.240 ms, and trust as 0.386.
WSNs have been deployed in many fields where the sensor nodes are usually dispersed throughout challenging areas to provide ongoing data gathering and monitoring. Modern wireless and electrical technologies have combined to enhance WSNs. Due to their frequent usage in unsupervised and hostile situations; Sensor nodes (SNs) are vulnerable to adversary node capture and collusion efforts. Cryptographic techniques are crucial to WSN security because they protect the entire network. Security is the primary concern since it is nearly impossible to do node authentication without impacting the longevity of the networks. This research offers the key management and mutual authentication technique for WSN connecting edge devices, which also employs a modified encryption standard for key management. The proposed model involves the following steps: Optimal Routing, Key management and mutual authentication. This work proposes a new hybrid optimization algorithm for optimal routing under the consideration of trust, risk, link quality, distance, and energy. For this, the Shuffled Combined Beluga whale algorithm (SCBWA) is implemented with the combination of Shuffled shepherd optimization and Beluga whale optimization. In the Key management and mutual authentication step, the Modified Advanced Encryption Standard (MAES) is proposed to ensure security via key management and following the key establishment and mutual authentication. The suggested SCBWA model has greater mean values (0.984) at node 200 than the other earlier schemes, such as SSO, BWO, TSO, BFO, TDO, and CM-MH. Finally, using a variety of criteria, the chosen technique is evaluated with other techniques.
