A Novel Communication Pathway Metric Evaluation using Throughput and Energy Improvements over Wireless Sensor Networks

Lifetime connectivity and low power consumption are two requirements for WSNs. Additionally, increasing WSN commercialization, application monitoring for higher QoS. Maintaining the improvement of the wireless sensor networks effectiveness requires the establishment of the energy-efficient and consistent connection. In order to increase the efficiency of routing algorithms in latest technology assisted WSNs, a novel method is developed. The gadgets with the lowest power consumption are carefully selected for the appropriate use and carefully managed. The goal of this research is to develop low-power routing algorithms for use in WSNs. Numerous sectors, including the military, the medical profession, surveillance of observing, public transportation sectors etc., can benefit from wireless sensor networks deployed with a large number of mobile nodes in a communications system. To examine data from nodes that are freely moving about the zone, we developed and simulated a wireless network system based on the Distributed Internet of Things. The proposed method of Intelligent Route Metric Analyzer (IRMA) improves upon the efficiency of the standard algorithm with regards to energy consumption. In addition, the ground wireless sensing design's ideal trajectory is identified using a realistic tempering approach. In the end, this concept is compared to similar ones like AODV and the findings reveal that it performs better with regard to of energy consumption, delay and other important metrics. According to the paper we analyzed, the primary objective was to devise a routing method that would sustain network operation for as long as feasible by decreasing the energy needed for different operations at each individual sensor node while keeping the total energy consumption of the nodes constant over their lifetimes. Finally, the study makes a contribution to the ongoing discussion of the difficulties in developing a routing protocol for WSN, taking into account the interdependency of different network factors. Median throughput, median network latency, and standardized route load are only few of the efficiency metrics addressed in this article

Different Security Mechanisms for Wireless Sensor Networks

In today’s world security becomes one of the important constraints in every research field. As increasing use of Wireless Sensor Networks (WSN) in various crucial applications security of wireless networks is becoming more important day by day. Today almost each and every important area makes use of wireless sensor networks. As Wireless Sensor Network is infrastructure-less network; data moves openly from one node to another thus it can be captured easily by attackers. To avoid data from being stolen security mechanism has to be applied. Many protocols are available for providing security on wireless network. We perform a detailed study of different security mechanisms used in sensor network against some criteria such as nature of algorithm, working, its benefits and some of the disadvantages of mechanism and also compare them

Machine Learning-Enhanced Advancements in Quantum Cryptography: A Comprehensive Review and Future Prospects

Quantum cryptography has emerged as a promising paradigm for secure communication, leveraging the fundamental principles of quantum mechanics to guarantee information confidentiality and integrity. In recent years, the field of quantum cryptography has witnessed remarkable advancements, and the integration of machine learning techniques has further accelerated its progress. This research paper presents a comprehensive review of the latest developments in quantum cryptography, with a specific focus on the utilization of machine learning algorithms to enhance its capabilities. The paper begins by providing an overview of the principles underlying quantum cryptography, such as quantum key distribution (QKD) and quantum secure direct communication (QSDC). Subsequently, it highlights the limitations of traditional quantum cryptographic schemes and introduces how machine learning approaches address these challenges, leading to improved performance and security. To illustrate the synergy between quantum cryptography and machine learning, several case studies are presented, showcasing successful applications of machine learning in optimizing key aspects of quantum cryptographic protocols. These applicatiocns encompass various tasks, including error correction, key rate optimization, protocol efficiency enhancement, and adaptive protocol selection. Furthermore, the paper delves into the potential risks and vulnerabilities introduced by integrating machine learning with quantum cryptography. The discussion revolves around adversarial attacks, model vulnerabilities, and potential countermeasures to bolster the robustness of machine learning-based quantum cryptographic systems. The future prospects of this combined field are also examined, highlighting potential avenues for further research and development. These include exploring novel machine learning architectures tailored for quantum cryptographic applications, investigating the interplay between quantum computing and machine learning in cryptographic protocols, and devising hybrid approaches that synergistically harness the strengths of both fields. In conclusion, this research paper emphasizes the significance of machine learning-enhanced advancements in quantum cryptography as a transformative force in securing future communication systems. The paper serves as a valuable resource for researchers, practitioners, and policymakers interested in understanding the state-of-the-art in this multidisciplinary domain and charting the course for its future advancements

PHYSICAL LAYER SECURITY OF WIRELESS SENSOR NETWORK BASED ON OPPORTUNISTIC SCHEDULING

In this paper, a physical layer security analysis of wireless sensor network in the presence of an attacker, employing opportunistic scheduling approach, is presented. The intended as well as unintended transmission paths experience the Weibull fading. A novel analytical expression for the intercept probability is derived. In order to emphasize the advantages of the opportunistic scheduling approach, a comparative analysis with round-robin and optimal scheduling schemes is also given. The impact of a number of active sensors and the impact of fading channel conditions over main and wiretap channels on the intercept probabilities is obtained. The accuracy of theoretical results is confirmed by independent Monte Carlo simulation results

Network Coding on Heterogeneous Multi-Core Processors for Wireless Sensor Networks

While network coding is well known for its efficiency and usefulness in wireless sensor networks, the excessive costs associated with decoding computation and complexity still hinder its adoption into practical use. On the other hand, high-performance microprocessors with heterogeneous multi-cores would be used as processing nodes of the wireless sensor networks in the near future. To this end, this paper introduces an efficient network coding algorithm developed for the heterogenous multi-core processors. The proposed idea is fully tested on one of the currently available heterogeneous multi-core processors referred to as the Cell Broadband Engine

Energy and Load Aware Multipath Route Selection for Mobile Ad hoc Networks

Routing protocols are crucial in delivering packets from source to destination in scenarios where destinations are not directly within the sender’s range. Various routing protocols employ different strategies, but their presence is indispensable for seamless data transfer from source to destination. Multipath routing, while offering load balancing, often falls short in efficiently distributing the network’s load, thus adversely impacting the vital communication resource—energy—due to packet loss. This paper introduces an Energy-Efficient Load-Aware Routing (ELAM) scheme to enhance the routing performance of Mobile Ad hoc Networks (MANETs). Our motivation stems from the observation that many multipath routing protocols are designed based on a single criterion, such as the shortest path, often neglecting load balancing or energy conservation. While the Ad Hoc On-Demand Multipath Distance Vector (AOMDV) protocol demonstrates improved performance compared to unipath routing schemes, achieving both load balancing and energy efficiency remains challenging.  The proposed ELAM scheme considers energy conservation, the shortest path, and load balancing to enhance the performance of multipath routing protocols. ELAM considers the shortest path and energy conservation while accommodating more than two paths in a MANET. We introduce an energy factor that contributes to the network’s lifespan, with efficient load balancing enhancing the longevity of nodes and the overall network. The energy factor provides insights into the energy status, and we evaluate the performance of AODV, AOMDV, and the proposed ELAM. The results demonstrate that the proposed scheme outperforms existing protocols and effectively manages unnecessary energy consumption by mobile nodes. Our performance analysis reveals a minimum 5% improvement in throughput and Packet Delivery Ratio (PDR), indicating reduced packet dropping and network delays

Broadcasting in LTE-Advanced networks using multihop D2D communications

In an LTE-Advanced network, network-controlled Device-to-Device (D2D) communications can be combined in a multihop fashion to distribute broadcasts over user-defined (and possibly large) areas, with small latencies and occupying few resources. Such a service may be exploited for several purposes, (e.g. Internet of Things, Vehicular communications). Engineering a multihop D2D-based broadcast service requires working at both the application level on the User Equipment (UE) and at the resource-allocation level within the eNodeBs. This paper describes the necessary modifications at both the UE and the eNodeB, what the main issues are, and how to solve them efficiently. We evaluate the performance of the above service using system-level simulations, and demonstrate its advantages over standard broadcasting techniques

Cooperative agent-based SANET architecture for personalised healthcare monitoring

The application of an software agent-based computational technique that implements Extended Kohonen Maps (EKMs) for the management of Sensor-Actuator networks (SANETs) in health-care facilities. The agent-based model incorporates the BDI (Belief-Desire-Intention) Agent paradigms by Georgeff et al. EKMs perform the quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organize. Current results show a combinatorial approach to optimization with EKMs provides an improvement in event trajectory estimation compared to standalone cooperative EKM processes to allow responsive event detection for patient monitoring scenarios. This will allow healthcare professionals to focus less on administrative tasks, and more on improving patient needs, particularly with people who are in need for dedicated care and round-the-clock monitoring. ©2010 IEEE

Deployment of an agent-based SANET architecture for healthcare services

This paper describes the adaptation of a computational technique utilizing Extended Kohonen Maps (EKMs) and Rao-Blackwell-Kolmogorov (R-B) Filtering mechanisms for the administration of Sensor-Actuator networks (SANETs). Inspired by the BDI (Belief-Desire-Intention) Agent model from Rao and Georgeff, EKMs perform the quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organize, while the Rao-Blackwell filtering mechanism reduces the external noise and interference in the problem set introduced through the self-organization process. Initial results demonstrate that a combinatorial approach to optimization with EKMs and Rao-Blackwell filtering provides an improvement in event trajectory approximation in comparison to standalone cooperative EKM processes to allow responsive event detection and optimization in patient healthcare