Akash Ghosh

The amplified concern in cloud and fog computing calls for a stimulus in the demands on the strategies that allocate virtual machines to amplify energy efficiency to alleviate high energy utilization and the environmental impacts that arise from it. This research presents a green computing approach that employs decentralized, peer-to-peer fog nodes in dynamic VM allocation within the fog and cloud ecosystems. Unlike traditional central allocation schemes, the proposed model allows for autonomous management, distribution, and sharing of workload at the level of a fog node, depending upon local capacity, real-time demands, and determined energy efficiency. P2P collaboration at geographically distributed fog nodes evokes optimal resource usage, minimal latency, energy costs, and carbon footprint. An energy-aware allocation algorithm is developed that integrates real-time workload prediction, power consumption metrics, and renewable energy availability across the boundaries of fog and cloud environments to enhance sustainability. Experimental results demonstrate that the decentralized P2P framework not only diminishes power utilization but also improves the response times for services and minimizes the overall environmental footprint of fog/cloud operations.

Server-less computing is a novel cloud-based paradigm that is gaining popularity today for running widely distributed applications. When it comes to server-less computing, features are available via subscription. Server-less computing is advantageous to developers since it lets them install and run programs without worrying about the underlying architecture. A common choice for code deployment these days, server-less design is preferred because of its independence, affordability, and simplicity. The healthcare industry is one excellent setting in which server-less computing can shine. In the existing literature, we can see that fewer studies have been put forward or explored in the area of server-less computing with respect to smart healthcare systems. A cloud infrastructure can help deliver services to both users and healthcare providers. The main aim of our research is to cover various topics on the implementation of server-less computing in the current healthcare sector. We have carried out our studies, which are adopted in the healthcare domain and reported on an in-depth analysis in this article. We have listed various issues and challenges, and various recommendations to adopt server-less computing in the healthcare sector.

The increasing use of the Internet of Things (IoT), which has resulted in an exponential growth in network traffic, has serious implications on energy consumption and network performance. To reduce power consumption in cloud data centers, a server vacation-based energy-efficient traffic management solution is recommended. The primary idea is that using software-defined network (SDN) technologies, cloud system virtual machines (VMs) can take vacations. The goal of the energy-saving optimization task is to reduce the number of virtual machines (VMs) in use while maintaining service quality standards. This research study focuses on impatient client behaviour, several vacations, limited buffer and queuing system with many servers. Impatient customers may be kept in the cloud system by implementing certain customer retention strategies. The steady-state probability for the proposed SDN-assisted cloud system have been determined using recurrences. To determine the efficiency of the proposed system, several performance studies are conducted.

As Advanced Persistent Threats (APTs) proliferate and evolve, they constitute an increasingly formidable challenge to organizational cybersecurity frameworks. The imperative for innovative, multifaceted detection methodologies has never been more critical. This manuscript elucidates a groundbreaking framework that ingeniously synergizes Central Processing Unit (CPU) utilization metrics with the principles of Zero-Trust architecture. Our approach scrutinizes the nuanced, idiosyncratic patterns of CPU utilization that are indicative of APT activities. Significantly, this method is adept at identifying hallmarks of APTs congruent with criteria delineated in the MITRE ATT&CK framework-specifically in stages antecedent to lateral movement tactics. Parallel to this, the framework assimilates the austere security policies typified by Zero Trust architecture, culminating in a holistic, dynamically adaptive defense mechanism. Rigorous experimental validations conducted in realistic operational environments substantiate the efficacy of our approach, which attained an unparalleled accuracy rate of 99.7% in the detection of APTs. The manifest advantages of this multifaceted strategy extend beyond mere detection efficacy, offering perspicacious insights into the operational modalities of APTs, thereby fostering the capability for preemptive cybersecurity initiatives. The contributions of this study are poised to significantly augment both academic discourse and practical applications in the persistent endeavor to fortify cybersecurity infrastructures against ever-escalating APT threats.

When conventional communication routes are unavailable or malfunctioning, mobile adhoc networks (MANETs) are essential for establishing communication. These networks can be easily and cheaply built whenever necessary because they don't require any pre-existing infrastructure. In some extreme situations (such as floods, battle zones, rescue operations, etc.), MANETs cannot be used. Lacking a fixed infrastructure in some situations, flying ad hoc networks (FANETs) can be quite useful for establishing communication. In FANETs, many drones are connected one to another directly or through middle nodes. In this research work, the arrival rate of events during the catastrophe, the drone's service rate, the waiting buffer of the system is considered and various performance measures such as the waiting time of the requests in the waiting buffer, the waiting time of the requests in the system, average queue length and the drones' idle time have all been considered. The ideal number of drones should be used to handle catastrophic occurrences and reduce casualties by adopting the queuing model.