Sukhpal Singh Gill

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Verified

Sukhpal Singh verified their affiliation via an institutional email.

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• PhD
• Academic at Queen Mary University of London

Autonomic computing investigates how systems can achieve (user) specified “control” outcomes on their own, without the intervention of a human operator. Autonomic computing fundamentals have been substantially influenced by those of control theory for closed and open-loop systems. In practice, complex systems may exhibit a number of concurrent and...

Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI refers to the practice of doing AI computations near the users at the network's edge, instead of centralised location like a cloud service provider's data centre. With the latest innovations in AI efficiency, the proliferation of Internet of Things (IoT...

Artificial intelligence (AI) and machine learning have changed the nature of scientific inquiry in recent years. Of these, the development of virtual assistants has accelerated greatly in the past few years, with ChatGPT becoming a prominent AI language model. In this study, we examine the foundations, vision, research challenges of ChatGPT. This a...

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapti...

ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the educat...

Quantum Computing: Principles and Paradigms covers a broad range of topics, providing a state-of-the-art and comprehensive reference for the rapid progress in the field of quantum computing and related technologies from major international companies (such as IBM, Google, Intel, Rigetti, Q-Control) and academic researchers. This book appeals to a br...

This paper proposes a novel framework for a real-time music visualization system designed for the hearing-impaired, utilizing AI and serverless computing. The system converts audio signals into visual representations that capture both the physical and emotional aspects of music. A neural network-based Music Emotion Recognition (MER) model extracts...

Cloud computing, thanks to the pervasiveness of information technologies, provides a foundational environment for developing IT applications, offering organizations virtually unlimited and flexible computing resources on a pay-per-use basis. However, the large data centres where cloud computing services are hosted consume significant amounts of ele...

Coronary heart disease is a leading cause of mortality worldwide. Although no cure exists for this condition, appropriate treatment and timely intervention can effectively manage its symptoms and reduce the risk of complications such as heart attacks. Prior studies have mostly relied on a limited dataset from the UC Irvine Machine Learning Reposito...

Diabetes is a chronic disease affecting millions globally, necessitating the development of early detection tools to mitigate severe complications such as heart disease, kidney failure, and nerve damage. This project focuses on creating a cloud-based machine learning system to predict diabetes risk using the Pima Indians Diabetes Database. The prob...

As the cloud infrastructure grows, it becomes more challenging to manage resources in such a massive, diverse, and distributed setting, despite the fact that cloud computing provides computational capabilities on-demand. Due to resource variability and unpredictability, resource allocation issues arise in a cloud setting. A Quality of Service (QoS)...

The evolution of Artificial Intelligence of Things (AIoT), coupled with advancements in edge and cloud computing, has enabled the development of real-time IoT-based applications. Integrating Internet of Things (IoT) and AI-driven edge-cloud services can address challenges such as early disease detection, system performance, data management and envi...

The inherent volatility of the stock market presents significant challenges for accurate price forecasting, influenced by factors such as market sentiment, economic indicators, and geopolitical events. In this paper, we propose an Artificial Intelligence (AI)-based stock price prediction framework, StockAICloud, built with FastAPI to offer scalable...

Efficient cloud resource allocation is critical for optimising cloud computing services in terms of minimising operational costs and improving energy efficiency. The increasing demand for cloud services results in considerable energy consumption. In order to improve cloud sustainability and reduce energy consumption, the latest Artificial intellige...

Microservice architecture has transformed traditional monolithic applications into lightweight components. Scaling these lightweight microservices is more efficient than scaling servers. However, scaling microservices still faces the challenges resulted from the unexpected spikes or bursts of requests, which are difficult to detect and can degrade...

The growing number of consumer Internet of Things (IoT) gadgets, including smart homes, fitness trackers, connected appliances, and home security systems, is transforming the way we live our daily lives. This has led to the emergence of a collaborative cloud-edge paradigm to leverage resources and services near the end-user, thereby providing promp...

In cloud data centers, precise resource prediction is a critical issue due to the dynamic environment, the presence of irrelevant data points, and the unpredictable nature of resource demand. An accurate prediction helps with resource management, cost planning, and improving cloud-related services, whereas an inaccurate prediction increases the bud...

The generative Artificial Intelligence (AI) tools based on Large Language Models (LLMs) use billions of parameters to extensively analyse large datasets and extract critical information such as context, specific details, identifying information, use this information in the training process, and generate responses for the requested queries. The extr...

Quantum computing's current capacity to efficiently tackle complex problems exceeds that of traditional methods, as demonstrated by its use in optimisation and artificial intelligence. This chapter explains the concept of quantum computing, along with its differences from traditional computing. It further provides an overview of the fundamental ele...

Quantum computing is poised to revolutionize computational performance and capabilities, offering unprecedented efficiency in solving complex problems that surpasses classical approaches. This potential is particularly evident in fields such as optimization and AI. This chapter delves into critical priority areas in quantum computing, including the...

Edge Artificial Intelligence (AI) incorporates a network of interconnected systems and devices that receive, cache, process, and analyse data in close communication with the location where the data is captured with AI technology. Recent advancements in AI efficiency, the widespread use of Internet of Things (IoT) devices, and the emergence of edge...

Recently, academics and the corporate sector have paid attention to serverless computing, which enables dynamic scalability and an economic model. In serverless computing, users only pay for the time they actually use resources, enabling zero scaling to optimise cost and resource utilisation. However, this approach also introduces the serverless co...

Yellow fever is a vigorous, phlebotomic, vector-borne disease that poses a significant public health threat in regions with high mosquito density and inadequate vaccination coverage. The disease's toxic phase is lethal, making prompt identification and control measures crucial. The emergence of the latest technologies and data analytics techniques...

The vision for the sixth-generation (6G) network involves the integration of communication and sensing capabilities in internet of everything (IoE), towards enabling broader interconnection in the devices of distributed wireless sensor networks (WSN). Moreover, the merging of SDN policies in 6G IoE-based WSNs i.e. SDN-enable WSN improves the networ...

Cloud computing is an emerging choice among businesses all over the world since it provides flexible and world wide web computer capabilities as a customizable service. Because of the dispersed nature of cloud services, security is a major problem. Since it is extremely accessible to intruders for any kind of assault, privacy and security are major...

Kubernetes has revolutionized traditional monolithic Internet of Things (IoT) applications into lightweight, decentralized, and independent microservices, thus becoming the de facto standard in the realm of container orchestration. Intelligent and efficient container placement in Mobile Edge Computing (MEC) is challenging subjected to user mobility...

Deep neural network (DNN) and machine learning (ML) models/ inferences produce highly accurate results demanding enormous computational resources. The limited capacity of end‐user smart gadgets drives companies to exploit computational resources in an edge‐to‐cloud continuum and host applications at user‐facing locations with users requiring fast r...

Contributions: In this article, a generative artificial intelligence (AI)-based Q&A system has been developed by integrating information retrieval and natural language processing techniques, using course materials as a knowledge base and facilitating real-time student interaction through a chat interface. Background: The rise of advanced AI exempl...

The advent of cloud computing has made a global impact by providing on-demand services, elasticity, scalability, and flexibility, hence delivering cost-effective resources to end users in pay-as-you-go manner. However, securing cloud services against vulnerabilities, threats, and modern attacks remains a major concern. Application layer attacks are...

The escalating threat of easily transmitted diseases poses a huge challenge to government institutions and health systems worldwide. Advancements in information and communication technology offer a promising approach to effectively controlling infectious diseases. This article introduces a comprehensive framework for predicting and preventing zoono...

One of the most enticing research areas is the stock market, and projecting stock prices may help investors profit by making the best decisions at the correct time. Deep learning strategies have emerged as a critical technique in the field of the financial market. The stock market is impacted due to two aspects, one is the geo-political, social and...

In today's digital landscape, combating fraud has become paramount across industries like finance, healthcare, and e-commerce. This chapter employs a comparative approach to evaluate the effectiveness of various fraud detection models, both centralised and decentralised, across multiple datasets. Results reveal distinct model strengths and limitati...

Due to the heterogeneous characteristics of depression, diagnosis is often hard to perform and the time interval between first showing depression symptoms and the first treatment can be as big as 8 years. Given the ubiquitous nature of smartphones, it is not surprising that our emotions have a direct impact on our interactions with them. Furthermor...

Social events and gatherings have always been vital to the communal structure. With an ever-increasing amount of social events occurring each year, there is an increasing trend for tech platforms to plan, analyse, and promote events to reach audiences. These platforms, however, are restricted to covering only one aspect of the events, which is the...

Cancer has quickly risen to become one of the world's most serious health problems and the leading cause of death. Artificial intelligence (AI)-based solutions have been created recently to aid clinicians in making decisions that will lower morbidity and death. This contemporary research does, however, frequently suffer from explanations of its res...

Skin cancer is one of the world's most dangerous diseases. Early skin lesion classification could benefit medical decisions by enabling precise diagnostic accuracy, potentially raising the likelihood of treatment before cancer starts spreading. However, reaching fully automated skin cancer classification is challenging because the significant propo...

Federated learning (FL) has emerged as a promising approach to decentralise machine learning, offering advantages in privacy and data efficiency. This research chapter sought to compare the efficacy of FL with traditional machine learning (TML) in predicting household financial expenditure. Using the same multivariate linear regression (MLR) model...

Edge computing has brought improvements that reduce latency and unnecessary bandwidth usage by bringing processing power closer to the source where data are produced. However, due to the decentralized nature of edge computing, edge nodes are vulnerable to attacks. For this reason, some innovative solutions are needed to ensure the security of edge...

Predicting real estate prices has always been a complex task, influenced by diverse socioeconomic factors, local amenities, and the evolving urban landscape. Real estate pricing is a nuanced arena influenced by a gamut of socioeconomic elements, neighbourhood facilities, and the changing dynamics of urban spaces. Utilising the H4M dataset, which me...

Since the emergence of COVID-19, people's perspectives on various things in their surroundings and online social media have significantly changed. A few examples include articles, websites, blogs, messages, postings, news channels, and web content. The behaviour of reading the news online has gained popularity and is becoming a routine for certain...

Machine learning (ML) is an element of artificial intelligence (AI) that involves the use of algorithms and statistical models to analyse and interpret patterns in data. Thyroid disease affects millions of people worldwide, and early diagnosis and treatment are crucial for better health outcomes. ML techniques have shown great potential in predicti...

Theoretical and practical purposes are crucial to gaining knowledge about using machine learning (ML) techniques to improve prediction in an advanced way. Although momentous progress has been made in predicting accuracy using advanced tools and techniques, developers still depend on costly, time-inefficient methods to improve data prediction. This...

Breast cancer remains a formidable global health challenge, demanding innovative approaches for early detection, accurate diagnosis, and personalised treatment. This chapter seeks to leverage the power of artificial intelligence (AI) (especially deep learning) to enhance the understanding of breast cancer and transform its management landscape. The...

Breast cancer is the most prevalent type of cancer, because of which a large and disproportionate number of deaths occur every year, especially in women. Breast cancer is ranked as the world's most prevalent cancer diagnosed in women after skin cancer. It happens globally, and usually older women are at high risk, but it can start occurring after p...

Applying artificial intelligence (AI) to new fields has made AI and data science indispensable to researchers in a wide range of fields. The proliferation and successful deployment of AI algorithms are fuelling these changes, which can be seen in fields as disparate as healthcare and emerging Internet of Things (IoT) applications. Machine learning...

One of the most enticing research areas is the stock market, and projecting stock prices may help investors profit by making the best decisions at the correct time. Deep learning strategies have emerged as a critical technique in the field of the financial market. The stock market is impacted due to two aspects. The first is the geopolitical, socia...

Cloud computing technologies have gained great momentum in recent years in the academic and private sectors because of the advantages they offer such as scalability and a suitable economic model. They allow users to focus solely on application development by isolating them from time-consuming and costly tasks such as server infrastructure managemen...

Heart disease remain*ns the leading global killer, responsible for millions of deaths annually. While many efforts have been directed towards predicting heart disease using biomedical markers, a comprehensive analysis that identifies the most significant markers and leverages the latest machine learning techniques is essential for enhancing predict...

This research explores how optical interconnection networks for the telecom sector might perform better by utilising machine learning (ML) and predictive analytics. Any CPU may send point-to-point messages to other CPUs thanks to the message-passing communication method used in these networks. The effectiveness of these networks could be greatly in...

Quantum computing is a novel method of computation that uses the principles of quantum mechanics to handle highly challenging situations in a very short amount of time. Quantum technology has the ability to significantly impact worldwide advancement, even prior to the complete deployment of quantum machines. Quantum technology for communication, co...

The Internet and computer commercialization have transformed the computing systems area over the past sixty years, affecting society. Computer systems have evolved to meet diverse social needs thanks to technological advances. The Internet of Things (IoT), cloud computing, fog computing, edge computing, and other emerging paradigms provide new econ...

The Internet and computer commercialization have transformed the computing systems area over the past sixty years, affecting society. Computer systems have evolved to meet diverse social needs thanks to technological advances. The Internet of Things (IoT), cloud computing, fog computing, edge computing, and other emerging paradigms provide new econ...

Edge Artificial Intelligence (AI) incorporates a network of interconnected systems and devices that receive, cache, process, and analyze data in close communication with the location where the data is captured with AI technology. Recent advancements in AI efficiency, the widespread use of Internet of Things (IoT) devices, and the emergence of edge...

Smart resource allocation is essential for optimising cloud computing efficiency and utilisation, but it is also very challenging as traditional approaches often overprovision CPU resources, leading to financial inefficiencies. Recently developed Artificial Intelligence (AI) techniques have the potential to solve this problem efficiently; for examp...

Internet of Things (IoT) based sensor networks have been established as a pillar in intelligent communication systems for efficiently handling roadside congestion and accidents. These IoT networks sense, collect, and process data on a real‐time basis. However, IoT based sensor network clustering has various energy constraints such as inefficient ro...

Sentiment Analysis (SA) employing Natural Language Processing (NLP) is pivotal in determining the positivity and negativity of customer feedback. Although significant research in SA is focused on English texts, there is a growing demand for SA in other widely spoken languages, such as Arabic. This is predominantly due to the global reach of social...

Quantum computing is a new paradigm that will revolutionize various areas of computing, especially cloud computing. Quantum computing, still in its infancy, is a costly technology that can operate in highly isolated environments because of its rapid response to environmental factors. This makes quantum computing a challenging technology for researc...

The fog computing paradigm has generated increasing research interest because it focuses on transferring the computational process to the edge of the network near the end-user. Fog nodes, the majority of physical devices in a fog environment, are geographically distributed and heterogeneous with limited resources. Fog computing consumes a lot of en...

Sentiment analysis (SA) is a subfield of artificial intelligence that entails natural language processing. This has become increasingly significant because it discerns the emotional tone of reviews, categorising them as positive, neutral, or negative. In the highly competitive coffee industry, understanding customer sentiment and perception is para...

The diverse student body at Queen Mary University of London requires an effective approach to ensure equal opportunity in higher education. This includes promoting equality, inclusion, equity, and access to services. To address this, the authors present a case study about a redesigned cloud computing module to enhance student engagement, employabil...

The convergence of the Internet of Things (IoT) with e-health records is creating a new era of advancements in the diagnosis and treatment of disease, which is reshaping the modern landscape of healthcare. In this paper, we propose a neural networks-based smart e-health application for the prediction of Tuberculosis (TB) using serverless computing....

Serverless edge computing has emerged as a new paradigm that integrates the serverless and edge computing. By bringing processing power closer to the edge of the network, it provides advantages such as low latency by quickly processing data for time‐sensitive Internet of Things (IoT) applications. Additionally, serverless edge computing also brings...

To meet next-generation Internet of Things (IoT) application demands, edge computing moves processing power and storage closer to the network edge to minimize latency and bandwidth utilization. Edge computing is becoming increasingly popular as a result of these benefits, but it comes with challenges such as managing resources efficiently. Research...

There is a very significant knowledge gap between Artificial Intelligence (AI) and a multitude of industries that exist in today’s modern world. This is primarily attributable to the limited availability of resources and technical expertise. However, a major obstacle is that AI needs to be flexible enough to work in many different applications, uti...

The integration of serverless edge computing and the Industrial Internet of Things (IIoT), like Industry 4.0 applications, is seen as a promising development that can make industrial processes more efficient and faster. These two technologies can be integrated to optimize production by enabling faster adaptation in critical industries with variable...

Edge computing plays a crucial role in the processing of Consumer Internet of Things (IoT)-enabled latency-sensitive applications. In smart homes, dynamic action strategies based on multiple IoT objects with edge processing can be the best solution for handling adverse events. To overcome these challenges, the use of Stochastic Game Net (SGN) formi...

The massive amounts of data generated by the Industrial Internet of Things (IIoT) require considerable processing power, which increases carbon emissions and energy usage, and we need sustainable solutions to enable flexible manufacturing. Serverless computing shows potential for meeting this requirement by scaling idle containers to zero energy-ef...

Containerized edge computing emerged as a preferred platform for latency-sensitive applications requiring informed and efficient decision-making accounting for the end user and edge service providers’ interests simultaneously. Edge decision engines exploit pipelined knowledge streams to enhance performance and often fall short by employing inferior...

The advent of sixth-generation (6G) technology is poised to revolutionize connectivity, particularly by enhancing the integration of Internet of Medical Things (IoMT) devices. This advancement offers ultra-fast data transmission, low latency, and high mobility but also brings the challenge of ensuring secure and energy-efficient communication. To s...

Multi-access Edge Computing (MEC, formerly, Mobile Edge Computing) offers users of Mobile Devices (MDs) such as smartphones advantages in computational task completion times by offloading to superior but geographically close computing resources. There is a need to make these services more sustainable (energy-efficient) as an initial step towards ne...

The proliferation of ubiquitous Internet of Things (IoT) sensors and smart devices in several domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to a prodigious amount of data requiring ever-increasing computations and services from cloud to the edge of the network. Fog/Edge computing is a promising and distr...

The trend towards transitioning from monolithic applications to microservices has been widely embraced in modern distributed systems and applications. This shift has resulted in the creation of lightweight, fine-grained, and self-contained microservices. Multiple microservices can be linked together via calls and inter-dependencies to form complex...

With the development of new sensor technologies, Internet of Things (IoT)-based healthcare applications have gained momentum in recent years. However, IoT devices have limited resources, making them incapable of executing large computational operations. To solve this problem, the serverless paradigm, with its advantages such as dynamic scalability...

Day trading has been gaining attention from prospective investors over the past decades, even more so in the last decade due to a plethora of factors such as instantaneous availability and accessibility to information such as social media, news, Internet of Things (IoT), availability of market’s sentiment data associated with them, and increased br...

Every year in the United States, the 4th Thursday of November is commemorated as Thanksgiving Day. The next day which is a Friday is known as Black Friday. This day is the busiest day in terms of shopping because all major retailers and e-commerce websites offer massive amounts of discounts and deals. Hence, this sale is termed the Black Friday Sal...

The prolonged 5G network deployment includes the Internet of Things (IoT) as a technological advancement toward the expansion of wireless communication. The Internet of Everything (IoE), a superset of IoT, acts as the proliferation that accelerated the outburst of data and sparked new disciplines. Nonetheless, the foundational and crucial elements...

Over the past few years, the demand for data traffic has experienced explosive growth thanks to the increasing need to stay online. New applications of communications, such as wearable devices, autonomous systems, drones, and the Internet of Things (IoT), continue to emerge and generate even more data traffic with vastly different performance requi...

Commonsense reasoning is a basic ingredient of intelligence in humans, empowering the ability to deduce conclusions based on the observations of surroundings. Large language models (LLMs) are emerging as potent tools increasingly capable of performing human-level tasks. The recent development in the form of GPT-4 and its demonstrated success in tas...

Companies across the globe are keen on targeting potential high-value customers in an attempt to expand revenue, and this could be achieved only by understanding the customers more. Customer Lifetime Value (CLV) is the total monetary value of transactions or purchases made by a customer with the business over an intended period of time and is used...

Companies across the globe are keen on targeting potential high-value customers in an attempt to expand revenue and this could be achieved only by understanding the customers more. Customer Lifetime Value (CLV) is the total monetary value of transactions/purchases made by a customer with the business over an intended period of time and is used as m...

A wide variety of Mobile Devices (MDs) are adopted in Internet of Things (IoT) environments, resulting in a dramatic increase in the volume of task data and greenhouse gas emissions. However, due to the limited battery power and computing resources of MD, it is critical to process more data with less energy. This paper studies the Wireless Power Tr...

Fog computing is one of the most widely used paradigms for analyzing and computing the data locally, instead of sending data to remote cloud servers. The main objective of fog computing is to lower the latency of services compared to cloud systems while also reducing the requirement of network bandwidth across computing devices. But as in a fog env...

The Internet of Things (IoT) enabled wireless sensor networks (WSNs) are used to collect data from various nodes in hostile environments, but it is essential to authenticate legitimate nodes to prevent malicious attacks. Traditional authentication schemes may be vulnerable to attack, necessitating the development of more secure authentication techn...

COVID-19 was one of the deadliest and most infectious illnesses of this century. Research has been done to decrease pandemic deaths and slow its spread. COVID-19 detection investigations have utilized Chest X-ray (CXR) images with deep learning techniques due to the sensitivity in identifying pneumonic alterations. However, CXR images are not publi...

Digitalisation, accelerated by the pandemic, has brought the opportunity for companies to expand their businesses beyond their geographic location and has considerably affected networks around the world. Cloud services have a better acceptance nowadays, and it is foreseen that this industry will grow exponentially in the following years. With more...

A cyber-physical system is considered to be a collection of strongly coupled communication systems and devices that poses numerous security trials in various industrial applications including healthcare. The security and privacy of patient data is still a big concern because healthcare data is sensitive and valuable, and it is most targeted over th...

Mobile Internet services are developing rapidly for several applications based on computational ability such as augmented/virtual reality, vehicular networks, etc. The mobile terminals are enabled using mobile edge computing (MEC) for offloading the task at the edge of the cellular networks, but offloading is still a challenging issue due to the dy...

Heart disease is one of the leading causes of death worldwide, and with early detection, mortality rates can be reduced. Well-known studies have shown that the latest artificial intelligence (AI) can be used to determine the risk of heart disease. However, existing studies did not consider dynamic scalability to get the best performance from these...

Digitalisation, accelerated by the pandemic, has brought the opportunity for companies to expand their businesses beyond their geographic location and has considerably affected networks around the world. Cloud services have a better acceptance nowadays, and it is foreseen that this industry will grow exponentially in the following years. With more...

Serverless computing is an innovative method for the production and distribution of software since it does not rely on a centralised server management infrastructure. As a result of this, serverless computing is becoming more widespread. Instead, the cloud service provider must ensure that the code will execute as intended in the cloud environment....

Large-scale computing systems are becoming more popular as the need for computing power increases every year. Serverless computing has emerged as a powerful and compelling paradigm for the hosting services and applications because of the rapid shift in business application architectures for containers and microservices. Further, Serverless computin...

This book explores how advances in graphic processing units (GPUs), programmable logic devices (TPUs), and field-programmable gate arrays have altered the serverless computing landscape (FPGAs). Distributed system architectures and implementations have undergone significant changes due to the popularity of serverless computing. Making and releasing...

Artificial intelligence (AI) and machine learning have changed the nature of scientific inquiry in recent years. Of these, the development of virtual assistants has accelerated greatly in the past few years, with ChatGPT becoming a prominent AI language model. In this study, we examine the foundations, vision, research challenges of ChatGPT. This a...

Medical cyber–physical systems (MCPS) firmly integrate a network of medical objects. These systems are highly efficacious and have been progressively used in the Healthcare 4.0 to achieve continuous high-quality services. Healthcare 4.0 encompasses numerous emerging technologies and their applications have been realized in the monitoring of a varie...

A cyber-physical system is considered to be a collection of strongly coupled communication systems and devices that poses numerous security trials in various industrial applications including healthcare. The security and privacy of patient data is still a big concern because healthcare data is sensitive and valuable, and it is most targeted over th...

Microservices is a structural approach, where multiple small set of services are composed and processed independently with lightweight communication mechanism. To accomplish the end-user demand in minimum delay and cost without violating the service level agreement (SLA) constraints and overhead is a challenging issue in cloud computing. In additio...

Cloud computing is a mainstay of modern technology, offering cost-effective and scalable solutions to a variety of different problems. The massive shift of organization resource needs from local systems to cloud-based systems has greatly increased the costs incurred by cloud providers in expanding, maintaining, and supplying server, storage, networ...

Resource management in computing is a very challenging problem that involves making sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse nature of workload, and the unpredictability of fog/edge computing environments have made resource management even more challenging to be considered in the fog landscape. Recentl...

Edge-Cloud Datacenters (ECDCs) have been massively exploited by the owners of technology and industrial centers to satisfy the user demand. At the same time, the amount of energy used by these data centers is considerable. To address this challenge, Virtual machine placement of the ECDCs plays an important role; therefore, assigning Virtual Machine...