Abstract: Cloud computing is new model that permit to the clients, associations, to buy the necessary adminis-trations as indicated by our requirements. It is used to upload their data and retrieve data accordingto the needs over the internet. This model offer several services like to store data, easy and conve-nient web services, etc. In this era Cloud Application is developed the different services some arePlatform-as-a-Service (Paas), Software-as-a-Service (Saas), Infrastructures-as-a-Service (Iaas), andCloud computing improve their services day by client also demand reliable and new services forefficiency and reliability. Load Balancing be major provocation in cloud computing. Techniquecalled load balancing is used to distribute load of the data over the cloud network. It is also used tominimize the resource usage.

Abstract: Cloud computing is one of the most spectacular technological achievements of the 21st century, allowing users to access various on-demand services (e.g., storage, servers, networks, apps, and services) from anywhere. All advanced technologies such as internet of things (IoT), smart cities, smart grid, system automation, 5G, and logistics systems require services offered by cloud computing. This paper provides a complete architectural tutorial on cloud computing, focusing on various service and deployment models, architectures, inter-clouds concepts, and multiple merits of cloud computing in artificial intelligence, fog computing, edge computing, and IoT. It also discusses different quality-of-service (QoS) parameters that are helpful for the consumers to decide upon the service quality offered by any cloud provider. A comparative study of the hypervisor and container-based virtualization technologies has been discussed. Finally, simulation tools and various open research issues of cloud computing are presented, appealing for the researchers to decide on future research directions.

Abstract: Cloud computational service is one of the renowned services utilized by employees, employers, and organizations collaboratively. It is accountable for data management and processing through virtual machines and is independent of end users’ system configurations. The usage of cloud systems is very simple and easy to organize. They can easily be integrated into various storages of the cloud and incorporated into almost all available software tools such as Hadoop, Informatica, DataStage, and OBIEE for the purpose of Extraction-Transform-Load (ETL), data processing, data reporting, and other related computations. Because of this low-cost-based cloud computational service model, cloud users can utilize the software and services, the implementation environment, storage, and other on-demand resources with a pay-per-use model. Cloud contributors across this world move all these cloud-based apps, software, and large volumes of data in the form of files and databases into enormous data centers. However, the main challenge is that cloud users cannot have direct control over the data stored at these data centers. They do not even know the integrity, confidentiality, level of security, and privacy of their sensitive data. This exceptional cloud property creates several different security disputes and challenges. To address these security challenges, we propose a novel Quantum Hash-centric Cipher Policy-Attribute-based Encipherment (QH-CPABE) framework to improve the security and privacy of the cloud user’s sensitive data. In our proposed model, we used both structured and unstructured big cloud clinical data as input so that the simulated experimental results conclude that the proposal has precise, resulting in approximately 92% correctness of bit hash change and approximately 96% correctness of chaotic dynamic key production, enciphered and deciphered time as compared with conventional standards from the literature.

Abstract: Fault-tolerance methods are required to ensure high availability and high reliability in cloud computing environments. In this survey, we address fault-tolerance in the scope of cloud computing. Recently, cloud computing-based environments have presented new challenges to support fault-tolerance and opened new paths to develop novel strategies, architectures, and standards. We provide a detailed background of cloud computing to establish a comprehensive understanding of the subject, from basic to advanced. We then highlight fault-tolerance components and system-level metrics and identify the needs and applications of fault-tolerance in cloud computing. Furthermore, we discuss state-of-the-art proactive and reactive approaches to cloud computing fault-tolerance. We further structure and discuss current research efforts on cloud computing fault-tolerance architectures and frameworks. Finally, we conclude by enumerating future research directions specific to cloud computing fault-tolerance development.

Abstract: Cloud computing has been widely adopted over the years by practitioners and companies with a variety of requirements. With a strong economic appeal, cloud computing makes possible the idea of computing as a utility, in which computing resources can be consumed and paid for with the same convenience as electricity. One of the main characteristics of cloud as a service is elasticity supported by auto-scaling capabilities. The auto-scaling cloud mechanism allows adjusting resources to meet multiple demands dynamically. The elasticity service is best represented in critical web trading and transaction systems that must satisfy a certain service level agreement (SLA), such as maximum response time limits for different types of inbound requests. Nevertheless, existing cloud infrastructures maintained by different cloud enterprises often offer different cloud service costs for equivalent SLAs upon several factors. The factors might be contract types, VM types, auto-scaling configuration parameters, and incoming workload demand. Identifying a combination of parameters that results in SLA compliance directly in the system is often sophisticated, while the manual analysis is prone to errors due to the huge number of possibilities. This paper proposes the modeling of auto-scaling mechanisms in a typical cloud infrastructure using a stochastic Petri net (SPN) and the employment of a well-established adaptive search metaheuristic (GRASP) to discover critical trade-offs between performance and cost in cloud services.The proposed SPN models enable cloud designers to estimate the metrics of cloud services in accordance with each required SLA such as the best configuration, cost, system response time, and throughput.The auto-scaling SPN model was extensively validated with 95% confidence against a real test-bed scenario with 18.000 samples. A case-study of cloud services was used to investigate the viability of this method and to evaluate the adoptability of the proposed auto-scaling model in practice. On the other hand, the proposed optimization algorithm enables the identification of economic system configuration and parameterization to satisfy required SLA and budget constraints. The adoption of the metaheuristic GRASP approach and the modeling of auto-scaling mechanisms in this work can help search for the optimized-quality solution and operational management for cloud services in practice.

Abstract: Software testing is the process of identifying flaws as a programme is being run so that a client can receive software that has no defects. Testing is the methodical, step-by-step detection of various sorts of defects with the least amount of time and effort possible. Software testing is a crucial tool for evaluating the quality of software. Testing is a method used to evaluate the quality, accuracy, and completeness of generated computer software. Testing is used to check performance, safety, fault tolerance, and security in addition to discovering mistakes. The most crucial method of software quality assurance is testing, which accounts for up to 40% of the budgets of some software companies.The heterogeneous and virtual networks are the main focus of this research. Therefore, we have found that explaining cloud computing is the best strategy when conducting research. There are various tools of cloud like cloudsim (To simulate cloud & its software architecture), live migration on cloudsim (To test service migration), Green cloudsim (to test service on cloud for application on green cloud & testing as per reliability as per new green computing norms) are available for software testing and analyze their performance by collecting simulation results.

Abstract: Abstract: Cloud computing is something simple we can define as maintaining data centers and data servers and also u can access technology services by computing power, storage, and database using cloud computing technology AWS(Amazon Web Services). It is an emerged model which is already popular among almost all enterprises. It provides us the concept of ondemand services where we are using and scaling cloud resources on demand and as per demand respectively. AWS Cloud computing is a cost-effective model. The major concern in this model is Security and Storage in the cloud. This is one of the major reasons many enterprises of choosing AWS cloud computing. This paper provides a review of security research in the field of cloud security and storage services of the AWS cloud platform. After security and storage, we have presented the working of AWS (Amazon Web Service) cloud computing. AWS is the most trusted provider of cloud computing which not only provides excellent cloud security but also provides excellent cloud storage services. The main aim of this paper is to make cloud computing storage and security a core operation and not an add-on operation. As per the increase in the Service provider and related companies, this AWS Cloud Platform plays a vital role in service industries by giving its best web services, so, therefore, choosing the cloud service providers wisely is the basic need of the industry. Therefore we are going to see how AWS fulfills all these specific needs. Keywords: Trusted Computing, AWS, Information-Centric Security, Cloud Storage, S3, EC2, Cloud Computing

Abstract: Abstract Cloud computing is a new technology that is undergoing tremendous development today. People who use it are not able to separate the reasonable from the unreasonable arguments that come with the security requirements in the cloud. The claim that cloud computing is hereditarily insecure is as absurd as the claim that cloud computing does not create new security problems. Cloud computing is a way to dynamically increase resources without the need for in-depth knowledge of a brand new infrastructure, without training new workers or designing new software solutions. The article aims to analyse the different cloud security issues and models of cloud architectures. Some of the main problems with security in virtualization, concerns about storing data in the cloud and the assessment of risk tolerance in cloud computing are presented. Legal and regulatory issues for the protection of personal data are addressed.

Abstract: In recent years, cloud computing has emerged as a major change in the world of technology, whereby computing workloads are transferred first from local data centers located within companies and organizations to large cloud centers. On the horizon, a new wave of change forces the transition from cloud computing to edge computing, which is located at the borders of networks so that computation is close to the source of the processed data. This is to improve the performance and reliability of applications and services, and reduce the cost of their operation by optimizing the distance of the traveled data. In a mobile environment, we have to ask for the best technology to handle such an environment, whether it be cloud computing or edge computing. This survey will go over several papers varying from cloud computing to mobile edge computing to understand the researchers’ focus. We will see that mobility is a simple phenomenon that will help the emergence of new technologies.

Abstract: The term "cloud computing" refers to a place where we can store our important data and use pay-as-you-go computing and networking services without a physical environment. Today's cloud computing provides us with robust computing and storage, high availability and security, rapid accessibility and adaption, ensured scalability and interoperability, and cost and time efficiency. Users in a cloud environment assume that there are endless resources accessible, and they only pay for the resources they really utilize. The number of cloud service providers is growing quickly and they are adding new capabilities as technology advances. However, a cloud consumer may find it challenging to identify the best service provider for their needs. Three cloud service providers—Amazon Web Services, Google and Microsoft Azure—are explored in this study, and a comparison of these cloud service providers is provided. On the basis of service availability, price, pricing structure, data security, operating system, Windows support, free trial, and geographies, the cloud service providers were compared.

Abstract: Cloud computing complexity is growing rapidly with the advancements that it is witnessing. It has created a requirement to simplify the process of configuring cloud and re-configuring it when required, it also involves tasks like auto scaling of infrastructure, elastic computing and maintaining the health of the servers. The proposed method introduces a smart cloud management using knowledge base, which models the resources of cloud; it handles service level agreement and its evaluations. The proposed knowledge base supports representational state transfer (REST/RESTful) services to store and manipulate different cloud aspects like type of application, business configuration, and metrics value and its type; it also implements the strategy for efficient resource management for smart clouds. The proposed architecture consists of smart cloud engine (which provides autonomous services, which help to exploit cloud resources for service optimization and to perform service automation), knowledge base (KB) (provide a cloud ontology which will help in the management of resources and provides intelligence to the smart cloud), server and cloud enrolment, designated monitoring tool and moderator. The resulted module is easy to integrate with any of the existing cloud management tool or orchestrator. As It is developed using REST protocol and extensible markup language (XML) language it is also easy to integrate with existing monitoring tool or application programming interface (APIs).

Abstract: The article provides a survey on cloud platforms suitable for a virtual online laboratory, which contains Linux online environments and is intended to support the Operating Systems course.The study justifies the choice of utilizing private cloud as a deployment model and IaaS as a service model and substantiates the decision to create specially tailored cloud environments adapted for educational needs in contrast to applying ready-made IaaS (Infrastructure as a Service) cloud services given by providers. The related works on cloud platforms for teaching operating systems are analyzed. The study also makes a review of the authors' previous research on virtualization tools and environments for the Operating Systems course and Cisco CyberSecurity Operations course. The basic and additional requirements for cloud computing software for virtual online laboratory supporting Operating Systems course have been elaborated. Finally, the work makes the comparison of Eucalyptus, OpenStack, CloudStack and OpenNebula cloud platforms and substantiates the selection among these cloud computing software the platforms of the first and the second choice.

Abstract: Cloud-based data storage has grown in popularity due to its flexibility and concerns about security and confidentiality. In computer science, cloud computing is a relatively new concept. Users are using fewer resources while increasing their reliance on cloud resources. Cloud computing, mobile computing, and wireless networks are combined in Mobile Cloud Computing (MCC). On the other hand, Mobiles provide vast computational resources to mobile consumers due to their capabilities. On the other hand, cloud computing refers to data centers that are accessible via the Internet to a large number of people. The purpose of this paper is to provide an overview of cloud computing and mobile cloud computing. The study covers delivery and deployment models of cloud computing and the main features of mobile cloud computing.

Abstract: Today, cloud computing has emerged as new technology and a business model. Cloud computing is spreading everywhere on the planet because of its simplicity and easy-to-use model. Growing cloud computing services offer great opportunities for sponsors to induce the most effective and the best prices, which poses new challenges in choosing the simplest service for an outsized group. Cloud computing uses a spread of computer resources to facilitate large-scale operations. Therefore, selecting the correct node to try to do the duty can improve the performance of an outsized cloud computing site. It takes time for consumers to assemble the required information and analyze all service providers to create a call.. Load balancing is the technique used to distribute the loads among various systems to optimize performance. Load balancing ensures that nodes are neither overloaded nor underloaded. Cloud Analyst could be a tool that helps developers to simulate large-scale Cloud applications to understand the functionality of such programs under various deployment settings. The cloud analyst simulator is used to run the experiments.

Abstract: The purpose of this study is to look at Cloud Computing Security. The term “cloud computing” refers to a way of delivering services over the internet. As a network service, computing resources are made available. These services are cost-effective, scalable, and self-contained. Cloud computing is responsible for the IT industry's rapid growth. Despite its many benefits, it has a number of security concerns that must be addressed. In order to make Cloud Computing even more secure and trustworthy, some efforts must be made against the model's hazards. All of the risks linked with Cloud Computing, as well as potential cures, are evaluated in this paper. Various resources like as memory, software, CPU, and network services are offered on-demand via the internet in cloud computing. Because all resources such as hardware, software, and network are used without physically purchasing them, the company's primary investment in the cloud is retained. Many advances are being implemented in the cloud platform to deliver a better experience for cloud users.

Abstract: Cloud computing has proposed a new perspective for provisioning the large-scale computing resources by using virtualization technology and a pay-per-use cost model. Load balancing is taken into account as a vital part for parallel and distributed systems. It helps cloud computing systems by improving the general performance, better computing resources utilization, energy consumption management, enhancing the cloud services’ QoS, avoiding SLA violation and maintaining system stability through distribution, controlling and managing the system workloads. In this paper we study the necessary equirements and considerations for designing and implementing a suitable load balancer for cloud environments. In addition we represent a complete survey of current proposed cloud load balancing solutions which according to our classification, They can be classified into three categories: General Algorithm-based, Architectural-based and Artificial Intelligence-based load balancing mechanisms. Finally, we propose our evaluation of these solutions based on Suitable metrics and discuss their pros and cons. Index Terms—Cloud Computing, Load Balancing, Distributed Systems, Virtual Machine.

Abstract: The rapid development of mobile device applications put tremendous pressure on edge nodes with limited computing capabilities, which may cause poor user experience. To solve this problem, collaborative cloud-edge computing is proposed. In the cloud-edge computing, an edge node with limited local resources can rent more resources from a cloud node. According to the nature of cloud service, cloud service can be divided into private cloud and public cloud. In a private cloud environment, the edge node must allocate resources between the cloud node and the edge node. In a public cloud environment, since public cloud service providers offer various pricing modes for users' different computing demands, the edge node also must select the appropriate pricing mode of cloud service; which is a sequential decision problem. In this stydy, we model it as a Markov decision process and parameterized action Markov decision process, and we propose a resource allocation algorithm cost efficient resource allocation with private cloud (CERAI) and cost efficient resource allocation with public cloud (CERAU) in the collaborative cloud-edge environment based on the deep reinforcement learning algorithm deep deterministic policy gradient and P-DQN. Next, we evaluated CERAI and CERAU against three typical resource allocation algorithms based on synthetic and real data of Google datasets. The experimental results demonstrate that CERAI and CERAU can effectively reduce the long-term operating cost of collaborative cloud-side computing in various demanding settings. Our analysis can provide some useful insights for enterprises to design the resource allocation strategy in the collaborative cloud-side computing system.

Abstract: Consider an analogy where personal computer users are not required to run, install or store their applications on their personal computers. Consider a situation where every piece of your information and data may be stored on the cloud (Internet). As an allegory for the Internet, cloud is a very popular word but when integrated with the word “computing,” it becomes more important and uncertain. Cloud computing comes into focus only when users think about what they always need, which leads to the concept of an updated version of utility computing. The advancement of cloud computing came about because of the quickly developing utilization of the web among the general population. Cloud computing is anything but an absolutely new innovation; it's actually a voyage through distributed, cluster, grid and presently cloud computing. Before the increasing utilization of the web everywhere throughout the globe, cloud computing had just been used in the IT business. Cloud computing is transforming the computing landscape. The cloud concept and its computing process is an emerging topic in internet-centric and IT-market-oriented businesses. The goal required for the IT industry should be a direct conversation about how this new computing worldview will put an effect the associations, how it can be utilized with the current advancements. Cloud computing needs a third-party vendor through which a client or an end user or a customer may use the cloud provided by a cloud service provider (CSP) on demand.

Abstract: In the IT industry, we are now in the era of Cloud Computing Technology. Cloud computing, which is based on the Internet, has the most powerful computation architecture. It is made up of a collection of connected and integrated hardware, software, and internet infrastructure. It has a number of features atop grid computing and other types of computing. In this work, I provide a summary of cloud computing evaluations based on a review of more than 30 cloud computing articles. The outcome of this study represents the state of the IT industry before and after cloud computing. Cloud computing is defined as the provision of resources such as network, storage, and servers on demand or on a pay-per-use basis over the internet. Although cloud computing is assisting the Information Technology business, there is still a need for more study and development in this area. In this work, we have contributed an advanced overview focused on the cloud computing idea and the most advanced research issues.

Abstract: Cloud computing is gaining popularity among small and medium-sized enterprises. The cost of cloud resources plays a significant role for these companies and this is why cloud resource optimization has become a very important issue. Numerous methods have been proposed to optimize cloud computing resources according to actual demand and to reduce the cost of cloud services. Such approaches mostly focus on a single factor (i.e., compute power) optimization, but this can yield unsatisfactory results in real-world cloud workloads which are multi-factor, dynamic and irregular. This article presents a novel approach which uses anomaly detection, machine learning and particle swarm optimization to achieve a cost-optimal cloud resource configuration. It is a complete solution which works in a closed loop without the need for external supervision or initialization, builds knowledge about the usage patterns of the system being optimized and filters out anomalous situations on the fly. Our solution can adapt to changes in both system load and the cloud provider’s pricing plan. It was tested in Microsoft’s cloud environment Azure using data collected from a real-life system. Experiments demonstrate that over a period of 10 months, a cost reduction of 85 percent was achieved.

Abstract: Cloud computing is a new standard for large-scale distributed and parallel computing that is still in its infancy. At a predetermined time, provides common resources, information, software packages, and other resources in accordance with client requirements. As cloud computing becomes more popular and more people become interested in assistive computing, better and quicker service is necessary. It is necessary to enhance the management of the good load balancing solutions that are already accessible. Recently, numerous clients from all over the world have been seeking various services at a quick rate, negatively impacting cloud computing performance. The various load balancing techniques used in cloud computing are effective in customizing demand by identifying the appropriate virtual machines. In this review, a comparative study will be done between many load balancing algorithms in different cloud computing, as many studies have been done on this important topic. Important research will also be analyzed and defined, and analyzes will be written for each research that talks about dynamic and non-dynamic load balancing techniques and algorithms. Many details will also be mentioned from the researcher's point of view as a summary of each research.

Abstract: Cloud computing is the use of a virtual repository of resources dispersed throughout the Internet. It is a development of computer technology that is based on the Internet. Depending on their demands, several levels of users can access cloud computing services. However, data security on the Internet is the most crucial concern for cloud computing. Confidentiality, security, anonymity, and authenticity are common problems experienced by both cloud service providers and customers. Cloud service users do not have complete access to or control over these services. However, the cloud service provider must guarantee that the client’s login information is safe. To strengthen cloud security, we were able to recognize and look at a wide range of encryption problems. A hybrid framework for cloud computing security is taken into consideration based on these techniques.

Abstract: ABSTRACT Cloud computing is one of the rapidly growing technologies in computing. It includes many benefits such as improved reliability, enormous scalability, decreased costs, portability, enhanced geographic coverage with fastest time, less infrastructure investment though it has challenges such as data security, insufficient resources, skill, etc. For past few years, cloud computing has grown considerably in information technology. Safety of information is a great concern as enormous information of individuals and companies was being stored in cloud. Many software giants such as Microsoft joined hands to build cloud services. The growth of cloud computing had been affected by data security issues, which leads to complexity with data privacy and protection. The objective of this work is to study and analyze the security issues in cloud computing. The security issues pertaining to network, data, application, storage, and information in cloud domain with the algorithms and tools deployed were addressed and reviewed elaborately.

Abstract: In this chapter, an overview of cloud computing is presented. We try to define the term, describe its main characteristics, outline the types of services provided by cloud technology, and detail how it is related to new concepts such as edge and fog computing. To this end, we check various definitions presented by companies, academics, and analyst firms and study the historical evolution of cloud computing. Cloud computing describes a model for on-demand delivery of computing power based on pay-per-use business models. Virtualization and dynamic scalability on demand are the main features of the cloud. Here, software, platform, and infrastructure are often provided in as a service manner, for which multitenancy and resource pooling, on-demand usage, elasticity, broad network access, measured usage, and resiliency are the main common characteristics. Infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) are three constitutive layers of a cloud. There are four deployment models for cloud computing: public, private, hybrid, and community. In this chapter, the main advantages and disadvantages of this technology are given, and the motivations of organizations for acquiring cloud computing services are discussed. Finally, the relationship between cloud computing and several close technologies such as grid, edge, and fog computing are presented and discussed.

Abstract: Cloud computing is a new computing model that allows businesses to adopt IT without making a large upfront commitment. Despite the potential benefits of the internet, model security remains a concern, which has a negative influence on cloud adoption. The security challenge gets more difficult under the data center, as additional dimensions such as model design, multitenancy, elasticity, and the layers dependency stack have been added to the problem scope. We present a thorough examination of the cloud security challenge in this article. We looked at the issue from the standpoints of network infrastructure, cloud-provided features, cloud consumers, and cloud service delivery methods. We develop a thorough characterization of the data protection challenge and essential aspects that any suggested security solution should address based on this research. Cloud computing is a fast-expanding field of research that depends on spreading computing power instead of using a dedicated server or smart devices to run programmers. The majority of the growth in this sector is attributable to the transition from a standard IT subscription model to a unique cloud model, as well as the widespread availability of electronic and digital gadgets. Cloud computing offered a significant danger and difficulty for information system projects, but it also provided them with several possibilities to improve their data processing. Furthermore, cloud users and consumers have yet to develop appropriate forensic abilities to aid in the detection of illegal activity in the cloud. Although the cloud offers some potential technological and economic benefits, consumers continue to be hesitant to adopt it, mostly owing to security concerns and the difficulty of conducting cloud proper investigation. Some study has been done in this area, and strategies for conducting forensic investigations have been proposed. In this research paper, we begin by analyzing the intrusion detection progress made by other academics, and then we analyze and evaluate our conclusions in order to assess the potential and difficulties that cloud forensics face based on these findings.

Abstract: Cloud computing provides computing resources, platforms, and applications as a service in a flexible, cost-effective, and efficient way. Cloud computing has integrated with industry and many other fields in recent years, which prompted researchers to look into new technologies. Cloud users have moved their applications, data and services to the Cloud storage due to the availability and scalability of Cloud services. Cloud services and applications are provided through the Internet-based on a pay-per-use model. Plenty of security issues are created due to the migration from local to remote computing for both Cloud users and providers. This paper discusses an overview of Cloud computing, as well as a study of security issues at various levels of Cloud computing. The article also provides a complete review of security issues with their existing solutions for a better understanding of specific open research issues.

Abstract: Cloud Computing means a place where we can store our valuable information of data and access the computing and networking services following the pay-as-you-go method without a physical environment. In the present day, cloud computing offers us powerful computing and storage, high availability and security, instant accessibility and adaptation, guaranteed scalability and interoperability, and cost and time effectiveness. Cloud computing has three platforms (IaaS, PaaS, SaaS) with exclusive features which assure to make easy their work for a client, Organization or Trade to build up any kind of IT business. In this paper, we managed a comparison of cloud service features and after the comparison, It's simple to select a certain cloud service from the available features by comparison with three selective cloud providers like Amazon, Microsoft Azure and Digital Ocean. Using the result of this survey to not only find the similarities and differences between various elements of cloud computing but also to propose some topics to look into for further research.

Abstract: Cloud computing is a new and advanced viewpoint for large-scale parallel and distributed computing systems. Cloud computing is growing quickly, and users are demanding more services and better results, so cloud-computing load balancing has become a very thought-provoking and important research area. Load on the cloud is growing extremely with the expansion of new applications. Load balancing is a major area of the cloud computing environment, which guarantees that all connected devices or processors simultaneously perform the same amount of work. Hence, an efficient load-balancing scheme is needed to improve the performance of cloud computing. Different researchers in the past years have proposed several load-balancing algorithms. This paper examines the important necessities and concerns for designing and implementing a suitable load balancer for cloud environments. In addition, we constitute an entire survey of recently proposed cloud load balancing solutions; finally, we propose evaluating these solutions based on suitable metrics and discuss their advantages and disadvantages.