Showing papers on "Software as a service published in 2022"

Investigating the use of an Artificial Intelligence Model in an ERP Cloud-Based System

Abstract: Enterprise Resource Planning (ERP) systems are necessary to improve an enterprise's management performance. However, the perception of information technology (IT) professionals about the integration of artificial intelligence (AI) and machine learning with ERP cloud service platforms is unknown. Few studies have examined how leaders can implement AI for strategic management, but no study has qualitatively explored AIs integration in the cloud ERP system. This qualitative phenomenological study explored IT professionals’ perceptions regarding the integration of AI and Supervised-machine (S-machine) learning into cloud service platforms in the enhancement of the cloud ERP system. Two research questions were developed for this study: 1) What are the perceptions of IT professionals regarding the use of an AI model to integrate SaaS and ERP? and 2) What are the perceptions of IT professionals regarding how AI can be integrated in order to enhance the security of using an ERP cloud-based system? Through a hermeneutical lens and a focus on integrating the Application Programming Interface (API), purposive sampling was used to interview five AI experts, three Machine Learning (ML) experts, five Cybersecurity experts, and two Cloud Service Providers provided their lived experiences with AI and S-machine learning. Five main themes emerged, including 1) use of an AI model to integrate SaaS and ERP helped perform work efficiently, 2) challenges for integrating AI into cloud service ERP and SaaS, 3) resources needed to fully implement an AI into cloud-service ERP or SaaS, 4) the best practices for developing and implementing an AI model for ERP and SaaS, and 5) how security of an ERP clouds-based system is optimized by integrating AI. The culmination of these findings has positive implications for individuals and organizations to improve management performance. While this study does not proposal a new theory, this study extends current literature on the application of theories related to technology integration.

Interference-Aware SaaS User Allocation Game for Edge Computing

Abstract: Edge Computing, extending cloud computing, has emerged as a prospective computing paradigm. It allows a SaaS (Software-as-a-Service) vendor to allocate its users to nearby edge servers to minimize network latency and energy consumption on their devices. From the SaaS vendor’s perspective, a cost-effective SaaS user allocation (SUA) aims to allocate maximum SaaS users on minimum edge servers. However, the allocation of excessive SaaS users to an edge server may result in severe interference and consequently impact SaaS users’ data rates. In this article, we formally model this problem and prove that finding the optimal solution to this problem is NP-hard. Thus, we propose ISUAGame, a game-theoretic approach that formulates the interference-aware SUA (ISUA) problem as a potential game. We analyze the game and show that it admits a Nash equilibrium. Then, we design a novel decentralized algorithm for finding a Nash equilibrium in the game as a solution to the ISUA problem. The performance of this algorithm is theoretically analyzed and experimentally evaluated. The results show that the ISUA problem can be solved effectively and efficiently.

Agile logic for SaaS implementation: Capitalizing on marketing automation software in a start-up

Abstract: The emergence of Software-as-a-Service (SaaS) has facilitated agile technology implementation that focuses on iterative adaptations via learning by doing rather than the realization of a predesigned implementation plan. This study conceptualizes such an agile approach and explicates its operationalization via a four-year qualitative case study of a business-to-business (B2B) start-up firm’s implementation of a HubSpot marketing automation (MA) SaaS. The study shows how agile implementation continuously introduces adaptations to SaaS features and organizational routines for improving their mutual fit given the organization’s goals. The study also contributes to theory by offering a novel framework for managing agile implementation processes. The findings identify the key processes of sales lead management, content marketing, and customer intelligence through which start-up firms may capitalize on MA software.

The cloud, platforms, and digital twins—Enablers of the digital supply chain

Abstract: The continued advancement of computing and digital technologies is transforming markets, economics, businesses, and society. We discuss the characteristics and applications of three important developments that are generating transformative change in the management of supply chains and business operations—Cloud-based systems, Digital Platforms, and Digital Twins. The cloud provides computer resources and computing services via the Internet. It has changed the economics of IT, enabling easy access to vast computing resources and the elastic scalability of IT solutions to match demand. Migration to the cloud is strongly affecting corporate IT strategies. Rapid developments in Software-as-a-Service (SaaS) include Enterprise Resource Planning applications offered through various modes of cloud delivery. Digital platforms have changed the nature of markets in many sectors, most notably across the retail economy. As well as facilitating commercial transactions, digital platforms can also nurture business ecosystems that support product and service innovation. Cloud Manufacturing offers the potential to deliver Manufacturing-as-a-Service (MaaS) through a platform. Digital Twins encompass a range of emerging technologies that capture the characteristics of a system, with dynamic exchange of information between the system and its digital representation. We define Digital Supply Chain Twins and discuss their potential to improve supply chain resilience.

Software-as-a-Service Security Challenges and Best Practices: A Multivocal Literature Review

Abstract: Cloud computing (CC) is the delivery of computing services on demand and is charged using a “pay per you use” policy. Of the multiple services offered by CC, SaaS is the most popular and widely adapted service platform and is used by billions of organizations due to its wide range of benefits. However, security is a key challenge and obstacle in cloud adoption and therefore needs to be addressed. Researchers and practitioners (R&P) have discussed various security challenges for SaaS along with possible solutions. However, no research study exists that systematically accumulates and analyzes the security challenges and solutions. To fill this gap and provide the state-of-the-art (SOTA) picture of SaaS security, this study provides a comprehensive multivocal literature review (MVLR), including SaaS security issues/challenges and best practices for mitigating these security issues. We identified SaaS security issues/challenges and best practices from the formal literature (FL) as well as the grey literature (GL) to evaluate whether R&P is on the same page or if controversies exist. A total of 93 primary studies were identified, of which 58 are from the FL and 35 belong to the GL. The studies are from the last ten years, from 2010 to 2021. The selected studies were evaluated and analyzed to identify the key security issues faced by SaaS computing and to be aware of the best practices suggested by R&P to improve SaaS security. This MVLR will assist SaaS users to identify the many areas in which additional research and development in SaaS security is required. According to our study findings, data breaches/leakage, identity and access management, governance and regulatory compliance/SLA compliance, and malicious insiders are the key security challenges with the maximum frequency of occurrence in both FL and GL. On the other hand, R&P agree that up-to-date security controls/standards, the use of strong encryption techniques, regulatory compliance/SLA compliance, and multifactor authentication are the most important solutions.

Green Cloud? An Empirical Analysis of Cloud Computing and Energy Efficiency

Abstract: The rapid, widespread adoption of cloud computing over the last decade has sparked debates on its environmental impacts. Given that cloud computing alters the dynamics of energy consumption between service providers and users, a complete understanding of the environmental impacts of cloud computing requires an investigation of its impact on the user side, which can be weighed against its impact on the vendor side. Drawing on production theory and using a stochastic frontier analysis, this study examines the impact of cloud computing on users’ energy efficiency. To this end, we develop a novel industry-level measure of cloud computing based on cloud-based information technology (IT) services. Using U.S. economy-wide data from 57 industries during 1997–2017, our findings suggest that cloud-based IT services improve users’ energy efficiency. This effect is found to be significant only after 2006, when cloud computing started to be commercialized, and becomes even stronger after 2010. Moreover, we find heterogeneous impacts of cloud computing, depending on the cloud service models, energy types, and internal IT hardware intensity, which jointly assist in teasing out the underlying mechanisms. Although software-as-a-service (SaaS) is significantly associated with both electric and nonelectric energy efficiency improvement across all industries, infrastructure-as-a-service (IaaS) is positively associated only with electric energy efficiency for industries with high IT hardware intensity. To illuminate the mechanisms more clearly, we conduct a firm-level survey analysis, which demonstrates that SaaS confers operational benefits by facilitating energy-efficient production, whereas the primary role of IaaS is to mitigate the energy consumption of internal IT equipment and infrastructure. According to our industry-level analysis, the total user-side energy cost savings from cloud computing in the overall U.S. economy are estimated to be USD 2.8–12.6 billion in 2017 alone, equivalent to a reduction in electricity use by 31.8–143.8 billion kilowatt-hours. This estimate exceeds the total energy expenditure in the cloud service vendor industries and is comparable to the total electricity consumption in U.S. data centers. This paper was accepted by Chris Forman, information systems.

Data Processing in Cloud Computing Model on the Example of Salesforce Cloud

Abstract: Data processing is integrated with every aspect of operation enterprises—from accounting to marketing and communication internal and control of production processes. The best place to store the information is a properly prepared data center. There are a lot of providers of cloud computing and methods of data storage and processing. Every business must do the right thing, which is to think over how the data at your disposal are to be managed. The main purpose of this paper is research and the comparison of available methods of data processing and storage outside the enterprise in the cloud computing model. The cloud in SaaS (software as a service) model—Salesforce.com and a free platform development offered by Salesforce.com—force.com were used to perform the research. The paper presents the analysis results of available methods of processing and storing data outside the enterprise in the cloud computing model on the example of Salesforce cloud. Salesforce.com offers several benefits, but each service provider offers different services, systems, products, and forms of data protection. The choice of customer depends on individual needs and business plans for the future. A comparison of available methods of data processing and storage outside the enterprise in the cloud computing model was presented. On the basis of collected results, it was determined for what purposes the data processing methods available on the platform are suitable and how they can meet the needs of enterprises.

SaaS Platform for Blockchain Based E-Document Authentication applications

Abstract: Technological developments are increasingly sophisticated where every day, these developments have directions and goals to make it easier for humans in all things. In society 5.0, technology is judged not only by its intelligence but also by its benefits in helping humans. In a company, documents are precious objects, so that various things are very concerning, such as ratification, storage, and sharing of documents. 2 (two) problems were identified, namely that many companies still use the manual method where documents must be printed to be ratified by meeting directly and conventionally storing printed documents, so it is considered ineffective and efficient. These problems can be overcome with a Software as a Service (SaaS)-based digital signature system with distributed Blockchain support, making it easier for companies to validate and store documents. By using the SDLC waterfall development method and six literature studies. Researchers hope that digital signatures make it easier for everyone to validate digitally without having to print documents and do not need to think about the validity of the digital documents so that they can be considered effective and efficient to facilitate work.

Managing Software‐as‐a‐Service: Pricing and operations

Abstract: Software-as-a-service (SaaS) applications have experienced a decade of explosive growth, eliminating barriers in reaching users and enabling real-time interchanges and intelligence. Using business analytics, SaaS applications are increasingly embedded in the day-to-day activities of businesses and consumers with competition and innovative pricing. Due to the evolution in cloud business models, new issues are surfacing to challenge practitioners and scholars. A number of issues encountered in the practice have not been properly addressed or even recognized. In this paper, we attempt to fill this important gap. We propose a framework of recent business research on SaaS in light of wide adoption of the SaaS business model. This framework broadly classifies SaaS research into two basic themes. For each theme, we review past work that has been instrumental in setting the direction of this line of research and discuss how emerging research opportunities can be addressed. For each research opportunity, we also propose an initial model and the applicable methodology. Further, in order to aid researchers, we identify the data sources wherever applicable, and even present some of the initial results. We conclude by describing promising directions on a roadmap for future research and explain why an integrative perspective of operations, marketing, and information systems is critical to SaaS. In this paper, we bridge the gap between research and practice by identifying the relevant industry problems that would help researchers who are interested in working in this area both to get a starting point and to address important theoretical and practical challenges.

Fast Multi-Criteria Service Selection for Multi-User Composite Applications

Abstract: As cloud computing becomes the prevailing aspect of software engineering, paradigms such as Service-Based Systems (SBSs) or Software as a Service (SaaS) are coming into focus. They are based on cloud services responding to numerous client requests. Selecting the actual service instance for request can be an issue, if requirements for multiple Quality of Service (QoS) attributes need to be satisfied for many users simultaneously. The problem becomes more complex if we take into account the compositeness of users applications, consisting of many tasks, where QoS properties are calculated over the whole composition. The existing approaches for this problem lack either efficiency or generality. In this paper, we propose a fast heuristic method for multi-criteria service selection, designed for multi-user composite workflows with the goal of satisfying all, or as many as possible, of the given QoS requirements. The proposed method reduces the problem to several independent transportation problems, using a global-aware utility cost based on expected compositional QoS, and iterative solution improvements. Apart from being more general than the existing approaches, the proposed method turns out to be more efficient than the alternatives (up to 5x faster), as shown by extensive experiments covering both special and more general cases.

Scalability resilience framework using application-level fault injection for cloud-based software services

Abstract: Abstract This paper presents an investigation into the effect of faults on the scalability resilience of cloud-based software services. The study introduces an experimental framework using the Application-Level Fault Injection (ALFI) to investigate how the faults at the application level affect the scalability resilience and behaviour of cloud-based software services. Previous studies on scalability analysis of cloud-based software services provide a baseline of the scalability behaviour of such services, allowing to conduct in-depth scalability investigation of these services. Experimental analysis on the EC2 cloud using a real-world cloud-based software service is used to demonstrate the framework, considering delay latency of software faults with two varied settings and two demand scenarios. The experimental approach is explained in detail. Here we simulate delay latency injection with two different times, 800 and 1600 ms, and compare the results with the baseline data. The results show that the proposed approach allows a fair assessment of the fault scenario’s impact on the cloud software service’s scalability resilience. We explain the use of the methodology to determine the impact of injected faults on the scalability behaviour and resilience of cloud-based software services.

The influence of dependability in cloud computing adoption

Abstract: Abstract Cloud computing (CC) has many benefits, so its use has spread rapidly, particularly in the business sector. An important consideration in the acceptance of CC is whether the CC system is dependable, and it can differ among industry and service type. However, little research has considered the effect of dependability (composed of availability , reliability , security , maintainability ) on CC acceptance. Especially, group comparisons between high IT-intensive (Hi-ITi) and low IT-intensive (Lo-ITi) industries have not been reported, nor have comparisons between software-as-a-service (SaaS) and platform-as-a-service (PaaS)/infrastructure-as-a-service (IaaS). This study aims to explore how the dependability of CC affects users’ intent to accept it, with focus on how this intent is affected by intensity of IT use (by industry) and by the type of CC service used. To validate the proposed model, this study applied structural equation modeling and conducted multi-group analysis. A total of 230 business managers in South Korea represent the sample for our study. For the full dataset , the three dependability attributes ( availability , reliability , security ) do not affect the usefulness of CC, but do affect the ease of use of CC. The usefulness of CC is a determinant for positive intention to accept CC, whereas the ease of use of CC is not. Maintainability is the strongest determinant of CC adoption for the full dataset, and for all individual groups, except those that use SaaS. For Hi-ITi and Lo-ITi industries, results show that managers show no differences in their perceptions of the effect of dependability attributes ( availability , reliability , security ) on the usefulness and the ease of CC. The absence of such a difference in managers’ perception also applies to the relationship between two core variables of TAM (i.e., perceived usefulness , perceived ease of use ) and behavioral intention to accept CC. For SaaS and PaaS/IaaS, managers have different perceptions of security on the usefulness of CC, and the effect of the usefulness of CC on the intention to accept CC. The findings can provide academic researchers and industry practitioners with a differentiated and in-depth perspective on the understanding and the spread of CC.

Autoscaling Pods on an On-Premise Kubernetes Infrastructure QoS-Aware

Abstract: Cloud systems and microservices are becoming powerful tools for businesses. The evidence of the advantages of offering infrastructure, hardware or software as a service (IaaS, PaaS, SaaS) is overwhelming. Microservices and decoupled applications are increasingly popular. These architectures, based on containers, have facilitated the efficient development of complex SaaS applications. A big challenge is to manage and design microservices with a massive range of different facilities, from processing and data storage to computing predictive and prescriptive analytics. Computing providers are mainly based on data centers formed of massive and heterogeneous virtualized systems, which are continuously growing and diversifying over time. Moreover, these systems require integrating into current systems while meeting the Quality of Service (QoS) constraints. The primary purpose of this work is to present an on-premise architecture based on Kubernetes and Docker containers aimed at improving QoS regarding resource usage and service level objectives (SLOs). The main contribution of this proposal is its dynamic autoscaling capabilities to adjust system resources to the current workload while improving QoS.

InteliRank: A Four-Pronged Agent for the Intelligent Ranking of Cloud Services Based on End-Users’ Feedback

Abstract: Cloud Computing (CC) provides a combination of technologies that allows the user to use the most resources in the least amount of time and with the least amount of money. CC semantics play a critical role in ranking heterogeneous data by using the properties of different cloud services and then achieving the optimal cloud service. Regardless of the efforts made to enable simple access to this CC innovation, in the presence of various organizations delivering comparative services at varying cost and execution levels, it is far more difficult to identify the ideal cloud service based on the user’s requirements. In this research, we propose a Cloud-Services-Ranking Agent (CSRA) for analyzing cloud services using end-users’ feedback, including Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and Software as a Service (SaaS), based on ontology mapping and selecting the optimal service. The proposed CSRA possesses Machine-Learning (ML) techniques for ranking cloud services using parameters such as availability, security, reliability, and cost. Here, the Quality of Web Service (QWS) dataset is used, which has seven major cloud services categories, ranked from 0–6, to extract the required persuasive features through Sequential Minimal Optimization Regression (SMOreg). The classification outcomes through SMOreg are capable and demonstrate a general accuracy of around 98.71% in identifying optimum cloud services through the identified parameters. The main advantage of SMOreg is that the amount of memory required for SMO is linear. The findings show that our improved model in terms of precision outperforms prevailing techniques such as Multilayer Perceptron (MLP) and Linear Regression (LR).

The Patient Acceptable Symptom State as a Predictor of the Sports Activity Available State After Arthroscopic Rotator Cuff Repair

Abstract: Background: The patient acceptable symptom state (PASS) has emerged as a metric for evaluating patient satisfaction after treatment. There is little research on the relationship between sports activity and PASS values after arthroscopic rotator cuff repair (ARCR). Purpose: To (1) introduce the sports activity available state (SAAS) as an indicator of whether sports activities are possible based on patient symptoms after ARCR, (2) investigate the correlation between the SAAS and PASS, (3) predict the SAAS using derived PASS values, and (4) identify factors for achieving the PASS and SAAS. Study Design: Case-control study; Level of evidence, 3. Methods: Included were 201 patients who underwent ARCR between January 2015 and December 2016. At a mean follow-up of 38.7 ± 7.0 months, anchor questions were used to classify patients as SAAS+ (sports group) or SAAS– (nonsports group) and derive the PASS values for the pain visual analog scale (pVAS), American Shoulder and Elbow Surgeons (ASES), and Single Assessment Numeric Evaluation (SANE). The authors analyzed the correlation and difference between PASS and SAAS acquisition, and univariate and multivariate logistic regression analyses were performed to determine factors for PASS and SAAS achievement. Results: The final PASS values for the pVAS, ASES, and SANE were 0.5, 93.5, and 82.5, respectively. A significant correlation existed between PASS and SAAS acquisition (phi correlation coefficient, 0.647; P < .001). Sensitivity and specificity were >0.7 for all outcome scores when predicting SAAS using PASS values. A higher preoperative ASES score was significantly associated with achieving both the SAAS (OR, 1.032 [95% CI, 1.005-1.059]; P = .018) and PASS (OR, 2.556 [95% CI, 1.753-3.726]; P < .001). Diabetes (OR, 0.348 [95% CI, 0.130-0.931], P = .036) and a large to massive tear (OR, 0.378 [95% CI, 0.162-0.884]; P = .025) were significantly negatively associated with achieving the SAAS. Conclusion: The authors found the SAAS to be significantly correlated with the PASS. Also, SAAS was able to be predicted using the PASS value. Patients with higher preoperative ASES scores had higher odds of achieving both the PASS and SAAS, and patients with diabetes and those with large to massive tears had lower odds of achieving the SAAS.

Evaluating and Ranking Cloud IaaS, PaaS and SaaS Models Based on Functional and Non-Functional Key Performance Indicators

Abstract: With the recent maturity of Cloud computing technology and the flexibility of the Cloud services, the offering of Cloud services has spread exponentially. Different Cloud service providers offer their services highlighting different features of their services. Because of the diversity of Cloud services and their highlighted features, the choice of the most suitable Cloud service is a complex problem for the Cloud users. Many Cloud users are unable to identify the Cloud services that best suit their needs and thus choose an unsuitable Cloud service, which results in financial loses as well as time delays. To this end, in this study, we propose an efficient three layered framework for evaluating and ranking IaaS, PaaS and SaaS Cloud services. We identified the functional and non-functional key performance indicators (KPIs) for Cloud services from 6 KPI classes. We classified these KPIs with respect to their types and criticality so that the Cloud user can easily choose according to his needs. The relative importance of the KPIs was determined using CRITIC method. We combined the KPIs values and their relative importance for an overall evaluation and ranking of the Cloud services using Vikor method. A case study is also presented for a step by step demonstration of the proposed method.

Relacional: Easing the Crisis Effects in the Education Sector

Abstract: This teaching case addresses the need for change in Relacional’s business strategy, driven by the negative effects of the COVID-19 pandemic in the Brazilian educational sector in the first half of 2020. The startup is a software warehouse whose systems seek to solve specific problems of educational institutions, from basic to higher level, such as relationship, attraction, and retention of students. In the midst of a scenario of probable crisis in the sector, the partners seek business alternatives to assist educational institutions while wanting to ensure the growth and continuity of the company itself. Applicable in Entrepreneurship, Marketing, and IT courses in undergraduate and graduate Business Management programs, this case addresses concepts of Information Economy, models of offer and pricing of software.

Analysis of Different SaaS Architectures from a Trust Service Provider Perspective

Abstract: The topic of cloud computing is becoming of extreme interest for trust service providers willing to move their services from a desktop-oriented approach into a more interconnected, mobile world. In our paper, we investigate and present from this perspective, several architectures that are currently available on the commercial market. The analysis covers some of the well-known commercial cloud platforms available: Amazon Web Services, Google Cloud Platform, IBM Cloud, Microsoft Azure, and Oracle Cloud. We have analyzed and identified several advantages associated with the use of these commercially available platforms with the objective of pondering the potential use of the Software-as-a-Service (SaaS) approach within an innovative Digital Enterprise making use of the traditional services of a trust service provider (including here digital signatures, digital notary, time stamping, etc.) The analysis of the above-mentioned commercial platforms is not only addressing their own intrinsic SaaS architectures but also the derived or personalized architectures that are provided for their tenants and clients.

Converting free users to paid subscribers in the SaaS context– the impact of marketing touchpoints, message content, and usage

Abstract: As software-as-a-service (SaaS) becomes an increasingly popular business model, free-trial acquisition, which allows prospective consumers to explore the service at no charge, also becomes a norm for SaaS companies. However, empirical research on the role of marketing communications, consumers’ free-trial usage, and their interactions is still lacking. This study utilizes the granular data from a leading SaaS firm that provides prospects with free trials and examines the impact of and interactions among various marketing touchpoints, different types of message content, and the frequency and variety of free-trial usage on consumers’ subscription decisions. Regarding advertising effectiveness, this study finds that consumer-initiated touchpoints with all message content enhance conversion, but the firm-initiated touchpoints conveying persuasive messages discourage conversion. Meanwhile, free-trial usage does not always follow the old adage “the more, the merrier.” When usage is unpacked as frequency and variety, more frequent free-trial usage encourages conversion, but exploring a greater variety of software leads to a lower conversion rate. For the focal firm, advertising and free-trial usage attenuate each other in leading to conversion, except for the persuasive messages sent to frequent users and featured messages to variety-seeking users. The robustness of these findings is tested, and two simulations demonstrate how the model helps firms determine when to contact consumers with additional display ads or emails. This research provides guidance to SaaS managers on the impact of advertising, free-trial usage, and the interplay between both on conversion, which facilitates decisions on marketing strategies and resource allocations.

Platform Provider Roles in Innovation in Software Service Ecosystems

Abstract: Following a new innovation strategy, software vendors move their software onto their software service platforms and open up their platforms to third-party software service vendors. Although many studies state that enlarging the scope of software service offerings is the goal of the platform providers, only a few studies have focused on the roles that the platform providers take on to achieve the goal. These studies identified that the platform providers not only manage the platform but also promote and regulate third-party software. In this article, we extend this research by analyzing the activities of how platform providers promote innovation. For the analysis, we use empirical data about software services gathered from AppExchange of Salesforce. The analysis identifies the clusters and positions of software services of Salesforce and third-party vendors in the software service network. Our analysis results show that Salesforce promotes innovation by provisioning software services that are in core positions or that are bridges between service clusters. Third-party vendors release software services that are complementary to those of Salesforce. Overall, the results suggest that platform providers need to position strategically their software services to build successful software ecosystems, and that research on innovation needs to analyze the roles and efforts of the platform providers in detail.

Cloud Computing and Its Impact on Industry 4.0

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.

Cloud Attacks and Defence Mechanism for SaaS: A Survey

Abstract: Cloud computing systems are the de-facto deployments for any user data and processing requirements. Due to a wide variety of cloud systems available today, increase in the number of services provided by these systems. These services range from software-based systems to high-end hardware-based infrastructures. The wide variety attracts a lot of attention by unwanted hackers, due to which the cloud deployments are one of the most cyber attacked entities here, we review the attacks and issues of cloud computing entities namely Software as a Service (SaaS). These attacks are quantified at both micro-level and macro-level. This paper also discusses the different solutions for these attacks, identified the gaps of each solutions and recommends methods which can be adopted to further improve the discussed solutions.