雲端運算環境的興起，軟體即服務(Software as a Service, SaaS)的營運模式也開始受到軟體開發商的注意，其中一項關鍵技術是支援多租戶的軟體開發。在設計多租戶應用程式時有許多需要考量的因素，包含每個租戶各自的客製化設定、資料安全性等等。本論文著重於資料層級的客製化部份，如何讓各個租戶之間可以共用資料庫，但又能提供租戶適度地更改其資料表綱要(schema)以達到客製化的需求。 為了解決資料層級客製化所面臨的問題，一種常見的作法是可延伸性表格(Extension Table Layout)。但是，在關聯式資料庫中實作可延伸性表格，軟體開發人員為了配合可延伸性表格的資料存放方式，所使用的SQL語句會變得相當複雜且易錯。因此，本研究實作一個系統工具協助軟體開發人員將SQL語句，從一租戶一資料表寫法自動轉換成以可延伸性表格邏輯表達的SQL語句，透過執行轉換後的語句來對儲存在可延伸性表格的資料進行增刪修改。 軟體開發人員在本系統工具的協助下，加入租戶識別碼(TenanId)的開發概念後，即可實際建立一個多租戶應用程式。為了評估本系統工具的效用，我們以其建置了一個多校(租戶)選課系統，並進行多項效能實驗以探討影響本系統工具效能的因素。初步的結果顯示，本系統工具可以協助軟體開發人員，以較低的代價滿足資料層級客製化應用的需求。 / Software as a service (SaaS) is an emerging service model of cloud computing. One of the key technology in SaaS is supporting multi-tenant applications. There are many considerations in the design of multi-tenant applications, including customized configuration of tenants and data security. In this thesis, we focus on data-level customized configuration, and propose an approach for not only sharing database between tenants but also supporting tenants to modify their table schemas within limits. Extension Table Layout is one solution for solving the problems in data-level customized configuration for multi-tenant applications. However, SQL statemenst based on the Extension Table Layout are rather complicated and error-prone. Thus, we develop a tool to help software developers that will automatically rewrite the SQL statements from the common Private Table Layout into those from the Extension Table Layout at runtime. In other words, our tool enable software developers to write SQL statements in a multi-tenant application like in a single tenant application. Indeed, software developers could develop a multi-tenant application easily by using our tool and the multi-tenant enabler - TenantId. In order to assess the feasibility of our tool, we develop an online multi-tenant course election application. Besides, we disscus the effectiveness of the factors that affecting our tool and work on a number of experiments and performance tests. The preliminary results show that our SQL rewriting tool can help software developers at a lower cost to meet the needs of data-level customized applications to a degree.

Increasing number of software vendors are offering or planning to offer their applications as a Software-as-a-Service (SaaS) to leverage the benefits of cloud computing and Internet-based delivery. Therefore, potential clients will face increasing number of providers that satisfy their requirements to choose from. Consequently, there is an increasing demand for automating such a time-consuming and error-prone task. In this work, we develop an architecture for automated service discovery and selection in cloud computing environment. The system is based on an algorithm that recommends service choices to users based on both functional and non-functional characteristics of available services. The system also derives automated ratings from monitoring results of past service invocations to objectively detect badly-behaving providers. We demonstrate the effectiveness of our approach using an early prototype that was developed following object-oriented methodology and implemented using various open-source Java technologies and frameworks. The prototype uses a Chord DHT as its distributed backing store to achieve scalability.

<p>Web-based Enterprise Resource Planning (ERP) Systems deployed through theSoftware-as-a-Service (SaaS) model are a major disruptive technology in the fieldof ERP systems. The defining features of the SaaS are that they are hosted remotelyand are completely used through the web; they are subscription-payment basedand they operate on a multi-tenant fashion. This technological innovation redefinestraditional technical and economic ERP paradigms.</p><p>This Bachelor’s thesis aims through interviews with vendors, users and consultants,as well as by researching various academical and professional publications onthe subject of Web-based (SaaS) ERPs to study these pehomena, and produce a listof their benefits to SMEs. It also analyses their opportunities and challenges via anumber of interesting facts, thus allowing for thought-provoking observations andspawning of stirring discussions.</p><p>The benefits of Web-based ERPs were reported to be similar to the ones characteristicfor the On-premise ERPs. They furthermore included remote data access, costefficiency,flexibility, scalability, as well as the esublishment of a new customerdrivenrelationship with the ERP vendor. The major disadvantages of SaaS wereconsidered to be security, cost (in the long run), and customizability. These disadvantages,which were first reported years ago, are continuously dismissed by theadavncements and innovations made in Web-based solutions. Findings from previousstudies and trends suggest that issues of security, cost and customizabilityare gradually disappearing as technology improves and industry dynamics becomesmore customer-centric. Security, which was a major issue in 2007 slowlyfaded and is not regarded as the concern it used to be. From 2008 till now the issuesof customizability and TCO have been heavily disputed about Web-based ERPsolutions. The problem of customizability has also been found to be diminishingdue to technologically advanced capabilities of these systems; new systems haveemerged and old systems have improved enough to provide this feature. Cost hasnever been a transparent issue when it comes to IT investments and has beenshown to be higher in On-Premise solutions through the TVO approach whichlooks at other hidden and non-financial costs. All of the above sheds new light intothe once-‘static’ benefits and drawbacks of Web-based solutions, and provides afresh insight into this developing phenomenon.</p>

Increasing number of software vendors are offering or planning to offer their applications as a Software-as-a-Service (SaaS) to leverage the benefits of cloud computing and Internet-based delivery. Therefore, potential clients will face increasing number of providers that satisfy their requirements to choose from. Consequently, there is an increasing demand for automating such a time-consuming and error-prone task. In this work, we develop an architecture for automated service discovery and selection in cloud computing environment. The system is based on an algorithm that recommends service choices to users based on both functional and non-functional characteristics of available services. The system also derives automated ratings from monitoring results of past service invocations to objectively detect badly-behaving providers. We demonstrate the effectiveness of our approach using an early prototype that was developed following object-oriented methodology and implemented using various open-source Java technologies and frameworks. The prototype uses a Chord DHT as its distributed backing store to achieve scalability.

My master thesis has the main objective to implement into the sector of small and medium sized enterprises a cloud computing solution as required the customer company. Subsidiary targets of my literary part are a definition of small and medium-sized enterprises, explanation of terms corresponding to cloud computing, explaining the very concept of cloud computing and its distribution models, analysis of cloud services and what is involved in the transition to a cloud environment for companies, including migration contract. The first part summarizes information on cloud computing. The second part provides specific implementation of a cloud computing solutions into corporate environments based on empirical research and requirements of the company.

abstract: Software-as-a-Service (SaaS) has received significant attention in recent years as major computer companies such as Google, Microsoft, Amazon, and Salesforce are adopting this new approach to develop software and systems. Cloud computing is a computing infrastructure to enable rapid delivery of computing resources as a utility in a dynamic, scalable, and virtualized manner. Computer Simulations are widely utilized to analyze the behaviors of software and test them before fully implementations. Simulation can further benefit SaaS application in a cost-effective way taking the advantages of cloud such as customizability, configurability and multi-tendency. This research introduces Modeling, Simulation and Analysis for Software-as-Service in Cloud. The researches cover the following topics: service modeling, policy specification, code generation, dynamic simulation, timing, event and log analysis. Moreover, the framework integrates current advantages of cloud: configurability, Multi-Tenancy, scalability and recoverability. The following chapters are provided in the architecture: Multi-Tenancy Simulation Software-as-a-Service. Policy Specification for MTA simulation environment. Model Driven PaaS Based SaaS modeling. Dynamic analysis and dynamic calibration for timing analysis. Event-driven Service-Oriented Simulation Framework. LTBD: A Triage Solution for SaaS. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2015

abstract: Nowadays, Computing is so pervasive that it has become indeed the 5th utility (after water, electricity, gas, telephony) as Leonard Kleinrock once envisioned. Evolved from utility computing, cloud computing has emerged as a computing infrastructure that enables rapid delivery of computing resources as a utility in a dynamically scalable, virtualized manner. However, the current industrial cloud computing implementations promote segregation among different cloud providers, which leads to user lockdown because of prohibitive migration cost. On the other hand, Service-Orented Computing (SOC) including service-oriented architecture (SOA) and Web Services (WS) promote standardization and openness with its enabling standards and communication protocols. This thesis proposes a Service-Oriented Cloud Computing Architecture by combining the best attributes of the two paradigms to promote an open, interoperable environment for cloud computing development. Mutil-tenancy SaaS applicantions built on top of SOCCA have more flexibility and are not locked down by a certain platform. Tenants residing on a multi-tenant application appear to be the sole owner of the application and not aware of the existence of others. A multi-tenant SaaS application accommodates each tenant’s unique requirements by allowing tenant-level customization. A complex SaaS application that supports hundreds, even thousands of tenants could have hundreds of customization points with each of them providing multiple options, and this could result in a huge number of ways to customize the application. This dissertation also proposes innovative customization approaches, which studies similar tenants’ customization choices and each individual users behaviors, then provides guided semi-automated customization process for the future tenants. A semi-automated customization process could enable tenants to quickly implement the customization that best suits their business needs. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2016

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-03-14T23:51:19Z No. of bitstreams: 1 ArlindoRodriguesDaSilvaNeto_DISSERT.pdf: 3147140 bytes, checksum: 65ec83f6b7b7603769da720a2273e85b (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-03-16T23:01:46Z (GMT) No. of bitstreams: 1 ArlindoRodriguesDaSilvaNeto_DISSERT.pdf: 3147140 bytes, checksum: 65ec83f6b7b7603769da720a2273e85b (MD5) / Made available in DSpace on 2017-03-16T23:01:46Z (GMT). No. of bitstreams: 1 ArlindoRodriguesDaSilvaNeto_DISSERT.pdf: 3147140 bytes, checksum: 65ec83f6b7b7603769da720a2273e85b (MD5) Previous issue date: 2016-08-26 / Este trabalho consiste em criar uma ferramenta de BI (Business Intelligence) dispon?vel em nuvem (cloud computing) atrav?s de SaaS (Software as Service) utilizando t?cnicas de ETL (Extract, Transform, Load) e tecnologias de Big Data, com a inten??o de facilitar a extra??o descentralizada e o processamento de dados em grande quantidade. Atualmente, constata-se que ? praticamente invi?vel realizar uma an?lise consistente sem o aux?lio de um software para gera??o de relat?rios e estat?sticas. Para tais fins, a obten??o de resultados concretos com a tomada de decis?o exige estrat?gias de an?lise de dados e vari?veis consolidadas. Partindo dessa vis?o, enfatiza-se neste estudo o Business Intelligence (BI) com o objetivo de simplificar a an?lise de informa??es gerenciais e estat?sticas para propiciar indicadores atrav?s de gr?ficos ou listagens din?micas de dados gerenciais. Assim, ? poss?vel inferir que, com o crescimento exponencial dos dados torna-se cada vez mais dif?cil a obten??o de resultados de forma r?pida e consistente, tornando necess?rio atuar com novas t?cnicas e ferramentas para tratamentos de dados em larga escala. Este trabalho ? de natureza t?cnica de cria??o de um produto de Engenharia de Software, fundamentado a partir do estudo da arte da ?rea, e de um comparativo com as principais ferramentas existentes no mercado, evidenciando vantagens e desvantagens da solu??o criada. / This work is to create a BI tool (Business Intelligence) available in the cloud (cloud computing) through SaaS (Software as Service) using ETL techniques (extract, transform, load) and Big Data technologies, with the intention of facilitating decentralized extraction and data processing in large quantities. Currently, it appears that it is practically impossible conduct a consistent analysis without the aid of a software for reporting and statistics. For these purposes, the achievement of concrete results with decision making requires data analysis strategies and consolidated variable. From this view, it is emphasized in this study Business Intelligence (BI) in order to simplify the analysis of management information and statistics to provide indicators through graphs or dynamic lists of data management. Thus, it is possible to infer that with the exponential growth of data becomes increasingly difficult to obtain results quickly and consistently, making it necessary to work with new techniques and tools for large-scale data processing. This work is technical in nature to create a product of Software Engineering, based from the study of art in the area, and a comparison with the main existing tools on the market, showing advantages and disadvantages of the created solution. / 2020-12-31

Context. Software product planning involves product lifecycle management, roadmapping, release planning and requirements engineering. Requirements are collected and used together with criteria to define short-term plans, release plans and long-term plans, roadmaps. The different stages of the product lifecycle determine whether a product is mainly evolved, extended, or simply maintained. When eliciting requirements and identifying criteria for software product planning, the product manager is confronted with statements about customer interests that do not correspond to their needs. Analytics summarize, filter, and transform measurements to obtain insights about what happened, how it happened, and why it happened. Analytics have been used for improving usability of software solutions, monitoring reliability of networks and for performance engineering. However, the concept of using analytics to determine the evolution of a software solution is unexplored. In a context where a misunderstanding of users’ need can easily lead the effective product design to failure, the support of analytics for software product planning can contribute to fostering the realization of which features of the product are useful for the users or customers. Objective. In observation of a lack of primary studies, the first step is to apply analytics of software product planning concept in the evolution of software solutions by having an understanding of the product usage measurement. For this reason, this research aims to understand relevant analytics of users’ interaction with SaaS applications. In addition, to identify an effective way to collect right analytics and measure feature usage with respect to page-based analytics and feature-based analytics to provide decision-support for software product planning. Methods. This research combines a literature review of the state-of-the-art to understand the research gap, related works and to find out relevant analytics for software product planning. A market research is conducted to compare the features of different analytics tools to identify an effective way to collect relevant analytics. Hence, a prototype analytics tool is developed to explore the way of measuring feature usage of a SaaS website to provide decision-support for software product planning. Finally, a software simulation is performed to understand the impact of page clutter, erroneous page presentation and feature spread with respect to page-based analytics and feature-based analytics. Results. The literature review reveals the studies which describe the related work on relevant categories of software analytics that are important for measuring software usage. A software-supported approach, developed from the feature comparison results of different analytics tools, ensures an effective way of collecting analytics for product planners. Moreover, the study results can be used to understand the impact of page clutter, erroneous page representation and feature spread with respect to page-based analytics and feature-based analytics. The study reveals that the page clutter, erroneous page presentation and feature spread exaggerate feature usage measurement with the page-based analytics, but not with the feature-based analytics. Conclusions. The research provided a wide set of evidence fostering the understanding of relevant analytics for software product planning. The results revealed the way of measuring the feature usage to SaaS product managers. Furthermore, feature usage measurement of SaaS websites can be recognized, which helps product managers to understand the impact of page clutter, erroneous page presentation and feature spread between page-based and feature-based analytics. Further case study can be performed to evaluate the solution proposals by tailoring the company needs. / +46739480254

Context. Cloud computing is getting more and more interest with every year. It is an approach that allows Internet based applications to work in distributed and virtualized cloud environment. It is characterized by on-demand resources and payper-use pricing. Software-as-a-Service (SaaS) is a software distribution paradigm in cloud computing and represents the highest, software layer in the cloud stack. Since most cloud services providers charge for the resource use it is important to create resource efficient applications. One of the way to achieve that is multi-tenant architecture of SaaS applications. It allows the application for efficient self-managing of the resources Objectives. In this study I investigate the influence of tenant-based resource allocation model on cost-effectiveness of SaaS systems. I try to find out weather that model can decrease the system&apos;s actual costs in commercial public cloud environment. Methods. I am implementing two authorial SaaS systems: first tenant-unaware and then using tenant-based resource allocation model. Then they are deployed into Amazon public cloud environment. Tests focused on measuring over- and underutilization are conducted in order to compare cost-effectiveness of the solutions. Public cloud provider&apos;s billing service is used as a final cost measure. Results. The tenant-based resource allocation model proved to decrease my system&apos;s running costs. It also reduced the system&apos;s resources underutilization. Similar research was done, but the model was tested in private cloud. In this work the systems were deployed into commercial public cloud. Conclusions. The tenant-based resource allocation model is one of the method to tackle under-optimal resource utilization. When compared to traditional resource scaling it can reduce the costs of running SaaS systems in cloud environments. The more tenant-oriented the SaaS systems are the more benefits that model can provide.