When developing applications, developers face a challenge when they have to select the technologies that best fit the requirements gathered for the application that is going to be developed. New programming languages, frameworks, stacks, etc., have arisen in recent years making the choice even harder. Cloud computing is a new technology that has gained popularity in the last two decades providing computing resources to developers and companies. As with the other technologies, there are many cloud service providers to choose from. In this thesis, the two biggest cloud service providers Amazon Web Services and Microsoft Azure are compared. Furthermore, after comparing the providers a prototype of a customer relationship management system was deployed to the selected provider. From the data gathered it could be seen that further research needs to be done to decide which provider might fit better for application development.

In the last decades, the technology in ICT sector has advanced significantly. Rapid improvement of Internet services and virtualization techniques have caused the birth of a handful of computing paradigms, including the cloud computing. There are a number of major global cloud service providers that offers various cloud services to individual and companies. Consequently, there are increasing numbers of companies that are moving to the cloud leading to proliferation of cloud computing market. This thesis explores the impact of cloud computing towards early stage startups in terms of usage, benefit, competitive advantage, and dependency in order to be sustainable in the focus of a specific country: Sweden. Stockholm has become one of the top tech startup scenes in Europe and has given birth to a great deal of startups, some of the internationally recognized ones including Spotify, Klarna, and King while there are other ones that have a potential to catch up with them. In order to give an insight about what the impacts of cloud computing towards the early stage startups, three Stockholm-based early stage startups from 3 different field of business were interviewed. To ensure the anonymity of the startups, the companies are referred to The Healthy Company, a startup that sells healthy food through pop-up bicycle; The Invest Company, a startup that develops mobile application to connect startups and investors; and The Learning Company, a startup that summarizes business books that take 8 hours to finish into just half an hour. Based on the findings of this study, there are several characteristics that are similar in all 3 startups regardless of their field of business.

Cloud applications and services are frequently built using multiple tiers and current trends such as micro-services further increase componentization, allowing us to place each component in a different physical machine in a distributed cloud. Ericsson owns and manages very large networks, which offer diverse infrastructure in terms of computational power, storage but most importantly position in the network. Typically, a machine which is closer to the edge of the network (closer to the end user) will have limited resources but it will offer less latency, for a higher price. At the same time, several enterprise/industrial areas expect to benefit from the cloud business model in a large-scale distributed environment. These types of applications have very diverse end-2-end Service-Level Agreements (SLA) to be fulfilled, while at the same time the cloud environment needs to optimize processing, storage, and networking costs. Moreover, customers might want to change and adjust SLAs/requirements themselves using selfmanagement portals. The objective of this project is to model the network and services offered by Ericsson. Then, given the SLA, finding a valid solution of the problem, using a constraint solver. A solution is a set of physical machines that host the components the required service is composed from. This approach has many challenges since the same service can be composed from different sets of components. The connected components form a connectivity graph, where nodes in the graph are connected by physical links. But, since the connection is described by higher level components (composed by simpler components), this graph can also be expressed as a tree. Leaves in the tree are the nodes that compose the higher-level services and the ones that must be hosted in the infrastructure. The characteristics of each leaf-node depend on its parent and/or siblings in the component tree. Finally, since the components are normally connected, the physical connection between nodes in the network must be taken into consideration. The proposed model is evaluated in several cases, in order to identify how the number of the software components and the infrastructure topology affect the solution finding. The results are promising, showing fast resolution of the problem instances, varying for each test case, from a few seconds to a couple of minutes. / Molnapplikationer och tjänster är ofta byggda med flera nivåer och nuvarande trender såsom mikro-tjänster ökar ytterligare komponentiseringen, vilket tillåter oss att placera varje komponent i en annan fysisk maskin på ett distribuerat moln. Ericsson äger och förvaltar väldigt stora nätverk som erbjuder varierande infrastruktur när det gäller beräkningskraft , lagring och framför allt position i nätverket. Typiskt kommer en maskin som är närmare kanten av nätet (närmare slutanvändaren) att ha begränsade resurser, men det kommer att erbjuda mindre latens till ett högre pris. Samtidigt räknar flera företag / industriområden med att dra nytta av moln affärsmodelltjänster i en storskalig och distribuerad miljö. Den här typen av applikationer har väldigt olika end-to-end varierande servicenivåavtal (SLA) som skall uppfyllas, medan moln miljön behöver optimera bearbetnings, lagrings och nätverks kostnader. Dessutom, kan kunden komma att vilja ändra och justera SLA / krav själva med hjälp av självhantering portaler. Målet för detta projekt är att modellera nät och tjänster som erbjuds av Ericsson. Sedan, givet ett SLA, att hitta en giltig lösning på problemet, med hjälp av en villkorslösare. En lösning är en uppsättning av fysiska maskiner som är värdar för komponenterna från vilka den efterfrågade tjänsten är sammansatt. Detta tillvägagångssätt är förenat med många utmaningar eftersom samma tjänst kan bestå av olika uppsättningar av komponenter. De anslutna komponenterna bildar ett förbindelseschema, där noder i grafen är anslutna med fysiska länkar. Men eftersom anslutningen beskrivs av komponenter högre nivå (bestående av enklare komponenter), denna graf kan också uttryckas som ett träd. Löv i trädet är noderna som utgör de högre nivå tjänster och de som måste finnas i infrastrukturen. Egenskaperna hos varje löv-nod att bero på dess förälder och / eller syskon i komponentträdet. Slutligen, eftersom komponenterna i normal fall är anslutna, måste den fysiska anslutningen mellan noder i nätet tas i beaktande. Den föreslagna modellen utvärderas i flera fall, för att identifiera hur antalet programvarukomponenter och infrastrukturens topologi påverkar resultatet av lösningen. Resultaten är lovande och visar snabb lösning av problemets instanser, varierande för varje testfall, från några sekunder till ett par minuter.

Cloud computing has brought availability of services at unprecedented scales but data accessibility considerations become more complex due to involvement of multiple parties in providing the infrastructure. In this thesis, we discuss the problem of enabling cooperative data access in a multi-cloud environment where the data is owned and managed by multiple enterprises. We consider a multi-party collaboration scheme whereby a set of parties collectively decide accessibility to data from individual parties using different data models such as relational databases, and graph databases. In order to implement desired business services, parties need to share a selected portion of information with one another. We consider a model with a set of authorization rules over the joins of basic relations, and such rules are defined by these cooperating parties. The accessible information is constrained by these rules. Specifically, the following critical issues were examined: Combine rule enforcement and query planning and devise an algorithm which simultaneously checks for the enforceability of each rule and generation of minimum cost plan of its execution using a cost metric whenever the enforcement is possible; We also consider other forms of limiting the access to the shared data using safety properties and selection conditions. We proposed algorithms for both forms to remove any conflicts or violations between the limited accesses and model queries; Used graph databases with our authorization rules and query planning model to conduct similarity search between tuples, where we represent the relational database tuples as a graph with weighted edges, which enables queries involving "similarity" across the tuples. We proposed an algorithm to exploit the correlations between attributes to create virtual attributes that can be used to catch much of the data variance, and enhance the speed at which similarity search occurs; Proposed a framework for defining test functionalities their composition, and their access control. We discussed an algorithm to determine the realization of the given test via valid compositions of individual functionalities in a way to minimize the number of parties involved. The research significance resides in solving real-world issues that arise in using cloud services for enterprises After extensive evaluations, results revealed: collaborative data access model improves the security during cooperative data processes; systematic and efficient solving access rules conflict issues minimizes the possible data leakage; and, a systematic approach tackling control failure diagnosis helps reducing troubleshooting times and all that improve availability and resiliency. The study contributes to the knowledge, literature, and practice. This research opens up the space for further studies in various aspects of secure data cooperation in large-scale cyber and cyber-physical infrastructures. / Computer and Information Science

Cloud Computing is becoming increasingly popular, with large amounts of corporations revenue coming in from various cloud solutions offered to customers. When it comes to choosing a solution, multiple options exist for the same problem from many competitors. This report focuses on the ones offered by Microsoft in their Azure platform, and compares the architectures in terms of performance and scalability.In order to determine the most suitable architecture, three offered by Azure are considered: Cloud Services (CS), Service Fabric Mesh (SFM) and Virtual Machines (VM). By developing and deploying a REST Web API to each service and performing a load test, average response times in milliseconds are measured and compared. To determine scalability, the point at which each service starts timing out requests is identified. The services are tested both by scaling up, by increasing the power of a single instance of a machine, and by scaling out, if possible, by duplicating instances of machines running in parallel.The results show that VMs fall considerably behind both CS and SFM in both performance and scalability, for a regular use case. For low amounts of requests, all services perform about the same, but as soon as the requests increase, it is clear that both SFM and CS outperform VMs. In the end, CS comes ahead both in terms of scalability and performance.Further research may be done into other platforms which offer the same service solutions, such as Amazon Web Services (AWS) and Google Cloud, or other architectures within Azure. / Molntjänster blir alltmer populära i dagens industri, där stora mängder av företagens omsättning består av tjänster erbjudna i form av molnlösningar. När det kommer till att välja en lösning finns många för samma problem, där det är upp till kunden att välja vilken som passar bäst. Denna rapport fokuserar på tjänster erbjudna av Microsofts Azure plattform, i en jämförelse av arkitekturer som belastningstestas för att mäta prestanda och skalbarhet.För att avgöra vilken arkitektur som är optimalast mäts tre olika tjänster erbjudna i Azure: Cloud Services (CS), Service Fabric Mesh (SFM) och Virtual Machines (VM). Detta görs genom att utveckla och deploya ett REST Web API som är simulerat med användare, där prestanda mäts genom att ta medelresponstiden i millisekunder per anrop. För att avgöra skalbarhet identifieras en punkt där tjänsten inte längre klarar av antalet inkommande anrop och börjar returnera felkoder. Maskinerna för varje tjänst testas både genom att skala upp, genom att förstärka en maskin, men även genom att skala ut, där det skapas flera instanser av samma maskin.Resultatet visar att Virtual Machines hamnar betydligt efter både CS och SFM i både prestanda och skalbarhet för ett vanligt användarfall. För låga mängder anrop ligger samtliga tjänster väldigt lika, men så fort anropen börjar öka så märks det tydligt att SFM och CS presterar bättre än Virtual Machines. I slutändan ligger CS i framkant, både i form av prestanda och skalbarhet.Vidare undersökning kan göras för de olika plattformarna erbjudna av konkurrenter, så som Amazon Web Services (AWS) och Google Cloud, samt andra arkitekturer från Azure.

Sammanfattning Industri 4.0 tyder på den senaste fasen av industrialiseringen och fokuserar på digitalisering, automatisering och datautbyte. Den fjärde industriella revolutionen, Industri 4.0, bygger på tidigare industriella revolutioner och använder sig av olika teknologier såsom IoT, Big Data Analytics och Cloud Services. Inom inköpsprocessen innebär Industri 4.0 ett behov att effektivisera och uppnå flexibla processer för att möta ökade krav på innovation och kvalitet. Syftet med arbetet är att identifiera och analysera användningen av Industri 4.0-teknologier i inköpsprocessen för att förbättra effektiviteten. Forskningsfrågorna fokuserar på vilka teknologier som används i inköpsprocessen och på vilket sätt de används samt att analysera deras roll i att förbättra effektiviteten. Arbetet begränsas till inköpsprocessen inom supply chain management och använder en strukturerad litteraturgenomgång som metod. Användningen av IoT, CPS, Big Data-analys, Blockchain och Cloud Services automatiserar och effektiviserar inköpsaktiviteter. IoT används för realtidsövervakning och automatiserad påfyllning av lager. CPS samordnar både digitala och fysiska komponenter i syfte att förbättra spårbarhet och beslutsfattande. Big Data-analys förutser efterfrågan samt utvärderar leverantörers prestationer. Blockchain säkerställer transparenta och säkra transaktioner med hjälp av smarta kontrakt. Cloud Services hanterar realtidsdata och förbättrar kommunikation och samarbete i leveranskedjan. Dessa teknologier spelar en central roll för effektiviseringen i inköpsprocessen där manuella lager minskar, leverantörsförhandlingar effektiviseras och efterfrågeprognoser, spårbarhet och beslutsfattande förbättras. Det ökar i sin tur transparensen, säkerställer transaktioner och underlättar strategiska beslut, vilket leder till förbättrad effektivitet, resursförvaltning och konkurrenskraft. Syfte  Syftet med arbetet är att sammanställa information om Industri 4.0-teknologier med hjälp av systematisk litteraturgenomgång för att identifiera användningen av teknologierna i inköpsprocessen samt analysera vilken roll dessa teknologier spelar för att förbättra effektiviteten. Metod  En systematisk litteraturgenomgång genomfördes för att samla in relevant data som i sin tur användes för att analysera och besvara forskningsfrågorna. / Abstract Industry 4.0 signifies the latest phase of industrialization, focusing on digitalization, automation, and data exchange, utilizing different technologies to increase productivity and competitiveness. This work aims to identify and analyze the use of Industry 4.0 technologies in the procurement process to improve efficiency. The research questions focus on which technologies are used and their role in improving efficiency, limited to the procurement process within supply chain management, using a structured literature review as a method. The use of IoT, CPS, Big Data Analytics, Blockchain, and Cloud Services automates procurement activities. IoT is used for real-time monitoring and automated inventory replenishment. CPS coordinates both digital and physical components in order to improve traceability and decision-making. Big Data Analytics forecasts demand as well as evaluates supplier performance. Blockchain ensures transparent and secure transactions with the help of smart contracts. Cloud Services manage real-time data and improve communication and collaboration in the supply chain. These technologies play a central role in effectiveness for the procurement process where manual inventories decrease, supplier negotiations become more efficient and demand forecasts, traceability, and decision-making improve. This, in turn, increases transparency, ensures transactions, and facilitates strategic decisions, leading to improved efficiency, resource management, and competitiveness. Purpose  The purpose of the work is to compile information on Industry 4.0 technologies using a systematic literature review to identify the use of technologies in the purchasing process and analyze what role these technologies play in improving efficiency. Methodology  A systematic literature review was conducted to gather relevant data which in turn was used to analyze and answer the research questions.

Information Technology (IT) leaders must leverage cloud computing to maintain competitive advantage. Evidence suggests that IT leaders who have leveraged cloud computing in small and medium sized organizations have saved an average of $1 million in IT services for their organizations. The purpose of this qualitative single case study was to explore strategies that IT leaders use to adopt cloud computing for their organizations. The target population consisted of 15 IT leaders who had experience with designing and deploying cloud computing solutions at their organization in Long Island, New York within the past 2 years. The conceptual framework of this research project was the disruptive innovation theory. Semistructured interviews were conducted and company documents were gathered. Data were inductively analyzed for emergent themes, then subjected to member checking to ensure the trustworthiness of findings. Four main themes emerged from the data: the essential elements for strategies to adopt cloud computing; most effective strategies; leadership essentials; and barriers, critical factors, and ineffective strategies affecting adoption of cloud computing. These findings may contribute to social change by providing insights to IT leaders in small and medium sized organizations to save money while gaining competitive advantage and ensure sustainable business growth that could enhance community standards of living.

With advances in information technology, various cloud computing related research and development has become a hot trend. Except the vast amount of studies and reports appearing in local magazines and newspapers, government agencies have also set up corresponding R & D projects. However, most of these studies focus on the infrastructure or platform level of the cloud. For example, the projects for Infrastructure as a Service (IaaS) include the Cloud Computing Center for Mobile Application at Industrial Technology Research Institute (ITRI), the Cloud Service and Technology Center at Information Industry Institute (III) and the already launched ¡§hiCloud¡¨ at Chunghwa Telecom Corporation. In the business side, there is TCloud Computing that does the development of both "Infrastructure" and "Platform as a Service" (PaaS). As to Software as a Service (SaaS) related research, III has gathered 10 domestic companies to participate the co-operation plans for education cloud, manufacture cloud, ¡K and practice cloud, a total of nine cloud services. However, they are all in the early stages without much success stories or usages. The study of this thesis is angled toward business needs, from the point of resource-based analysis to see how a firm will be affected if introduction of SaaS to business. In particular, we will study this subject from four dimensions, which are the competitiveness of enterprises, IT outsourcing strategy, cost structure analysis and data security technology, to identify the possible critical factors for the introduction for cloud computing services. As most people are perceived, cloud computing has a comparative advantage of cost saving over traditional approach.

Cloud Computing is emerging as a new paradigm that aims at delivering computing as a utility. For the cloud computing paradigm to be fully adopted and effectively used it is critical that the security mechanisms are robust and resilient to malicious faults and attacks. Securing cloud is a challenging research problem because it suffers from current cybersecurity problems in computer networks and data centers and additional complexity introduced by virtualizations, multi-tenant occupancy, remote storage, and cloud management. It is widely accepted that we cannot build software and computing systems that are free from vulnerabilities and that cannot be penetrated or attacked. Furthermore, it is widely accepted that cyber resilient techniques are the most promising solutions to mitigate cyberattacks and change the game to advantage defender over attacker. Moving Target Defense (MTD) has been proposed as a mechanism to make it extremely challenging for an attacker to exploit existing vulnerabilities by varying different aspects of the execution environment. By continuously changing the environment (e.g. Programming language, Operating System, etc.) we can reduce the attack surface and consequently, the attackers will have very limited time to figure out current execution environment and vulnerabilities to be exploited. In this dissertation, we present a methodology to develop an Autonomic Resilient Cloud Management (ARCM) based on MTD and autonomic computing. The proposed research will utilize the following capabilities: Software Behavior Obfuscation (SBO), replication, diversity, and Autonomic Management (AM). SBO employs spatiotemporal behavior hiding or encryption and MTD to make software components change their implementation versions and resources randomly to avoid exploitations and penetrations. Diversity and random execution is achieved by using AM that will randomly "hot" shuffling multiple functionally-equivalent, behaviorally-different software versions at runtime (e.g., the software task can have multiple versions implemented in a different language and/or run on a different platform). The execution environment encryption will make it extremely difficult for an attack to disrupt normal operations of cloud. In this work, we evaluated the performance overhead and effectiveness of the proposed ARCM approach to secure and protect a wide range of cloud applications such as MapReduce and scientific and engineering applications.

Att inom företag och organisationer använda sig av molntjänster är den senaste heta trenden inom IT-världen. Men vad finns det egentligen för fördelar och nackdelar med att använda sig av molntjänster? I denna uppsats beskriver vi först fenomenet molnetoch molnjänster, även känt som cloud computing. Efter det har vi gjort en litteraturstudie för att ta reda på vad det finns för för och nackdelar med användandetav molntjänster. Vi har till slut utfört en kvalitativ enkätundersökning för att ta reda påvad IT-företag som använder sig av molntjänster upplever för för och nackdelar meddem. Den genomförda litteraturstudien resulterade i ett visst antal för och nackdeler.Dessa för och nackdelar har vi delat in i åtta stycken kategorier med övergripande teman. Vi har därefter utformat enkätfrågorna utifrån dessa kategorier.