Towards Measuring and Understanding Performance in Infrastructure- and Function-as-a-Service Clouds

Context. Cloud computing has become the de facto standard for deploying modern software systems, which makes its performance crucial to the efficient functioning of many applications. However, the unabated growth of established cloud services, such as Infrastructure-as-a-Service (IaaS), and the emergence of new services, such as Function-as-a-Service (FaaS), has led to an unprecedented diversity of cloud services with different performance characteristics.Objective. The goal of this licentiate thesis is to measure and understand performance in IaaS and FaaS clouds. My PhD thesis will extend and leverage this understanding to propose solutions for building performance-optimized FaaS cloud applications.Method.\ua0To achieve this goal, quantitative and qualitative research methods are used, including experimental research, artifact analysis, and literature review.Findings.\ua0The thesis proposes a cloud benchmarking methodology to estimate application performance in IaaS clouds, characterizes typical FaaS applications, identifies gaps in literature on FaaS performance evaluations, and examines the reproducibility of reported FaaS performance experiments. The evaluation of the benchmarking methodology yielded promising results for benchmark-based application performance estimation under selected conditions. Characterizing 89 FaaS applications revealed that they are most commonly used for short-running tasks with low data volume and bursty workloads. The review of 112 FaaS performance studies from academic and industrial sources found a strong focus on a single cloud platform using artificial micro-benchmarks and discovered that the majority of studies do not follow reproducibility principles on cloud experimentation.Future Work. Future work will propose a suite of application performance benchmarks for FaaS, which is instrumental for evaluating candidate solutions towards building performance-optimized FaaS applications

Performance Evaluation of Serverless Applications and Infrastructures

Context. Cloud computing has become the de facto standard for deploying modern web-based software systems, which makes its performance crucial to the efficient functioning of many applications. However, the unabated growth of established cloud services, such as Infrastructure-as-a-Service (IaaS), and the emergence of new serverless services, such as Function-as-a-Service (FaaS), has led to an unprecedented diversity of cloud services with different performance characteristics. Measuring these characteristics is difficult in dynamic cloud environments due to performance variability in large-scale distributed systems with limited observability.Objective. This thesis aims to enable reproducible performance evaluation of serverless applications and their underlying cloud infrastructure.Method. A combination of literature review and empirical research established a consolidated view on serverless applications and their performance. New solutions were developed through engineering research and used to conduct performance benchmarking field experiments in cloud environments.Findings. The review of 112 FaaS performance studies from academic and industrial sources found a strong focus on a single cloud platform using artificial micro-benchmarks and discovered that most studies do not follow reproducibility principles on cloud experimentation. Characterizing 89 serverless applications revealed that they are most commonly used for short-running tasks with low data volume and bursty workloads. A novel trace-based serverless application benchmark shows that external service calls often dominate the median end-to-end latency and cause long tail latency. The latency breakdown analysis further identifies performance challenges of serverless applications, such as long delays through asynchronous function triggers, substantial runtime initialization for coldstarts, increased performance variability under bursty workloads, and heavily provider-dependent performance characteristics. The evaluation of different cloud benchmarking methodologies has shown that only selected micro-benchmarks are suitable for estimating application performance, performance variability depends on the resource type, and batch testing on the same instance with repetitions should be used for reliable performance testing.Conclusions. The insights of this thesis can guide practitioners in building performance-optimized serverless applications and researchers in reproducibly evaluating cloud performance using suitable execution methodologies and different benchmark types

Cloud robotic architectures: directions for future research from a comparative analysis

Advances in robotics and cloud computing have led to the emergence of cloud robotics where robots can benefit from remote processing, greater memory and computational power, and massive data storage. The integration of robotics and cloud computing has often been regarded as a complex aspect due to the various components involved in such systems. In order to address this issue, different studies have attempted to create cloud robotic architectures to simplify representation into different blocks or components. However, limited study has been undertaken to critically review and compare these architectures. As such, this paper investigates and performs a comparative analysis of existing cloud robotic architectures in order to identify key limitations and recommend on the future of cloud robotic architectures. As part of this study, 7 such architectures have been reviewed and compared and results showed limited evaluation of existing architectures in favour of security weaknesses

Cloud Computing: TOE Adoption Factors By Service Model In Manufacturing

Organizations are adopting cloud technologies for two primary reasons: to reduce costs and to enhance business agility. The pressure to innovate, reduce costs and respond quickly to changes in market demand brought about by intense global competition has U.S. manufacturing firms turning to cloud computing as an enabling strategy. Cloud computing is a service based information technology model that enables on-demand access to a shared pool of computing services provisioned over a broadband network. Cloud is categorized across three primary service models, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), differentiated by the cloud provider’s level of responsibility for managing hardware services, development platforms and application services. While prior research in cloud computing has sought to define the concept and explore the business value, empirical studies in the Information Systems literature stream are sparse, limited to exploratory case studies and SaaS research. Using the Technology, Organization, and Environment framework as a theoretical foundation, this research provides a holistic cloud adoption model inclusive of all cloud service layers. The study analyzes factors influencing organizational cloud adoption utilizing survey data from 150 U.S. manufacturing firms. The results find organizational innovativeness as a crucial factor to cloud computing adoption in manufacturing. An inverse factor relationship suggests the more innovative the firm culture, the less likely it is to adopt cloud. Other significant adoption factors include trust and technical competency. Findings also suggest variations in adoption influences based on the cloud service model deployed. The study has strategic implications for both researchers and managers seeking to understand the antecedents to adoption, and for practitioners developing an organizational cloud strategy spanning multiple cloud service models. For vendors, the study provides insights that can be leveraged to inform product design, solution strategy, and value proposition creation for future cloud service offerings

Cloud robotic architectures: directions for future research from a comparative analysis

Advances in robotics and cloud computing have led to the emergence of cloud robotics where robots can benefit from remote processing, greater memory and computational power, and massive data storage. The integration of robotics and cloud computing has often been regarded as a complex aspect due to the various components involved in such systems. In order to address this issue, different studies have attempted to create cloud robotic architectures to simplify representation into different blocks or components. However, limited study has been undertaken to critically review and compare these architectures. As such, this paper investigates and performs a comparative analysis of existing cloud robotic architectures in order to identify key limitations and recommend on the future of cloud robotic architectures. As part of this study, 7 such architectures have been reviewed and compared and results showed limited evaluation of existing architectures in favour of security weaknesses

Container description ontology for CaaS

[EN] Besides its classical three service models (IaaS, PaaS, and SaaS), container as a service (CaaS) has gained significant acceptance. It offers without the difficulty of high-performance challenges of traditional hypervisors deployable applications. As the adoption of containers is increasingly wide spreading, the use of tools to manage them across the infrastructure becomes a vital necessity. In this paper, we propose a conceptualisation of a domain ontology for the container description called CDO. CDO presents, in a detailed and equal manner, the functional and non-functional capabilities of containers, Dockers and container orchestration systems. In addition, we provide a framework that aims at simplifying the container management not only for the users but also for the cloud providers. In fact, this framework serves to populate CDO, help the users to deploy their application on a container orchestration system, and enhance interoperability between the cloud providers by providing migration service for deploying applications among different host platforms. Finally, the CDO effectiveness is demonstrated relying on a real case study on the deployment of a micro-service application over a containerised environment under a set of functional and non-functional requirements.K. Boukadi; M.a Rekik; J. Bernal Bernabe; Lloret, J. (2020). Container description ontology for CaaS. International Journal of Web and Grid Services (Online). 16(4):341-363. https://doi.org/10.1504/IJWGS.2020.11094434136316

A Bibliometric Overview of the International Airports and Airlines ‘IAA’ Topic in Journals and Scientific Community.

Background: The purpose of this study is to provide an assessment of international airports and airlines, ‘IAAs’, and to organize and classify the literature on air transport to stage the importance of this topic and encourage future research in the projection of the aviation and tourism sectors. Methods: It is a bibliographic study, and this work focuses on IAA documents published in major international journals, conferences, and books from 2000 to 9 June 2021; this topic is scattered across various journals and has secondary data in many disciplines. Results: The findings suggest a new paradigm applied to the IAA topic and are classified in four first-order research streams: airports; airlines; connectivity; and competition. This study identifies new challenges and opportunities for researchers, airport and airline operators, and stakeholders to make better future decisions. Conclusions: There is no agreement on an explicit definition of the IAA concept that captures the true nature of this topic. For this reason, this article is innovative in the new IAA concept and in how it will possibly change the theoretical frameworks in future scientific research in the aviation and tourism sectors. This study has been needed to better understand the effectiveness, projection, and different business strategies to be adopted by researchers and organizations in the aviation and tourism future.Partial funding for open access charge: Universidad de Málaga

Bid-Centric Cloud Service Provisioning

Bid-centric service descriptions have the potential to offer a new cloud service provisioning model that promotes portability, diversity of choice and differentiation between providers. A bid matching model based on requirements and capabilities is presented that provides the basis for such an approach. In order to facilitate the bidding process, tenders should be specified as abstractly as possible so that the solution space is not needlessly restricted. To this end, we describe how partial TOSCA service descriptions allow for a range of diverse solutions to be proposed by multiple providers in response to tenders. Rather than adopting a lowest common denominator approach, true portability should allow for the relative strengths and differentiating features of cloud service providers to be applied to bids. With this in mind, we describe how TOSCA service descriptions could be augmented with additional information in order to facilitate heterogeneity in proposed solutions, such as the use of coprocessors and provider-specific services

A METHOD TO CLASSIFY STANDARDS IN EMERGING TECHNOLOGIES: THE CASE OF CLOUD COMPUTING

Standards are an important part of any product or service as they impact many aspects such as interoperability, portability, and security. Hence, they constitute the cornerstone of any distributed, open, and flexible system “ even more so for emerging technologies such as cloud computing as the rate of their adoption can heavily depend on it. Often there is a plethora of standards available and “ despite their importance “ accurate information that can be used to guide the selection of standards is missing. Selecting the wrong standards can increase cost, reduce uptake, profitability, or lead to a product or service being stuck in a niche. Selecting the right standards can result in as much as the exact opposite. Despite numerous efforts to create classifications of standards that should provide guidance for the selection of standards, there is a lack of conceptualization and methods on how to build standards classifications. In this paper, we provide a conceptualization of technology standards, which serves as the basis for our method to classify standards in emerging technologies (C-SET). The method provides a procedure to classify standards based on a conceptual data model and a stakeholder model. In doing so, C-SET provides the basis to structure the information that is required for an informed selection of standards in emerging technologies. In this paper, we illustrate C-SET referring to cloud computing as an example of an emerging technology

Towards multi-criteria cloud service selection

Cloud computing despite being in an early stage of adoption is becoming a popular choice for businesses to replace in-house IT infrastructure due to its technological advantages such as elastic computing and cost benefits resulting from pay-as-you-go pricing and economy of scale. These factors have led to a rapid increase in both the number of cloud vendors and services on offer. Given that cloud services could be characterized using multiple criteria (cost, pricing policy, performance etc.) it is important to have a methodology for selecting cloud services based on multiple criteria. Additionally, the end user requirements might map to different criteria of the cloud services. This diversity in services and the number of available options have complicated the process of service and vendor selection for prospective cloud users and there is a need for a comprehensive methodology for cloud service selection. The existing research literature in cloud service selection is mostly concerned with comparison between similar services based on cost or performance benchmarks. In this paper we discuss and formalize the issue of cloud service selection in general and propose a multi-criteria cloud service selection methodology