An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes

Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety of scenarios creates different challenges such as the heterogeneity of IoT devices, support for large numbers of connected devices, reliable and safe systems, energy efficiency and the possibility of using this system by third-parties in other scenarios. A transversal middleware in all IoT solutions is called an IoT platform. the IoT platform is a piece of software that works like a kind of “glue” to combine platforms and orchestrate capabilities that connect devices, users and applications/services in a “cyber-physical” world. In this way, the IoT platform can help solve the challenges listed above. This paper proposes an IoT agnostic architecture, highlighting the role of the IoT platform, within a broader ecosystem of interconnected tools, aiming at increasing scalability, stability, interoperability and reusability. For that purpose, different paradigms of computing will be used, such as microservices architecture and serverless computing. Additionally, a technological proposal of the architecture, called SEnviro Connect, is presented. This proposal is validated in the IoT scenario of smart farming, where five IoT devices (SEnviro nodes) have been deployed to improve wine production. A comprehensive performance evaluation is carried out to guarantee a scalable and stable platform

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

Evaluating Performance of Serverless Virtualization

Abstract. The serverless computing has posed new challenges for cloud vendors that are difficult to solve with existing virtualization technologies. Maintaining security, resource isolation, backwards compatibility and scalability is extremely difficult when the platform should be able to deliver native performance. This paper contains a literature review of recently published results related to the performance of virtualization technologies such as KVM and Docker, and further reports a DESMET benchmarking evaluation against KVM and Docker, as well as Firecracker and gVisor, which are being used by Amazon Web Services and Google Cloud in their cloud services. The context for this research is coming from education, where students return their programming assignments into a source code repository system that further triggers automated tests and potentially other tasks against the submitted code. The used environment consists of several software components, such as web server, database and job executor, and thus represents a common architecture in web-based applications. The results of the research show that Docker is still the most performant virtualization technology amongst the selected ones. Additionally, Firecracker and gVisor perform better in some areas than KVM and thus are viable options for single-tenant environments. Lastly, applications that run untrusted code or have otherwise really high security requirements could potentially leverage from using either Firecracker or gVisor

Security in DevOps: understanding the most efficient way to integrate security in the agile software development process

Modern development methodologies follow a fast and dynamic pace, which gives great attention to customers’ satisfaction in the delivery of new releases. On the other hand, the work pursued to secure a system, if not adapted to the new development trend, can risk to slow down the delivery of new software and the adaptability typical for an Agile environment. Therefore, it is paramount to think about a new way to integrate security into the development framework, in order to secure the software in the best way without slowing down the pace of the developers. Moreover, the implementation of automatic and repeatable security controls inside the development pipeline can help to catch the presence of vulnerabilities as early as possible, thus reducing costs, comparing to solving the issues at later stages. The thesis presents a series of recommendations on how to best deploy a so called DevSecOps approach and applies the theory to the use case of Awake.AI, a Finnish startup company focusing its business on the maritime industry. It is not always easy and feasible to practically apply all the suggestions presented in the literature to a real case scenario, but rather the recommendations need to be adapted and forged in a way that best suits the situation and the current target. It is undeniable that the presence of a strong and efficient secure development framework can give substantial advantage to the success of a company. In fact, not only it makes sure that the delivery of good quality code to the customers is not slowed down, but it also dramatically reduces the risk of incurring in expensive security incidents. Lastly, it is valuable to also mention that, being able to show a clean and efficient approach to security, the framework improves the reputation and trustfulness of the company under the eyes of the customers

Introduction to the Special Issue "Applications in Self-Aware Computing Systems and their Evaluation"

The joint 1st Workshop on Evaluations and Measurements in Self-Aware Computing Systems (EMSAC 2019) and Workshop on Self-Aware Computing (SeAC) was held as part of the FAS* conference alliance in conjunction with the 16th IEEE International Conference on Autonomic Computing (ICAC) and the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO) in Umeå, Sweden on 20 June 2019. The goal of this one-day workshop was to bring together researchers and practitioners from academic environments and from the industry to share their solutions, ideas, visions, and doubts in self-aware computing systems in general and in the evaluation and measurements of such systems in particular. The workshop aimed to enable discussions, partnerships, and collaborations among the participants. This special issue follows the theme of the workshop. It contains extended versions of workshop presentations as well as additional contributions

Cloud Cost Optimization: A Comprehensive Review of Strategies and Case Studies

Cloud computing has revolutionized the way organizations manage their IT infrastructure, but it has also introduced new challenges, such as managing cloud costs. This paper explores various techniques for cloud cost optimization, including cloud pricing, analysis, and strategies for resource allocation. Real-world case studies of these techniques are presented, along with a discussion of their effectiveness and key takeaways. The analysis conducted in this paper reveals that organizations can achieve significant cost savings by adopting cloud cost optimization techniques. Additionally, future research directions are proposed to advance the state of the art in this important field

Rise of the Planet of Serverless Computing: A Systematic Review

Serverless computing is an emerging cloud computing paradigm, being adopted to develop a wide range of software applications. It allows developers to focus on the application logic in the granularity of function, thereby freeing developers from tedious and error-prone infrastructure management. Meanwhile, its unique characteristic poses new challenges to the development and deployment of serverless-based applications. To tackle these challenges, enormous research efforts have been devoted. This paper provides a comprehensive literature review to characterize the current research state of serverless computing. Specifically, this paper covers 164 papers on 17 research directions of serverless computing, including performance optimization, programming framework, application migration, multi-cloud development, testing and debugging, etc. It also derives research trends, focus, and commonly-used platforms for serverless computing, as well as promising research opportunities

CLOUD LIVE VIDEO TRANSFER

As multimedia content continues to grow, considerations for more effective storage options, like cloud technologies, become apparent. While video has become a mainstream media source on the web, live video streaming is growing as a prominent player in the modern marketplace for both businesses and individuals. For instance, a business owner may want to oversee operations while he or she is away, or an individual may want to surveillance their property. In this work, we propose Cloud Live Video Streaming (CLVS) - a very efficient method to stream live video that creates a separate pricing model from modern video streaming services. The key component to CLVS is Amazon Simple Storage Service (S3), which is used to store video segments and metadata. By using S3, CLVS employs what is referred to as a ”serverless” design by removing the need to stream video through an intermediary server. CLVS also removes the need for third party accounts and license agreements. We implement a prototype of CLVS and compare it with an existing commercial video streaming software - Wowza Streaming Engine. As live video streaming becomes more common, alternative and cost effective solutions are essential