Optimized Strategy in Cloud-Native Environment for Inter-Service Communication in Microservices

Cloud computing has become a prominent technology in the software development industry. The term “cloud-native” is derived from cloud computing technologies and refers to the development and deployment of applications in a cloud environment. In the software industry, most enterprise-grade software buildings use the microservice architecture and cloud natively, ultimately leading to an expansive development in the software development framework. Microservices are deployed in a distributed environment and function as independent services. However, they need to communicate with each other in order to fulfill the functional requirement. Additional latency will be introduced when communicating with other services. Hence, it will impact the overall application response time and throughput. This research proposes a solution for the aforementioned problem in the cloud-native environment. A Request-response-based TCP communication solution has been developed and tested in the cloud-native, containerized environment. Experimental results showed that the turnaround time of the proposed solution is shorter than that of traditional HTTP communication methods. Furthermore, the results summarize that both vertical and horizontal scaling are improving the overall performance of the systems performance in terms of response time. Conclusively, the proposed solution improved the microservice performance and preserved the existing cloud-native qualities, such as scalability, maintainability, and portability

Revitalizing Legacy Systems: Extracting Key Features for Software Transplantation

The creation of intelligent software depends on the ability to transfer software without any restrictions. In this article, a crucial stage in software engineering, the feature extraction for effective software transplantation, is discussed. As hardware, operating systems, or other factors change, it is commonly necessary to move software from one environment to another. It is vital to identify and extract the relevant software characteristics, which might be challenging given how complex software is, in order to carry out efficient software transplantation. On the other hand, the procedure to extract these attributes from the software might be time-consuming and need extensive understanding. To address this, we propose a transplantation strategy that prioritizes automation with the help of AWS. Our approach involves an agent running on the application server (on-premises). It performs the task of feature identification, extraction and deployment on AWS Cloud. Currently, our strategy is confined to Java and .NET applications

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

Building Blocks to Empower Cognitive Internet with Hybrid Edge Cloud

As we transition from the mobile internet to the 'Cognitive Internet,' a significant shift occurs in how we engage with technology and intelligence. We contend that the Cognitive Internet goes beyond the Cognitive Internet of Things (Cognitive IoT), enabling connected objects to independently acquire knowledge and understanding. Unlike the Mobile Internet and Cognitive IoT, the Cognitive Internet integrates collaborative intelligence throughout the network, blending the cognitive IoT realm with system-wide collaboration and human intelligence. This integrated intelligence facilitates interactions between devices, services, entities, and individuals across diverse domains while preserving decision-making autonomy and accommodating various identities. The paper delves into the foundational elements, distinct characteristics, benefits, and industrial impact of the 'Cognitive Internet' paradigm. It highlights the importance of adaptable AI infrastructures and hybrid edge cloud (HEC) platforms in enabling this shift. This evolution brings forth cognitive services, a Knowledge as a Service (KaaS) economy, enhanced decision-making autonomy, sustainable digital progress, advancements in data management, processing techniques, and a stronger emphasis on privacy. In essence, this paper serves as a crucial resource for understanding and leveraging the transformative potential of HEC for Cognitive Internet. Supported by case studies, forward-looking perspectives, and real-world applications, it provides comprehensive insights into this emerging paradigm

Microservices based architecture and mobile application to suport crew and vessel inspections

Tese de mestrado, Engenharia Informática, 2023, Universidade de Lisboa, Faculdade de CiênciasWith the ever increasing importance of the maritime services around the world, the need to control and monitor ports and vessels is born, thus allowing to increase/improve the level of productivity, reliability, safety and security in this field. When it comes to safety and security, vessel monitoring is one of the most important parts that enables the respective authorities to verify and validate the vessels, their crews, and their missions through vessel inspections. These vessel inspection missions, as they can be carried out in various areas of the coastal zone, are subject to limitations that are not encountered in normal situations, such as adverse weather conditions or lack of connection to the network and therefore to the servers that support these types of inspections and store the relevant information. Another limitation that arises from this lack of connection, is the secure authentication of the inspectors and maintaining the access to the information. Also due to the increase in the number of vessels, there may be scalability problems with the backend systems. To help solve these problems, a backend architecture based on microservices and a mobile application were developed to support the inspectors by providing all the information, in a secure way, that is needed to perform the inspections, whether the inspector is in areas that have, or not, access to the network (online or offline). The developed architecture consists of several independent microservices, deployed through a Kubernetes cluster, and that supports the mobile application used by the inspectors, allowing the inspectors to store and have access to the inspection information about the vessels, crews, vessel licenses and predictions about possible future inspection targets, for a limited period of time after the beginning of the inspection, thus improving security

A software architecture for electro-mobility services: a milestone for sustainable remote vehicle capabilities

To face the tough competition, changing markets and technologies in automotive industry, automakers have to be highly innovative. In the previous decades, innovations were electronics and IT-driven, which increased exponentially the complexity of vehicle’s internal network. Furthermore, the growing expectations and preferences of customers oblige these manufacturers to adapt their business models and to also propose mobility-based services. One other hand, there is also an increasing pressure from regulators to significantly reduce the environmental footprint in transportation and mobility, down to zero in the foreseeable future. This dissertation investigates an architecture for communication and data exchange within a complex and heterogeneous ecosystem. This communication takes place between various third-party entities on one side, and between these entities and the infrastructure on the other. The proposed solution reduces considerably the complexity of vehicle communication and within the parties involved in the ODX life cycle. In such an heterogeneous environment, a particular attention is paid to the protection of confidential and private data. Confidential data here refers to the OEM’s know-how which is enclosed in vehicle projects. The data delivered by a car during a vehicle communication session might contain private data from customers. Our solution ensures that every entity of this ecosystem has access only to data it has the right to. We designed our solution to be non-technological-coupling so that it can be implemented in any platform to benefit from the best environment suited for each task. We also proposed a data model for vehicle projects, which improves query time during a vehicle diagnostic session. The scalability and the backwards compatibility were also taken into account during the design phase of our solution. We proposed the necessary algorithms and the workflow to perform an efficient vehicle diagnostic with considerably lower latency and substantially better complexity time and space than current solutions. To prove the practicality of our design, we presented a prototypical implementation of our design. Then, we analyzed the results of a series of tests we performed on several vehicle models and projects. We also evaluated the prototype against quality attributes in software engineering