5,595 research outputs found
Service Prototyping Lab Report - 2018 (Y3)
The annual activity report of the Service Prototyping Lab at Zurich University of Applied Sciences. Research trends and initiatives, research projects, transfer to education and local industry, academic community involvement, qualification and scientific development over the period of one year are among the covered topics
Software-Defined Networks for Future Networks and Services: Main Technical Challenges and Business Implications
In 2013, the IEEE Future Directions Committee (FDC) formed an SDN work group to explore the amount of interest in forming an IEEE Software-Defined Network (SDN) Community. To this end, a Workshop on "SDN for Future Networks and Services" (SDN4FNS'13) was organized in Trento, Italy (Nov. 11th-13th 2013). Following the results of the workshop, in this paper, we have further analyzed scenarios, prior-art, state of standardization, and further discussed the main technical challenges and socio-economic aspects of SDN and virtualization in future networks and services. A number of research and development directions have been identified in this white paper, along with a comprehensive analysis of the technical feasibility and business availability of those fundamental technologies. A radical industry transition towards the "economy of information through softwarization" is expected in the near future
On Evaluating Commercial Cloud Services: A Systematic Review
Background: Cloud Computing is increasingly booming in industry with many
competing providers and services. Accordingly, evaluation of commercial Cloud
services is necessary. However, the existing evaluation studies are relatively
chaotic. There exists tremendous confusion and gap between practices and theory
about Cloud services evaluation. Aim: To facilitate relieving the
aforementioned chaos, this work aims to synthesize the existing evaluation
implementations to outline the state-of-the-practice and also identify research
opportunities in Cloud services evaluation. Method: Based on a conceptual
evaluation model comprising six steps, the Systematic Literature Review (SLR)
method was employed to collect relevant evidence to investigate the Cloud
services evaluation step by step. Results: This SLR identified 82 relevant
evaluation studies. The overall data collected from these studies essentially
represent the current practical landscape of implementing Cloud services
evaluation, and in turn can be reused to facilitate future evaluation work.
Conclusions: Evaluation of commercial Cloud services has become a world-wide
research topic. Some of the findings of this SLR identify several research gaps
in the area of Cloud services evaluation (e.g., the Elasticity and Security
evaluation of commercial Cloud services could be a long-term challenge), while
some other findings suggest the trend of applying commercial Cloud services
(e.g., compared with PaaS, IaaS seems more suitable for customers and is
particularly important in industry). This SLR study itself also confirms some
previous experiences and reveals new Evidence-Based Software Engineering (EBSE)
lessons
ELECTRONIC REQUIREMENTS NEGOTIATION – A LITERATURE SURVEY ON THE STATE-OF-THE-ART (23)
In the software development process, requirements negotiation is an essential part in which stakeholders jointly have to come to an agreement. Such a negotiation process is often conducted using information systems, which makes it an electronic requirements negotiation process. The aim of the current paper is to present the state-of-the-art in electronic requirements negotiations. We elicit the state-of-the-art by analysing relevant literature, extracting areas of current research, and describing the status quo of each area. The identified areas of research are foundations of electronic requirements negotiation, electronic requirements negotiation methodology, automation of electronic requirements negotiation, computer- mediated communication, and social communication
Nature-Inspired Coordination Models: Current Status and Future Trends
Coordination models and languages are meant to provide abstractions and mechanisms to harness the space of interaction as one of the foremost sources of complexity in computational systems. Nature-inspired computing aims at understanding the mechanisms and patterns of complex natural systems in order to bring their most desirable features to computational systems. Thus, the promise of nature-inspired coordination models is to prove themselves fundamental in the design of complex computational systems|such as intelligent, knowledge-intensive, pervasive, adaptive, and self-organising ones. In this paper, we survey the most relevant nature-inspired coordination models in the literature, focussing in particular on tuple-based models, and foresee the most interesting research trends in the field
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
Interorganizational Information Systems: Systematic Literature Mapping Protocol
Organizations increasingly need to establish partnerships with other organizations to face environment changes and remain competitive. This interorganizational relationship allows organizations to share resources and collaborate to handle business opportunities better. This technical report present the protocol of the systematic mapping performed to understand what is an IOIS and how these systems support interorganizational relationships
Guidelines for the Search Strategy to Update Systematic Literature Reviews in Software Engineering
Context: Systematic Literature Reviews (SLRs) have been adopted within
Software Engineering (SE) for more than a decade to provide meaningful
summaries of evidence on several topics. Many of these SLRs are now potentially
not fully up-to-date, and there are no standard proposals on how to update SLRs
in SE. Objective: The objective of this paper is to propose guidelines on how
to best search for evidence when updating SLRs in SE, and to evaluate these
guidelines using an SLR that was not employed during the formulation of the
guidelines. Method: To propose our guidelines, we compare and discuss outcomes
from applying different search strategies to identify primary studies in a
published SLR, an SLR update, and two replications in the area of effort
estimation. These guidelines are then evaluated using an SLR in the area of
software ecosystems, its update and a replication. Results: The use of a single
iteration forward snowballing with Google Scholar, and employing as a seed set
the original SLR and its primary studies is the most cost-effective way to
search for new evidence when updating SLRs. Furthermore, the importance of
having more than one researcher involved in the selection of papers when
applying the inclusion and exclusion criteria is highlighted through the
results. Conclusions: Our proposed guidelines formulated based upon an effort
estimation SLR, its update and two replications, were supported when using an
SLR in the area of software ecosystems, its update and a replication.
Therefore, we put forward that our guidelines ought to be adopted for updating
SLRs in SE.Comment: Author version of manuscript accepted for publication at the
Information and Software Technology Journa
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