A Delphi study to recognize and assess systems of systems vulnerabilities

Context: System of Systems (SoS) is an emerging paradigm by which independent systems collaborate by sharing resources and processes to achieve objectives that they could not achieve on their own. In this context, a number of emergent behaviors may arise that can undermine the security of the constituent systems. Objective: We apply the Delphi method with the aims to improve our understanding of SoS security and related problems, and to investigate their possible causes and remedies. Method: Experts on SoS expressed their opinions and reached consensus in a series of rounds by following a structured questionnaire. Results: The results show that the experts found more consensus in disagreement than in agreement about some SoS characteristics, and on how SoS vulnerabilities could be identified and prevented. Conclusions: From this study we learn that more work is needed to reach a shared understanding of SoS vul nerabilities, and we leverage expert feedback to outline some future research directions.Ministerio de Ciencia, Innovación y Universidades PID2019-105455GB-C3

A quality of experience approach in smartphone video selection framework for energy efficiency

Online video streaming is getting more common in the smartphone device nowadays. Since the Corona Virus (COVID-19) pandemic hit all human across the globe in 2020, the usage of online streaming among smartphone user are getting more vital. Nevertheless, video streaming can cause the smartphone energy to drain quickly without user to realize it. Also, saving energy alone is not the most significant issues especially if with the lack of attention on the user Quality of Experience (QoE). A smartphones energy management is crucial to overcome both of these issues. Thus, a QoE Mobile Video Selection (QMVS) framework is proposed. The QMVS framework will govern the tradeoff between energy efficiency and user QoE in the smartphone device. In QMVS, video streaming will be using Dynamic Video Attribute Pre-Scheduling (DVAP) algorithm to determine the energy efficiency in smartphone devices. This process manages the video attribute such as brightness, resolution, and frame rate by turning to Video Content Selection (VCS). DVAP is handling a set of rule in the Rule Post-Pruning (RPP) method to remove an unused node in list tree of VCS. Next, QoE subjective method is used to obtain the Mean Opinion Score (MOS) of users from a survey experiment on QoE. After both experiment results (MOS and energy) are established, the linear regression technique is used to find the relationship between energy consumption and user QoE (MOS). The last process is to analyze the relationship of VCS results by comparing the DVAP to other recent video streaming applications available. Summary of experimental results demonstrate the significant reduction of 10% to 20% energy consumption along with considerable acceptance of user QoE. The VCS outcomes are essential to help users and developer deciding which suitable video streaming format that can satisfy energy consumption and user QoE

A Systematic Literature Review on the Description of Software Architectures for Systems of Systems

International audienc