Evaluation of IoT Measurement Solutions from a Metrology Perspective

To professionally plan and manage the development and evolution of the Internet of Things(IoT),researchers have proposed several IoT performance measurement solutions.IoT performance measurement solutions can be very valuable for managing the development and evolution of IoT systems,as they provide insights into performance issues,resource optimization,predictive maintenance,security,reliability,and user experience.However,there are several issues that can impact the accuracy and reliability of IoT performance measurements,including lack of standardization,complexity of IoT systems,scalability,data privacy,and security.While previous studies proposed several IoT measurement solutions in the literature,they did not evaluate any individual one to figure out their respective measurement strengths and weaknesses.This study provides a novel scheme for the evaluation of proposed IoT measurement solutions using a metrology-coverage evaluation based on evaluation theory,metrology principles,and software measurement best practices.This evaluation approach was employed for 12 IoT measure categories and 158 IoT measurement solutions identified in a Systematic Literature Review(SLR)from 2010 to 2021.The metrology coverage of these IoT measurement solutions was analyzed from four perspectives:across IoT categories,within each study,improvement over time,and implications for IoT practitioners and researchers.The criteria in this metrology-coverage evaluation allowed for the identification of strengths and weaknesses in the theoretical and empirical definitions of the proposed IoT measurement solutions.We found that the metrological coverage varies significantly across IoT measurement solution categories and did not show improvement over the 2010–2021 timeframe.Detailed findings can help practitioners understand the limitations of the proposed measurement solutions and choose those with stronger designs.These evaluation results can also be used by researchers to improve current IoT measurement solution designs and suggest new solutions with a stronger metrology base.

Multiperspective Representation of Internal Controls in Business Processes

The internal control process, which is designed to help an organization accomplish specific control objectives, is one of the most important processes, as it can determine whether or not the organization is in compliance with its internal or external requirements. Internal controls emerge from different perspectives. Currently, experts view and act on one control perspective at a time, which creates inefficiencies and duplication. This software engineering research is aimed at proposing a multiperspective framework for representing internal controls, in order to obtain a centralized and comprehensive view of all internal control mechanisms. To carry out this research, we also needed to represent the many different stakeholder perspectives of internal controls. Based on a literature review of mathematical and psychological analysis, we searched for the most suitable multiperspective representation of internal controls, and assessed the many representation options using the AHP (analytical hierarchical process) sensitivity analysis approach. This approach has been applied to a study group which has been called to answer to a questionnaire.

Design of a Performance Measurement Framework for Cloud Computing

Cloud Computing is an emerging technology for processing and storing very large amounts of data. Sometimes anomalies and defects affect part of the cloud infrastructure, resulting in a performance degradation of the cloud. This paper proposes a performance measurement framework for Cloud Computing systems, which integrates software quality concepts from ISO 25010.

A Privacy-Preserving System Design for Digital Presence Protection

A person’s privacy has become a growing concern,given the nature of an expansive reliance on real-time video activities with video capture,stream,and storage.This paper presents an innovative system design based on a privacy-preserving model.The proposed system design is implemented by employing an enhanced capability that overcomes today’s single parameterbased access control protection mechanism for digital privacy preservation.The enhanced capability combines multiple access control parameters:facial expression,resource,environment,location,and time.The proposed system design demonstrated that a person’s facial expressions combined with a set of access control rules can achieve a person’s privacy-preserving preferences.The findings resulted in different facial expressions successfully triggering a person’s face to be blurred and a person’s privacy when using a real-time video conferencing service captured from a webcam or virtual webcam.A comparison analysis of capabilities between existing designs and the proposed system design shows enhancement of the capabilities of the proposed system.A series of experiments exercising the enhanced,real-time multi-parameterbased system was shown as a viable path forward for preserving a person’s privacy while using a webcam or virtual webcam to capture,stream,and store videos.

A Data Security Framework for Cloud Computing Services

Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industry adoption and migration of traditional computing services to the cloud,one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies.This work proposes a Data Security Framework for cloud computing services(CCS)that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS.This framework is developed by means of a methodology based on a heuristic theory that incorporates knowledge generated by existing works as well as the experience of their implementation.The paper presents the design details of the framework,which consists of three stages:identification of data security requirements,management of data security risks and evaluation of data security performance in CCS.

A Three-Dimensional Performance Measurement Model for Cloud Computing

New paradigms for processing and storing data such as cloud computing require new approaches for the measurement of cloud service performance. To establish a Service Level Agreement (SLA) between a cloud service provider and its customers, the cloud services and their service level objectives need to be identified. An additional challenge in the performance measurement of cloud services is the lack of models that integrate the different perspectives of providers, maintainers and customers within the same model in order to define the concepts commonly used in cloud SLA contracts. This work proposes a three-dimensional Performance Measurement Model for Cloud Computing (P2M2C-3D) which consolidates performance measurement from the perspectives of providers, maintainers and customers for the different types of cloud services.