scholarly journals Architecting Software for the Internet of Thing Based Systems

2019 ◽  
Vol 11 (7) ◽  
pp. 153 ◽  
Author(s):  
Abdulrahman Alreshidi ◽  
Aakash Ahmad
Keyword(s):  
Software Architecture ◽  
State Of The Art ◽  
Autonomous Systems ◽  
The State ◽  
Design Development ◽  
Mapping Study ◽  
Agent Based ◽  
Research Themes ◽  
Human Decision ◽  
Internet Of Thing

Context—Internet of Thing (IoT) based systems support any-time/place computations by interconnecting humans, systems, services, devices, and things that enabling autonomous systems to shape-up digitized societies. Software architecture, as the blue-print of software-intensive systems, abstracts the complexities of modeling, design, development, and evolution phases of a software to engineer complex IoT driven systems effectively and efficiently. Objectives and Method—Research and development efforts are required to exploit architectural principle and practices to design and develop IoT systems to go beyond the state-of-the-art for IoTs. The objectives of this research are to empirically investigate and systematically classify the state-of-the-art on architecting IoT based software. We have used the Evidence Based Software Engineering (EBSE) method to conduct a mapping study of the existing IoT solutions by investigating 88 qualitatively selected studies. Results and Implications—The results of the mapping study highlight various research themes that exploit software architecture models to develop IoT systems. The identified research themes include, but are not limited to, cloud-based software ecosystems, software defined networking, autonomous, and adaptive software and agent-based systems that IoTs drive. The mapping study suggests that futuristic research on architecting IoT software is focused on architectural languages and patterns that support reusability, automation, and human decision support to develop and dynamically adapt IoT software. The mapping study represents a concentrated knowledge regarding architectural principle and practices to facilitate knowledge transfer—benefiting researchers and practitioners—on the role of software architecture for IoT systems.

scholarly journals Towards a framework for certification of reliable autonomous systems

2020 ◽  
Author(s):  
Michael Fisher ◽  
Viviana Mascardi ◽  
Kristin Yvonne Rozier ◽  
Bernd-Holger Schlingloff ◽  
Michael Winikoff ◽  
...  
Keyword(s):  
Everyday Life ◽  
Case Studies ◽  
Autonomous System ◽  
State Of The Art ◽  
Autonomous Systems ◽  
The State ◽  
Automated Verification ◽  
Unmanned Aerial System ◽  
Computational System ◽  
Regulatory Guidelines

AbstractA computational system is called autonomous if it is able to make its own decisions, or take its own actions, without human supervision or control. The capability and spread of such systems have reached the point where they are beginning to touch much of everyday life. However, regulators grapple with how to deal with autonomous systems, for example how could we certify an Unmanned Aerial System for autonomous use in civilian airspace? We here analyse what is needed in order to provide verified reliable behaviour of an autonomous system, analyse what can be done as the state-of-the-art in automated verification, and propose a roadmap towards developing regulatory guidelines, including articulating challenges to researchers, to engineers, and to regulators. Case studies in seven distinct domains illustrate the article.

scholarly journals BioDynaMo: an agent-based simulation platform for scalable computational biology research

2020 ◽  
Author(s):  
Lukas Breitwieser ◽  
Ahmad Hesam ◽  
Jean de Montigny ◽  
Vasileios Vavourakis ◽  
Alexandros Iosif ◽  
...  
Keyword(s):  
Software Design ◽  
Neural Development ◽  
State Of The Art ◽  
Biological Systems ◽  
The State ◽  
Single Server ◽  
Simulation Platform ◽  
Agent Based ◽  
Simulation Engine ◽  
Spheroid Growth

AbstractComputer simulation is an indispensable tool for studying complex biological systems. In particular, agent-based modeling is an attractive method to describe biophysical dynamics. However, two barriers limit faster progress. First, simulators do not always take full advantage of parallel and heterogeneous hardware. Second, many agent-based simulators are written with a specific research problem in mind and lack a flexible software design. Consequently, researchers have to spend an unnecessarily long time implementing their simulation and have to compromise either on model resolution or system size.We present a novel simulation platform called BioDynaMo that alleviates both of these problems researchers face in computer simulation of complex biological systems. BioDynaMo features a general-purpose and high-performance simulation engine. The engine simulates cellular elements, their interactions within a 3D physical environment, and their cell-internal genetic dynamics. Cell-internal dynamics can be described in C++ code or using system biology markup language (SBML).We demonstrate BioDynaMo’s wide range of application with three example use cases: soma clustering, neural development, and tumor spheroid growth. We validate our results with experimental data, and evaluate the performance of the simulation engine. We compare BioDynaMo’s performance with a state-of-the-art baseline, and analyze its scalability. We observe a speedup of 20–124× over the state-of-the-art baseline using one CPU core and a parallel speedup between 67× and 76× using 72 physical CPU cores with hyperthreading enabled. Combining these two results, we conclude that, on our test system, BioDynaMo is at least three orders of magnitude faster than the state-of-the-art serial baseline. These improvements make it feasible to simulate neural development with 1.24 billion agents on a single server with 1TB memory, and 12 million agents on a laptop with 16GB memory.BioDynaMo is an open-source project under the Apache 2.0 license and is available at www.biodynamo.org.Author summaryComputer simulations of biological systems are crucial to gain insights into complex processes of living organisms. However, the development of increasingly large and complex simulations is a difficult task, partly because a strong background in biology as well as computer science is required. In this paper, we introduce BioDynaMo, an agent-based simulation platform with which life scientists can create simulations that are three orders of magnitude faster than the state-of-the-art baseline. By taking advantage of the latest developments in computing hardware, we build a platform that is highly optimized. This enables the simulation of 1.24 billion agents on a single server and 12 million agents on a laptop. BioDynaMo places a lot of focus on hiding computational complexity and providing an easy-to-use interface, such that the life scientist can concentrate on biological aspects, rather than computational. BioDynaMo helps scientists to translate an idea quickly into a simulation by providing common building blocks, and a modular and extensible software design. We analyze the performance of the platform and demonstrate the capabilities with three example use cases: soma clustering, neural development, and tumor spheroid growth. The results support the view that BioDynaMo will help open up new research opportunities for large-scale biological simulations.

scholarly journals Towards a framework for certification of reliable autonomous systems

2020 ◽  
Vol 35 (1) ◽  
Author(s):  
Michael Fisher ◽  
Viviana Mascardi ◽  
Kristin Yvonne Rozier ◽  
Bernd-Holger Schlingloff ◽  
Michael Winikoff ◽  
...  
Keyword(s):  
Everyday Life ◽  
Case Studies ◽  
Autonomous System ◽  
State Of The Art ◽  
Autonomous Systems ◽  
The State ◽  
Automated Verification ◽  
Unmanned Aerial System ◽  
Computational System ◽  
Regulatory Guidelines

AbstractA computational system is called autonomous if it is able to make its own decisions, or take its own actions, without human supervision or control. The capability and spread of such systems have reached the point where they are beginning to touch much of everyday life. However, regulators grapple with how to deal with autonomous systems, for example how could we certify an Unmanned Aerial System for autonomous use in civilian airspace? We here analyse what is needed in order to provide verified reliable behaviour of an autonomous system, analyse what can be done as the state-of-the-art in automated verification, and propose a roadmap towards developing regulatory guidelines, including articulating challenges to researchers, to engineers, and to regulators. Case studies in seven distinct domains illustrate the article.

scholarly journals Architecting an Agent-Based Fault Diagnosis Engine for IEC 61499 Industrial Cyber-Physical Systems

2021 ◽  
Vol 13 (8) ◽  
pp. 190
Author(s):  
Barry Dowdeswell ◽  
Roopak Sinha ◽  
Stephen G. MacDonell
Keyword(s):  
Software Architecture ◽  
Early Stage ◽  
Cyber Physical Systems ◽  
Diagnostic Tools ◽  
Design Development ◽  
Current Function ◽  
Agent Based ◽  
Physical Systems ◽  
Trade Offs ◽  
Iec 61499

IEC 61499 is a reference architecture for constructing Industrial Cyber-Physical Systems (ICPS). However, current function block development environments only provide limited fault-finding capabilities. There is a need for comprehensive diagnostic tools that help engineers identify faults, both during development and after deployment. This article presents the software architecture for an agent-based fault diagnostic engine that equips agents with domain-knowledge of IEC 61499. The engine encourages a Model-Driven Development with Diagnostics methodology where agents work alongside engineers during iterative cycles of design, development, diagnosis and refinement. Attribute-Driven Design (ADD) was used to propose the architecture to capture fault telemetry directly from the ICPS. A Views and Beyond Software Architecture Document presents the architecture. The Architecturally-Significant Requirement (ASRs) were used to design the views while an Architectural Trade-off Analysis Method (ATAM) evaluated critical parts of the architecture. The agents locate faults during both early-stage development and later provide long-term fault management. The architecture introduces dynamic, low-latency software-in-loop Diagnostic Points (DPs) that operate under the control of an agent to capture fault telemetry. Using sound architectural design approaches and documentation methods, coupled with rigorous evaluation and prototyping, the article demonstrates how quality attributes, risks and architectural trade-offs were identified and mitigated early before the construction of the engine commenced.

scholarly journals Towards a framework for certification of reliable autonomous systems

2020 ◽  
Author(s):  
Michael Fisher ◽  
Viviana Mascardi ◽  
Kristin Yvonne Rozier ◽  
Bernd-Holger Schlingloff ◽  
Michael Winikoff ◽  
...  
Keyword(s):  
Everyday Life ◽  
Case Studies ◽  
Autonomous System ◽  
State Of The Art ◽  
Autonomous Systems ◽  
The State ◽  
Automated Verification ◽  
Unmanned Aerial System ◽  
Computational System ◽  
Regulatory Guidelines

AbstractA computational system is called autonomous if it is able to make its own decisions, or take its own actions, without human supervision or control. The capability and spread of such systems have reached the point where they are beginning to touch much of everyday life. However, regulators grapple with how to deal with autonomous systems, for example how could we certify an Unmanned Aerial System for autonomous use in civilian airspace? We here analyse what is needed in order to provide verified reliable behaviour of an autonomous system, analyse what can be done as the state-of-the-art in automated verification, and propose a roadmap towards developing regulatory guidelines, including articulating challenges to researchers, to engineers, and to regulators. Case studies in seven distinct domains illustrate the article.

scholarly journals Privacy Assessment in Android Apps: A Systematic Mapping Study

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1999
Author(s):  
Jose M. Del Alamo ◽  
Danny Guaman ◽  
Belen Balmori ◽  
Ana Diez
Keyword(s):  
State Of The Art ◽  
Personal Data ◽  
The State ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Research Directions ◽  
Android Apps ◽  
Body Of Knowledge ◽  
Research Domains

Android apps are daily installed by billions of users worldwide, who grant access to an extensive set of sensitive personal data. Different techniques have been developed over the years to understand how apps protect or harm their users’ privacy. However, these results have been produced in different research domains and addressing privacy from different perspectives, resulting in a growing but scattered body of knowledge. To bridge this gap, we have carried out a systematic mapping study to provide practitioners and researchers with an overview of the state-of-the-art technique, published between 2016 and 2020, to assess privacy in Android apps. In this paper, we highlight the most relevant findings, identify and analyse the most pressing gaps, and discuss the promising research directions.

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