Deployment Of Components Research Articles

Multi-objective fault-tolerant optimization algorithm for deployment of IoT applications on fog computing infrastructure

Nowadays, fog computing as a complementary facility of cloud computing has attracted great attentions in research communities because it has extraordinary potential to provide resources and processing services requested for applications at the edge network near to users. Recent researchers focus on how efficiently engage edge networks capabilities for execution and supporting of IoT applications and associated requirement. However, inefficient deployment of applications’ components on fog computing infrastructure results bandwidth and resource wastage, maximum power consumption, and unpleasant quality of service (QoS) level. This paper considers reduction of bandwidth wastage in regards to application components dependency in their distributed deployment. On the other hand, the service reliability is declined if an application’s components are deployed on a single node for the sake of power consumption management viewpoint. Therefore, a mechanism for tackling single point of failure and application reliability enhancement against failure are presented. Then, the components deployment is formulated to a multi-objective optimization problem with minimization perspective of both power consumption and total latency between each pair of components associated to applications. To solve this combinatorial optimization problem, a multi-objective cuckoo search algorithm (MOCSA) is presented. To validate the work, this algorithm is assessed in different conditions against some state-of the arts. The simulation results prove the amount 42%, 29%, 46%, 13%, and 5% improvement of proposed MOCSA in terms of average overall latency respectively against MOGWO, MOGWO-I, MOPSO, MOBA, and NSGA-II algorithms. Also, in term of average total power consumption the improvement is about 43%, 28%, 41%, 30%, and 32% respectively.

A High Step-Up Switched Z-Source Converter (HS-SZC) with Minimal Components Count for Enhancing Voltage Gain

Some applications such as fuel cells or photovoltaic panels offer low output voltage, and it is essential to boost this voltage before connecting to the grid through an inverter. The Z-network converter can be used for the DC-DC conversion to enhance the output voltage of renewable energy sources. However, boosting capabilities of traditional Z-network boost converters are limited, and the utilization of higher parts count makes it bulky and expensive. In this paper, an efficient, high step-up, switched Z-source DC-DC boost converter (HS-SZC) is presented, which offers a higher boost factor at a smaller duty ratio and avoids the instability due to the saturation of inductors. In the proposed converter, the higher voltage gain is achieved by using one inductor and switch at the back end of the conventional Z-source DC-DC converter (ZSC). The idea is to utilize the output capacitor for filtering and charging and discharging loops. Moreover, the proposed converter offers a wider range of load capacity, thus minimizing the power losses and enhancing efficiency. This study simplifies the structure of conventional Z-source converters through the deployment of fewer components, and hence making it more cost-effective and highly efficient, compared to other DC-DC boost converters. Furthermore, a comparison based on the boosting capability and number of components is provided, and the performance of the proposed design is analyzed with non-ideal elements. Finally, simulation and experimental studies are carried out to evaluate and validate the performance of the proposed converter.

Runtime Safety Monitoring of Neural-Network-Enabled Dynamical Systems.

Complex dynamical systems rely on the correct deployment and operation of numerous components, with state-of-the-art methods relying on learning-enabled components in various stages of modeling, sensing, and control at both offline and online levels. This article addresses the runtime safety monitoring problem of dynamical systems embedded with neural-network components. A runtime safety state estimator in the form of an interval observer is developed to construct the lower bound and upper bound of system state trajectories in runtime. The developed runtime safety state estimator consists of two auxiliary neural networks derived from the neural network embedded in dynamical systems, and observer gains to ensure the positivity, namely, the ability of the estimator to bound the system state in runtime, and the convergence of the corresponding error dynamics. The design procedure is formulated in terms of a family of linear programming feasibility problems. The developed method is illustrated by a numerical example and is validated with evaluations on an adaptive cruise control system.

Energy Insecurity: Problems & Remedial Actions [Guest Editorial

The articles in this special section focus on power system security. As the power industry moves from a capacity-limited to an energyconstrained generation mix, diverse situations impact energy security. Environmental considerations may prevent the deployment of components that increase the energy security level, e.g., nuclear or thermal units, or they may require the retirement of such components. Limited transmission capacity, outdated operational procedures, and/or limited storage availability may also significantly decrease the operational security level. The interaction of different energy systems is yet another emerging issue. For example, natural gas unavailability due to issues with natural gas sources or pipelines affects the operational capability of power systems with a significant share of renewable generation.

No-Need-To-Deploy UHF Antenna for CubeSat: Design Based on Characteristic Modes

This letter proposes a compact 435 MHz telemetry, tracking, and command (TT&C) CubeSat antenna, which does not require an in-orbit deployment mechanism for proper operation. It uses characteristic modes on spacecraft's body to increase the radiating aperture, resulting in a λ/4 sized antenna (as calculated along diagonal of the cube). The antenna aims to provide reliable communication, operating independently from spacecraft's orientation and does not rely on proper deployment of vulnerable mechanical components. The limited space in the launcher limits any protrusions to no more than 6 mm (1/115th of the wavelength) from the spacecraft's wall, which results in low input impedance of 0.4 - 3.2j. To overcome this issue, a differential feeding structure is proposed that incorporates a power divider with impedance matching circuit. It also incorporates a lumped capacitor that can adjust the antenna's operating frequency. The antenna offers a dipolelike radiation pattern with performances comparable to larger deployable UHF antennas. It is intended for reliable TT&C.

Qualification pathways for additively manufactured components for nuclear applications

This research paper evaluated three pathways for qualification of 316 L stainless steel components made by laser powder bed fusion additive manufacturing (AM). Comprehensive and consistent process flows with computational modeling, in-situ measurements, ex-situ characterization and mechanical testing with simple- and complex- geometries were explored. The role of post-process hot isostatic pressing (HIP), and solution anneal treatment were evaluated. By using HIP, the scatter in 316 L steel AM properties within single and complex components was minimized to meet the requirement of existing industry standards. For applications where HIP may not be feasible and with some extent of defect tolerance, alternative qualification methodologies of deploying l-PBF AM parts were also explored with samples made with and without engineered porosities. The data generated in this research will be relevant to deployment of AM components for emerging nuclear energy applications.

Real-Time Facial Expression Recognition Based on Edge Computing

In recent years, many large-scale information systems in the Internet of Things (IoT) can be converted into interdependent sensor networks, such as smart cities, smart medical systems, and industrial Internet systems. The successful application of edge computing in the IoT will make our algorithms faster, more convenient, lower overall costs, providing better business practices, and enhance sustainability. Facial action unit (AU) detection recognizes facial expressions by analyzing cues about the movement of certain atomic muscles in the local facial area. According to the detected facial feature points, we could calculate the values of AU, and then use classification algorithms for emotion recognition. In edge devices, using optimized and custom algorithms to directly process the raw image data from each camera, the detected emotions can be more easily transmitted to the end-user. Due to the tremendous network overhead of transferring the facial action unit feature data, it poses challenges of a real-time facial expression recognition system being deployed in a distributed manner while running in production. Therefore, we designed a lightweight edge computing-based distributed system using Raspberry Pi tailed for this need, and we optimized the data transfer and components deployment. In the vicinity, the front-end and back-end processing modes are separated to reduce round-trip delay, thereby completing complex computing tasks and providing high-reliability, large-scale connection services. For IoT or smart city applications and services, they can be made into smart sensing systems that can be deployed anywhere with network connections.

From OBD to connected diagnostics: a game changer at fleet, vehicle and component level

Abstract Early on-board diagnostics (OBD) standards were enforced in 1988 and, by the beginning of the XXI century, all major automotive markets require some sort of OBD. Over the years, the diagnostics software layer has grown in complexity, yet robust fault detection remains a challenging task: insufficient memory and computation power, suboptimal calibration, and the lack of sufficient real-life operation data for model development are some of the limiting factors. The connected vehicle paradigm allows a complete reshaping of the vehicle diagnostics: real-life data feeds provide operation data of the vehicle fleet; artificial intelligence assists data clustering and model development; and over-the-air update tools allow the deployment of new software components and optimized calibration. A smart combination of embedded and cloud components seems to be a major step forward for the next generation of vehicles, allowing the determination of the in-service emissions at vehicle and fleet level. While many challenges are still to be solved, connectivity offers a giant leap in the area of vehicular diagnostics.

The Language and Mythology of The City in The Lyrics by Alexander Blok: The Case Study of Russian Language

The urban text is of particular importance in the development of the meta-plot of the second volume of Blok's humanization trilogy. The correlation of the language and mythology of the city with the symbol of the elements implies the deployment of the destructive component of the elements. The symbolic images of the Serpent, the bronze horseman as well as sunset symbolism become the meaning-and structure-forming centre. The analysis of the city's mythology and linguistic features in the context of the second volume of Blok's lyrics makes it possible to trace the development of the general meta-plot and, at the same time, to identify the specific features of the functioning of the mythology under study. The sense-forming dominants determine the specifics of the chronotopic and symbolic-associative deployment of mythologemes. The movement of light symbols in the structure of the second volume makes it possible to consider the transformation of the primary system of symbols that define the Blok's meta-plot.

A stakeholder-oriented security analysis in virtualized 5G cellular networks

Besides significantly outperforming past generations in terms of capacity and throughput, 5G networks and systems will provide an infrastructure for the support of highly diversified services and “verticals”. Indeed, the major paradigm shift with respect to previous cellular network generations, specifically oriented to one class of terminals (namely, people’s cell phones), is the largely heterogeneous nature of the multiplicity of end systems supported. Within a 5G infrastructure, playing the role of “network of networks”, traditionally independent technical and business stakeholders are now called to cooperate in the deployment of crucial infrastructure components relying on innovative (for the Telecom world) technologies such as virtualization, not in the traditional operators’ portfolio, and eventually placed in security-critical parts of the network — think e.g. to Multi Access Edge Computing systems. Goal of this survey is to analyze the complex threat landscape of 5G systems, by taking the point of view of the involved stakeholders. The motivation behind our proposed analysis revolves on the observation that, in complex and virtualized systems such as the 5G infrastructure, an attack to a system component under the responsibility of a given stakeholder may yield a dramatic impact to a completely different player. Therefore, while reviewing the many 5G security risks and relevant threats which the main stakeholders operating in virtualized 5G cellular networks are exposed to, we will try to showcase the sometimes non-obvious relation between impact and responsibility, as well as identify shared responsibilities.

Multi-objective Beam-ACO for Maximising Reliability and Minimising Communication Overhead in the Component Deployment Problem

Automated deployment of software components into hardware resources is a highly constrained optimisation problem. Hardware memory limits which components can be deployed into the particular hardware unit. Interacting software components have to be deployed either into the same hardware unit, or connected units. Safety concerns could restrict the deployment of two software components into the same unit. All these constraints hinder the search for high quality solutions that optimise quality attributes, such as reliability and communication overhead. When the optimisation problem is multi-objective, as it is the case when considering reliability and communication overhead, existing methods often fail to produce feasible results. Moreover, this problem can be modelled by bipartite graphs with complicating constraints, but known methods do not scale well under the additional restrictions. In this paper, we develop a novel multi-objective Beam search and ant colony optimisation (Beam-ACO) hybrid method, which uses problem specific bounds derived from communication, co-localisation and memory constraints, to guide the search towards feasibility. We conduct an experimental evaluation on a range of component deployment problem instances with varying levels of difficulty. We find that Beam-ACO guided by the co-localisation constraint is most effective in finding high quality feasible solutions.

Удосконалення підготовки військових частин і підрозділів морської компоненти Сил спеціальних операцій Збройних Сил України за досвідом участі в міжнародних навчаннях “SEA-BREEZE” (2018–2019 рр.)

In the context of the ongoing armed aggression of the Russian Federation against Ukraine, in particular, from the naval direction, the military-political leadership of the state is forced to revise the main guidelines for the development of the Operations Forces (SSO) of the Armed Forces of Ukraine and pay more attention to which are performed in peacetime and in the Special Period. The lack of sufficient experience in the training and deployment of naval components of the Operations Forces of the Armed Forces of Ukraine according to NATO standards significantly reduces their level of readiness and makes it difficult to achieve compatibility with similar structures of NATO member states. The urgency of this topic is due to the presence in the Operations Forces of the Armed Forces of Ukraine of military units and units that are designed to conduct reconnaissance and sabotage operations in the naval direction and require training for use according to NATO standards. The purpose of the article is to highlight the experience of participation of the tactical group of Operations Forces of the Armed Forces of Ukraine in the international exercises Sea-Breeze in 2018-2019. Base on this experience providing recommendations for further improvement of training of military units and subdivisions of the naval component of the Operations Forces of the Armed Forces of Ukraine. To improve the training of military units and units of the naval component of the Operations Forces of the Armed Forces of Ukraine during participation in international exercises and application during the Joint Forces Operation, it is proposed to include the positive experience of these exercises in the Guidelines for International Exercises.

Innovating Across Technologies: How Systems Integrators Increase Outsourced Components’ Innovations?

This study addresses the question of how firms taking the role of systems integrators can increase innovativeness by adding new features to their products from outsourced components. We focus on a sample of global automotive manufacturers which have systematically outsourced production of several key components while at the same time remained active in terms of innovation efforts around these component technologies. We provide evidence that as systems integrators increase innovation efforts around outsourced components, they are able to increase new outsourced component introductions that provide important new features to their final products. Yet, we also investigate how systems integrators manage their search efforts regarding these outsourced components’ technologies. We find that while increasing search from suppliers’ knowledge base for innovation is beneficial to a greater deployment of new components, increasing search from competitors in this context has a detrimental effect on the frequency of new outsourced components’ introductions.

Securing Cyberspace of Future Smart Cities with 5G Technologies

Future smart cities promise to dramatically improve the quality of life and have been attracting the attention of many researchers in recent years. The integration of IoT with their corresponding service delivery models to manage a city's asset securely remains a significant challenge. The deployment of diverse IoT technologies and several architectural components and novel entities of emerging ICT solutions opens up new security threats and vulnerabilities. Large-scale, seamless communication among multiple IoT technologies is highly dependent on the operations of the underlying wireless access technologies such as WSNs, SDR, CR and RFID. We present thematic layered taxonomies to highlight the potential security vulnerabilities, attacks, and challenges of key IoT enabling technologies which underpin the development of smart cities. We also identify potential requirements and key enablers that play a vital role in the development of secure smart cities. Finally, we discuss various open issues that need to be addressed to unlock the full potential of 5G for future smart cities.

An IoT Platform-as-a-Service for NFV-Based Hybrid Cloud/Fog Systems

Cloud computing, despite its inherent advantages (e.g., resource efficiency), still faces several challenges. The wide area network used to connect the cloud to end users could cause high latency, which may not be tolerable for some applications, especially Internet-of-Things (IoT) applications. Fog computing can reduce this latency by extending the traditional cloud architecture to the edge of the network and by enabling the deployment of some application components on fog nodes. Application providers use Platform-as-a-Service (PaaS) to provision (i.e., develop, deploy, manage, and orchestrate) applications in cloud. However, existing PaaS solutions (including IoT PaaS) usually focus on cloud and do not enable provisioning of applications with components spanning cloud and fog. Provisioning such applications requires novel functions, such as application graph generation, that are absent from existing PaaS. Furthermore, several functions offered by existing PaaS (e.g., publication/discovery) need to be significantly extended in order to fit in a hybrid cloud/fog environment. In this article, we propose a novel architecture for PaaS for hybrid cloud/fog system. It is IoT use case driven, and its applications' components are implemented as virtual network functions (VNFs) with execution sequences modeled as graphs with substructures, such as selection and loops. It automates the provisioning of applications with components spanning cloud and fog. In addition, it enables the discovery of existing cloud and fog nodes and generates application graphs. A proof of concept is built based on Cloudify open source. Feasibility is demonstrated by evaluating its performance when the PaaS modules and application components are placed in clouds and fogs in different geographical locations.

Safety and Feasibility of Percutaneous Purse-String-Like Downsizing for Femoral Access During Complex Endovascular Aortic Repair.

To describe a percutaneous "purse-string-like" technique to downsize the femoral access sheath achieving early pelvis and limb reperfusion during complex endovascular aortic repair, while maintaining a sheath in place. After ultrasound-guided femoral catheterization, two Perclose ProGlide vascular closure devices (VCD) are employed with the pre-close technique. When the deployment of aortic components is complete, the large delivery sheath is exchanged for a smaller non-occlusive one (≤ 10 F) and the rail suture of both VCDs is pulled to achieve hemostasis. At the end of the procedure, the access is closed according to standard technique. Fifty-eight femoral accesses were downsized achieving hemostasis with a completion percutaneous closure success of 95% (55/58). The median ischemic time to the limb was 66min (IQR 31-131) for the main access and 65min (IQR 30-100) for the contralateral one. When compared to a 1:2 propensity score-matched cohort who did not undergo access downsizing, no differences in closure success were recorded (95% vs. 89%, p = 0.19). However, hemostasis required more frequently an additional ProGlide in the downsizing group (26 cases, 45% vs. 17 cases, 15%; p < .001). Percutaneous purse-string-like sheath downsizing to restore perfusion to limbs and pelvis during complex endovascular aortic repair is feasible with high closure success rates, although a third ProGlide is more frequently needed to achieve hemostasis. The impact of this practice on SCI rates requires further evaluation in larger series as part of a multimodal approach for spinal cord protection.

An energy efficient service composition mechanism using a hybrid meta-heuristic algorithm in a mobile cloud environment

By increasing mobile devices in technology and human life, using a runtime and mobile services has gotten more complex along with the composition of a large number of atomic services. Different services are provided by mobile cloud components to represent the non-functional properties as Quality of Service (QoS), which is applied by a set of standards. On the other hand, the growth of the energy-source heterogeneity in mobile clouds is an emerging challenge according to the energy saving problem in mobile nodes. In order to mobile cloud service composition as an NP-Hard problem, an efficient selection method should be taken by problem using optimal energy-aware methods that can extend the deployment and interoperability of mobile cloud components. Also, an energy-aware service composition mechanism is required to preserve high energy saving scenarios for mobile cloud components. In this paper, an energy-aware mechanism is applied to optimize mobile cloud service composition using a hybrid Shuffled Frog Leaping Algorithm and Genetic Algorithm (SFGA). Experimental results capture that the proposed mechanism improves the feasibility of the service composition with minimum energy consumption, response time, and cost for mobile cloud components against some current algorithms.

Multi-Device Complementary View Adaptation with Liquid Media Queries

The design of responsive Web applications is traditionally based on the assumption that they run on a single client at a time. Thanks to CSS3 media queries, developers can declaratively specify how the Web application UI adapts to the capabilities of specific devices. As users own more and more devices and they attempt to use them to run Web applications in parallel, we propose to extend CSS media queries so that they can be used to adapt the UI of liquid Web applications while they are dynamically deployed across multiple devices.In this paper we present our extension of CSS media queries with liquid-related types and features, allowing to detect the number of devices connected, the number of users running the application, or the role played by each device. The liquid media query types and features defined in this paper are designed and suitable for liquid component-based Web architectures, and they enable developers to control the deployment of individual Web components across multiple browsers. Furthermore we show the design of liquid media queries in the Liquid.js for Polymer framework and propose our adaptation algorithms. We describe multiple adaptation policies and discuss the implications of the multi-device adaptation from the perspective of the developers and users of a Web application. Finally we showcase the expressiveness of the liquid media queries to support real-world examples and evaluate the algorithmic complexity of our approach.

Architecting and Deploying IoT Smart Applications: A Performance-Oriented Approach.

Layered internet of things (IoT) architectures have been proposed over the last years as they facilitate understanding the roles of different networking, hardware, and software components of smart applications. These are inherently distributed, spanning from devices installed in the field up to a cloud datacenter and further to a user smartphone, passing by intermediary stages at different levels of fog computing infrastructure. However, IoT architectures provide almost no hints on where components should be deployed. IoT Software Platforms derived from the layered architectures are expected to adapt to scenarios with different characteristics, requirements, and constraints from stakeholders and applications. In such a complex environment, a one-size-fits-all approach does not adapt well to varying demands and may hinder the adoption of IoT Smart Applications. In this paper, we propose a 5-layer IoT Architecture and a 5-stage IoT Computing Continuum, as well as provide insights on the mapping of software components of the former into physical locations of the latter. Also, we conduct a performance analysis study with six configurations where components are deployed into different stages. Our results show that different deployment configurations of layered components into staged locations generate bottlenecks that affect system performance and scalability. Based on that, policies for static deployment and dynamic migration of layered components into staged locations can be identified.

An adaptive plan‐oriented and continuous software migration to cloud in dynamic enterprises

SummaryReplacing existing software/hardware components with their equivalent cloud services is an important decision faced by IT managers in today's enterprises. A variety of possible migration targets and cloud services with too many configurations and cost models, disparate and changing strategic objectives of the enterprise management that triggers the migration process, and the complex structure of the legacy applications make software migration to the cloud a challenging issue. In contrast to the existing approaches that model the migration process as an optimization problem to find the optimal deployment of software components on cloud services without presenting a practical migration plan, in this paper, a plan‐oriented migration approach is proposed by which the enterprise management is able to follow migration steps of a valid plan. All valid plans are modeled using a labeled transition system, and a recommender engine directs the management through the possible migration paths using predefined fitness functions. It was observed that, particularly in dynamic and changing conditions that a flexible migration plan is essential, the proposed plan‐oriented method is very much effective in satisfying the enterprise strategic objectives. Evaluations have been performed using two quality indicators: total cost of ownership and scalability index.