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Event-driven software architecture of decision support systems for M2M is proposed.Complex event processing serves as key technology for intelligent M2M systems.General architecture defines M2M-specific domain, event and state models.Machine data is processed by a CEP event processing pipeline in real-time.It is shown how the architecture can be adapted to real-world M2M scenarios. M2M (machine-to-machine) systems use various communication technologies for automatically monitoring and controlling machines. In M2M systems, each machine emits a continuous stream of data records, which must be analyzed in real-time. Intelligent M2M systems should be able to diagnose their actual states and to trigger appropriate actions as soon as critical situations occur.In this paper, we show how complex event processing (CEP) can be used as the key technology for intelligent M2M systems. We provide an event-driven architecture that is adapted to the M2M domain. In particular, we define different models for the M2M domain, M2M machine states and M2M events. Furthermore, we present a general reference architecture defining the main stages of processing machine data. To prove the usefulness of our approach, we consider two real-world examples 'solar power plants' and 'printers', which show how easily the general architecture can be extended to concrete M2M scenarios.

The presented agent-based framework (Acromovi - an acronym in Spanish which stands for Cooperative Architecture for Intelligent Mobile Robots) was born from the idea that teamworking is an essential capability for a group of multiple mobile robots (Jung & Zelinsky, 1999; Mataric, 1998). In the last years, there is an increasing interest in the development of systems of multiple autonomous robots, so that they exhibit collective behaviour. This interest is due to the fact that having one single robot with multiple capabilities may waste resources. Different robots, each one with its own configuration, are more flexible, robust and cost-effective. Moreover, the tasks to achieve may be too complex for one single robot, whereas they can be effectively done by multiple robots (Arai et al., 2002). In this work is described the design and implementation of a distributed architecture for the programming and control of a team of coordinated heterogeneous mobile robots, which are able to collaborate among them and with people in the accomplishment of tasks of services in daily environments, the Acromovi architecture. Acromovi architecture is a framework for application development by means of embedding agents and interfacing agent code with native low-level code. It addresses the implementation of resource sharing among all the group of robots. Cooperation among the robots is also made easier in order to achieve complex tasks in a coordinated way. Moreover, in this work is emphasized the reusability of software, allowing the programmer to seamlessly integrate native software components (vision libraries, navigation and localization modules) , by means of agent wrappers, providing the programmer with a set of tools for mobile robots. Also, it allows sharing the robots’ resources among the team and an easy access to the robots’ elements by the applications. Other important characteristics of the Acromovi architecture are the scalability and ease-of-use. Though robot programming has been extensively done in C or C++ languages, a Java-based multiagent development system was chosen to develop the architecture of our team of robots (Nebot & Cervera, 2005a). Among Java strengths, those particularly pursued were the high-level communication capabilities, and the native interface to existing C/C++ code. On the other hand, Acromovi architecture is a distributed architecture that works as a middleware of another global architecture for programming robots. Though any common agent architecture can be used, it has been implemented by means of the JADE (Java Agent

Most works on person re-identification (ReID) take advantage of large backbone networks such as ResNet, which are designed for image classification instead of ReID, for feature extraction. However, these backbones may not be computationally efficient or the most suitable architectures for ReID. In this work, we aim to design a lightweight and suitable network for ReID. We propose a novel search space called Combined Depth Space (CDS), based on which we search for an efficient network architecture, which we call CDNet, via a differentiable architecture search algorithm. Through the use of the combined basic building blocks in CDS, CDNet tends to focus on combined pattern information that is typically found in images of pedestrians. We then propose a low-cost search strategy named the Top-k Sample Search strategy to make full use of the search space and avoid trapping in local optimal result. Furthermore, an effective Fine-grained Balance Neck (FBLNeck), which is removable at the inference time, is presented to balance the effects of triplet loss and softmax loss during the training process. Extensive experiments show that our CDNet (~1.8M parameters) has comparable performance with state-of-the-art lightweight networks., Accepted by CVPR2021

This paper is going to focus on concepts of space-based architecture (Blackboard system) to evaluate how well the components of the system function using the space paradigm and how it could be further implemented to the benefit of the students. The purpose of it is to increase space and performance in the data grid, which is composed of units that are independent of each other to attain high-performance application since application workloads are amplifying regularly. Especially in the current scenario of the current pandemic, every educational institution is required to continue their classes in an online delivery mode. The blackboard system is assimilated from a set of processing units. Blackboard has gained its popularity since the early stages, it is used by many educational managements including some of the health care services to teach, provide, and associate with one another.

Cloud computing has brought a new method of resource utilization and management. Nowadays some researchers are working on cloud-based instrumentation and measurement systems designated as Instrumentation and Measurement Clouds (IMCs). However, until now, no standard definition or detailed architecture with an implemented system for IMC has been presented. This paper adopts the philosophy of cloud computing and brings forward a relatively standard definition and a novel architecture for IMC. The architecture inherits many key features of cloud computing, such as service provision on demand, scalability and so on, for remote Instrumentation and Measurement (IM) resource utilization and management. In the architecture, instruments and sensors are virtualized into abstracted resources, and commonly used IM functions are wrapped into services. Users can use these resources and services on demand remotely. Platforms implemented under such architecture can reduce the investment for building IM systems greatly, enable remote sharing of IM resources, increase utilization efficiency of various resources, and facilitate processing and analyzing of Big Data from instruments and sensors. Practical systems with a typical application are implemented upon the architecture. Results demonstrate that the novel IMC architecture can provide a new effective and efficient framework for establishing IM systems.

With the commencement of Electronic Transaction Act, Nepal has taken further step in the field of information and communication technology. With government offices nowadays starting to use computers; there lies ahead many challenges to maximize the utilization of computing resources offered by each computer and minimize the overall cost. With many computers, so many idle resources are being wasted unnecessarily. Jobs can be distributed out to idle servers or even to idle desktops. Many of these resources remain idle during office hours off or even during office hours with many users utilizing the computing as well as memory resources. The proposed model not only utilizes resources to optimum but also makes the architecture more modular, adaptive and then provides dynamic fail over recovery and linear scalability. This approach is useful in a place which requires clusters to set up to perform resource intensive works like data processing or computing works. This model can be realized using JINI/Java Space technology which is open source technology and hence, can be cost effective as compared to other proprietary solutions. The motivating factor of this paper is to understand and identify the architectural constraint in the existing distributed application.

Software architecture is a critical artefact in the software lifecycle. It is a system blueprint for construction, it aids in planning teaming and division of work, and it aids in reasoning about system properties. But architecture documentation is seldom created and, even when it is initially created, it is seldom maintained. For these reasons organisations often feel the need to recover legacy architectures, for example, as part of planning for evolution or cloud migration. But there is no existing general architecture recovery approach nor tool that can be applied to any type of system, under any condition. We will show that one way of achieving such generality is to apply systematic code inspection following a Grounded Theory (GT) approach. Though relatively costly and human-intensive, a GT-based approach has several merits, for example: (a) it is general by design; (b) it can be partially automated; (c) it yields evidence-based results rooted of the system being examined. This article presents one theoretical formulation of a general architecture recovery method–called REM–and reports on the evaluation of REM in the context of a large architecture recovery campaign performed for the European Space Agency. Our results illustrate some intriguing properties and opportunities of GT-based architecture recovery approaches and point out lessons learned and venues for further research.

The paper introduces new generic architecture for Internet of Things (IoT) applications with focus on online experimentation. The proposed architecture was inspired by many common features shared between IoT applications and online laboratories. The architecture follows principles of component based design of software systems, and reusability of components. The main goal of the proposed architecture and its implementations is to simplify and accelerate future development and deployment of new online laboratories and IoT applications as well.

In this paper, we propose an integrated security architecture which combines policy based access control with intrusion detection techniques and trusted computing technologies for securing distributed applications running on virtualised systems. Our security architecture incorporates access control security policies for secure interactions between applications and virtual machines in different physical virtualized servers. It provides intrusion detection and trusted attestation techniques to detect and counteract dynamic attacks in an efficient manner. We demonstrate how this integrated security architecture is used to secure the life cycle of virtual machines including dynamic hosting and allocation of resources as well as migration of virtual machines across different physical servers. We discuss the implementation of the developed architecture and show how the architecture can counteract attack scenarios involving malicious users exploiting vulnerabilities to achieve privilege escalation and then using the compromised machines to generate further attacks. The feedback between the various security components of our security architecture plays a critical role in detecting sophisticated, dynamically changing attacks, thereby increasing the resilience of the overall secure system.

Computational power needs have greatly increased during the last years, and this is also the case in the Natural Language Processing (NLP) area, where thousands of documents must be processed, i.e., linguistically analyzed, in a reasonable time frame. These computing needs have implied a radical change in the computing architectures and big-scale text processing techniques used in NLP. In this paper, we present a scalable architecture for distributed language processing. The architecture uses Storm to combine diverse NLP modules into a processing chain, which carries out the linguistic analysis of documents. Scalability requires designing solutions that are able to run distributed programs in parallel and across large machine clusters. Using the architecture presented here, it is possible to integrate a set of third-party NLP modules into a unique processing chain which can be deployed onto a distributed environment, i.e., a cluster of machines, so allowing the language-processing modules run in parallel. No restrictions are placed a priori on the NLP modules apart of being able to consume and produce linguistic annotations following a given format. We show the feasibility of our approach by integrating two linguistic processing chains for English and Spanish. Moreover, we provide several scripts that allow building from scratch a whole distributed architecture that can be then easily installed and deployed onto a cluster of machines. The scripts and the NLP modules used in the paper are publicly available and distributed under free licenses. In the paper, we also describe a series of experiments carried out in the context of the NewsReader project with the goal of testing how the system behaves in different scenarios.

This article presents evaluation data regarding the MAPIS3 architecture which is proposed as a solution for the data-transfer among various tools to promote flexible collaborative learning designs. We describe the problem that this architecture deals with as “tool orchestration” in collaborative learning settings. This term refers to a situation where data relevant to a collaborative learning activity need to be forwarded to and processed by various learning technological tools (e.g. a forum, a pedagogical agent, a service or a software component that provides a specific functionality, etc.), in order for the collaborative activity to be efficiently represented and teachers’ pedagogical level decisions implemented. To facilitate data-transfer among the various tools and accomplish flexible interventions during runtime, the architecture employs a key component (“mediator component”) which makes use of an IMS-LD based representation of the activity. By implementing the architecture tradeoff analysis method in three case studies, evaluation data regarding the proposed architecture have been recorded and are presented in this paper. Targeted stakeholders (learners, teachers, and developers) provided valuable insights on the capacity of the architecture to efficiently facilitate tool orchestration during the realization of a flexible IMS-LD based course. Additionally, limitations of IMS-LD are discussed and suggestions are made on how to tackle these constraints and increase flexibility during tool orchestration in collaborative learning deployment.

Researchers are now considering alternatives to the von Neumann computer architecture as a way to improve performance. The current approach of simulating benchmark applications favors continued use of the von Neumann architecture, but architects can help overcome this bias.

In the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this paper we present a more detailed case-based organizational memory ontology, which aims at contributing to the design of an organizational memory based on cases, so that it can be used to learn, reasoning, solve problems, and as support to better decision making as well. The objective of this Organizational Memory is to serve as base for the organizational knowledge exchange in a processing architecture specialized in the measurement and evaluation. In this way, our processing architecture is based on the C-INCAMI framework (Context-Information Need, Concept model, Attribute, Metric and Indicator) for defining the measurement projects. Additionally, the proposal architecture uses a big data repository to make available the data for consumption and to manage the Organizational Memory, which allows a feedback mechanism in relation with online processing. In order to illustrate its utility, two practical cases are explained: A pasture predictor system, using the data of the weather radar (WR) of the Experimental Agricultural Station (EAS) INTA Anguil (La Pampa State, Argentina) and an outpatient monitoring scenario. Future trends and concluding remarks are extended.

This paper relies on the resource-oriented architecture (ROA) to propose a middleware that shares resources (sensors, actuators and services) of one or more robots through the TCP/IP network, providing greater efficiency in the development of software applications for robotics. The proposed middleware consists of a set of web services that provides access to representational state of resources through simple and high-level interfaces to implement a software architecture for autonomous robots. The benefits of the proposed approach are manifold: i) full abstraction of complexity and heterogeneity of robotic devices through web services and uniform interfaces, ii) scalability and independence of the operating system and programming language, iii) secure control of resources for local or remote applications through the TCP/IP network, iv) the adoption of the Resource Description Framework (RDF), XML language and HTTP protocol, and v) dynamic configuration of the connections between services at runtime. The middleware was developed using the Linux operating system (Ubuntu), with some applications built as proofs of concept for the Android operating system. The architecture specification and the open source implementation of the proposed middleware are detailed in this article, as well as applications for robot remote control via wireless networks, voice command functionality, and obstacle detection and avoidance.

We apply cybernetics theory to control software behaviors in architecture-level.We propose Breeze/ADL to specify the self-adaptive architecture.We design a learning algorithm to derive feedbacks to adjust the architecture.We extend tool - Breeze to support our framework. Display Omitted The cloud computing era requires software architecture to be self-adaptive to the dynamic environment. This autonomous feature brings uncertainty and makes software behavior difficult to control. The uncontrollable behavior is caused by ill-defined architecture and might lead to system disruption. To address this problem, we propose a novel framework which applies software cybernetics to guide self-adaptive architecture evolution. In our framework, we formulate the architecture evolution process as a feedback control process. In the process, we take the self-adaptive architecture model and the model checking technique as the controlled object and controller, respectively. First, the self-adaptive architecture is specified by Breeze/ADL. Second, the framework leverages model checking to validate adaptive Breeze/ADL specifications. Third, a learning algorithm is designed to regulate validation results to generate feedback rules - Productions to guide the architecture evolution. A smart phone application example is chosen to demonstrate the feasibility of our framework. The results show that our framework facilitates architects to detect undesired states which are caused by error-prone adaptation rules.

Clustering-based software architecture recovery is an area that has received significant attention in the software engineering community over the years. Its key concept is the compilation and clustering of a system-wide graph that consists of source code entities as nodes, and source code relations as edges. However, the related research has mostly focused on investigating different clustering methods and techniques, and consequently there is limited work on addressing the question of what is a minimal set of relations that can be easily extracted from the system's source code, and yet can be accurately used for extracting its architecture. In this paper, we report on results obtained from an architecture recovery case study we have conducted, by considering all possible combinations which can be generated from thirteen commonly used source code relations. We have examined the similarity of the extracted architectures obtained by using each different relation combination for different systems, against the corresponding architecture which is obtained by applying all thirteen relations and whch we consider as the ground truth architecture. For this purpose, we have also examined whether the use of all these thirteen relations is indeed adequate to yield a ground truth architecture, by applying this architecture extraction process on five large sofware systems for which their ground truth architecture has been independently established. The overall results of our study indicate that there is small set of relations for procedural systems, and another similar set for object oriented systems, that can be easily extracted from the source code and yet used to yield an architecture that is close to the ground truth architecture.

In modern manufacturing, the product architecture design options are usually restricted to those that can be produced with 100% confidence using those proven technologies to satisfy the existing customer requirement. As a result, the inefficiencies of architecture design are considerable due to such limitations. This issue is of particular interests in cyber manufacturing when exploring the tradeoff between generality and feasibility in product design and manufacturing. It can be expected that the improvement and extension of the existing product architecture may be required to meet new customer requirement when new technologies become available. An effective system performance assessment algorithm is necessary to facilitate the extension of existing product architecture. Though there has been a lot of research on architecture assessment, there is no well-defined model for level by level architecture assessment considering architecture extension. In this paper, we propose a general architecture assessment model considering the integration of additional functionality requirements and performance metrics to evaluate the architecture performance along its value pathway to meet stakeholder’s requirements. A numerical case study focusing on a hypothetical auto cooling system is used to validate the effectiveness of the proposed model.

The Internet of Things has been widely deployed in various areas of daily life through heterogeneous communications protocols. Each unstandardized protocol focuses on a specific IoT communication pattern. Inspired by the Internet architecture over which divergent devices can easily be accessed and a considerable number of applications can be run, we propose a generic architecture for IoT. This architecture supports two DIY areas: network DIY for data aggregation and application DIY for service cooperation. To connect these two DIYs, a centralized controller has been designed to provide standardized interfaces for data acquisition, organization, and storage, and to support elastic and supportive computing. With these properties, divergent devices can coexist in a uniform microworld, and rich services can be developed and provided on demand to interoperate with physical devices. This article discusses the background, design principles, and advantages of the proposed architecture, as well as open problems and our initial solution, which substantiates a novel IoT architecture and new research ground.

Interactive live-streaming applications and platforms face particular challenges: the actions of the viewer's affect the content of the stream. A minimal capture-render delay is critical. This is the case of applications, such as remote laboratories, which allow students to view specific hardware through a webcam, and interact with it remotely in close to real time. It is also the case of other applications, such as videoconferencing or remote rendering. In the latest years, several commercial live-streaming platforms have appeared. However, the most of them have two significant limitations. First, because they are oriented toward standard live-streaming, their capture-render delay tends to be too high for interactive live-streaming. Second, their architectures and sources are closed. That makes them unsuitable for many research and practical purposes, especially when customization is required. This paper presents the requirements for an interactive live-streaming platform, focusing on remote lab needs as a case study. Then, it proposes an architecture to satisfy those requirements that relies on Redis to achieve high scalability. The architecture is based on open technologies, and has been implemented and published as open source. From a client-side perspective, it is web-based and mobile-friendly. It is intended to be useful for both research and practical purposes. Finally, this paper experimentally evaluates the proposed architecture through its contributed implementation, analyzing its performance and scalability.

Currently, context awareness has become essential in software applications and services owing to the high demand by users, especially for mobile computing applications. This need to provide context awareness requires a software infrastructure not only to receive context information but also to make use of it so that it provides advantageous services that may be customized according to user needs. In this paper, we provide an event-driven service-oriented architecture supported by an enterprise service bus, which will facilitate the incorporation of Internet of Things data and provide real-time context-aware services. The result, which has been validated through a real-world case study, is a scalable context-aware architecture which can be applied in a wide spectrum of domains.

The rapid increase in the number and diversity of smart devices connected to the Internet has raised the issues of flexibility, efficiency, availability, security, and scalability within the current IoT network. These issues are caused by key mechanisms being distributed to the IoT network on a large scale, which is why a distributed secure SDN architecture for IoT using the blockchain technique (DistBlockNet) is proposed in this research. It follows the principles required for designing a secure, scalable, and efficient network architecture. The DistBlockNet model of IoT architecture combines the advantages of two emerging technologies: SDN and blockchains technology. In a verifiable manner, blockchains allow us to have a distributed peer-to-peer network where non-confident members can interact with each other without a trusted intermediary. A new scheme for updating a flow rule table using a blockchains technique is proposed to securely verify a version of the flow rule table, validate the flow rule table, and download the latest flow rules table for the IoT forwarding devices. In our proposed architecture, security must automatically adapt to the threat landscape, without administrator needs to review and apply thousands of recommendations and opinions manually. We have evaluated the performance of our proposed model architecture and compared it to the existing model with respect to various metrics. The results of our evaluation show that DistBlockNet is capable of detecting attacks in the IoT network in real time with low performance overheads and satisfying the design principles required for the future IoT network.

This paper presents a software architecture for micro-controllers based solutions that run in capture data cards for Internet of Things (IoT). The present approach describes the components of the software architecture and its interaction. Equally, the architecture allows the development of modular and configurable applications as is focused on the overall design and system specification. The evaluation was performed in a Fog Water Collection system.

Single-instruction set architecture (ISA) heterogeneous multi-processor architecture is promising for developing multi-processor system-on-chips (MPSoCs). In this architecture, all processors execute the same instruction set, yet with various performance and power behavior, since processors may have various micro-architectures. Therefore, systems with this architecture have the advantages of easy to develop new functions as the homogeneous architecture, and easy to customize the resource allocation to achieve high energy efficiency as the heterogeneous architecture. However, for an MPSoC utilizing the target architecture, a key design issue is how to select the set of processors so that the target system can achieve good performance while the cost of the chip is constrained to the expected value. To solve this, in this paper, we propose a processor allocation method for MPSoCs with single-ISA heterogeneous multi-core architecture. The goal of the proposed method is to automatically synthesize the allocation of cores for the given workload so that the performance is optimized while the resource constraint is met. To the best of our knowledge, this is the first work that tackles the processor allocation problem for MPSoCs with the target architecture. To bring out the best performance of a hardware configuration, the proposed algorithm also synthesizes the software design of task mapping for a selected hardware configuration. The experimental results show that, compared with the homogeneous architecture with the least cost and lowest performance cores only, even if the number of core is set to the maximum parallelism degree of the target workload, the proposed method achieves up to 8.25% of performance improvement among all the cases we evaluated while the area constraint is met. Compared with the architecture with all high performance but large cores, when the number of cores is also set to the same as the maximum parallelism degree of the target workload, the proposed method has at most 11.5% of performance degradation, while the area cost is reduced by 60.7%.

In a smart distribution power grid, cost efficient and reliable communication architecture plays a crucial role in achieving complete functionality. There are different sets of Quality of Services (QoS) requirements for different data packets transmitting inside the microgrid (a regionally limited smart distribution grid), making it challenging to derive optimal communication architecture. The objective of this research work is to determine the optimal communication technologies for each data packet based on its QoS requirement. In this paper, we have proposed an architecture for a smart distribution power grid with Cyber Physical System enabled microgrids, which accommodate almost all functional requirements of a smart distribution power grid. For easy transition towards optimal communication architecture, we have presented a six-tier communication topology, which is derived from the architecture for a smart distribution power grid. The optimization formulations for each packet structure presented in this paper minimize the overall cost and consider the QoS requirements for each packet. Based on the simulation results, we have made recommendations for optimal communication technologies for each packet and thereby developed a heterogeneous communication architecture for a microgrid.

This paper aims at introducing a type of social commerce architecture to which the name Interaction Commerce has been given. First, a global description of the main macro-components forming the structure of this architecture is provided. Such components also take care of managing e-commerce activities and social relationships within the architecture. Second, the focus is set on the analysis of the single components that are key to the social aspects of the architecture. A special chapter is then entirely focussed on a topic that is considered extremely important by the entire research community, i.e., recommender systems. After providing a general introduction on the topic, the two most common recommendation approaches are analyzed and compared. These are the content-based approach and the collaborative filtering approach. The analysis has shown how all recommender systems are threatened by the cold-start problem. Studying recommender systems has allowed for their implementation in the architecture, which now has a new “social” approach that is able to solve the new user cold-start problem. An architecture prototype was developed and tested in order to be validated. To cite this document: Luca Salvatori and Fausto Marcantoni, "Interaction commerce, a technological architecture focused on recommender system", International Journal of Electronic Commerce Studies, Vol.7, No.2, pp.105-134, 2016. Permanent link to this document: http://dx.doi.org/10.7903/ijecs.1443

One big challenge in building a smart grid arises from the fast growing amount of data and limited communication resources. The traditional centralized communication architecture does not scale well with the explosive increase of data and has a high probability of encountering communication bottlenecks due to long communication paths. To address this challenging issue, this article presents a distributed communication architecture that implements smart grid communications in an efficient and cost-effective way. This distributed architecture consists of multiple distributed operation centers, each of which is connected to several data concentrators serving one local area and only sends summary or required integrated information to a central operation center. Using this distributed architecture, communication distance is much shortened, and thus data will be delivered more efficiently and reliably. In addition, such a distributed architecture can manage and analyze data locally, rather than backhauling all raw data to the central operation center, leading to reduced cost and burden on communication resources. Advanced metering infrastructure is chosen as an example to demonstrate benefits of this architecture on improving communication performance. The distributed communication architecture is also readily applicable to other smart grid applications, for example, demand response management systems.

To provide modeling and simulation functionality as services is strategically leveraged in the defense domain and elsewhere. To describe and understand the context, the ecosystem, wherein such services are used and interoperate with other services and capabilities, one needs tools that capture the simulation services themselves as well as the capability landscape they operate in. By using the NATO Consultation, Command, and Control (C3) Taxonomy to structure architecture design in the NATO Architecture Framework (NAF), cohesive descriptions of modeling and simulation capabilities within larger contexts can be given. We show how a basic seven-step approach may benefit architecture work for modeling and simulation at the overarching, reference, and target architectural levels; in particular for (1) hybrid architectures that embed simulation architectures within a larger service-oriented architecture and (2) for architectural design of simulation scenarios. Central to the approach is the use of the C3 Taxonomy as a repository for overarching architecture building blocks and patterns. We conclude that the promotion of technical functionality as capabilities in their own right helps delineate simulation environment boundaries, helps delineate services within and outside the boundary, and is an enabler for defining the service concepts in cloud-based approaches to modeling and simulation as a service (MSaaS).

Efficient and dedicated hardware architecture and accelerator micro-engines are crucial implementation forms of MPEG-like video coder. It is significant to excavate and generalize the common technologies and design philosophy of hardwired MPEG-like coders behind number of architectures from academic and industrial communities. This paper makes systematic survey on algorithm and architecture of hardwired MPEG-like coders, from microscopic and macroscopic perspectives, taking H.264/AVC as the analysis target. Recent advances in hardware architectures of prevailing H.264/AVC coders are reviewed and summarized. Furthermore, important algorithm modules, such as integer and fractional pixel motion estimation, mode decision, motion vector prediction, intra prediction, rate control, CABAC coder and deblocking filter are reviewed with detailed analysis on algorithm and hardware architecture. In accordance with the intrinsic characteristics of the algorithm flows, the major design constraints and consideration factors of algorithm and architecture are analyzed respectively. The common technologies of the prevailing architectures are summarized from a systematic perspective, coving different levels ranging from algorithm, architecture, to control and data flows, etc. Based on these analysis, this survey further highlights in-depth summarization and perspectives on MPEG-like coder architecture design. First, the design challenges with multiple target performance optimization are analyzed, and the possible solutions for design challenges are systematically summarized. Second, the rate-distortion-complexity constrained algorithm optimization for MPEG-like video encoder is discussed. Third, typical four-level hierarchical architecture model (SoC system, module, inter-connection, memory) is analyzed, and the pivotal memory architecture and inter-connection architecture are emphasized for analysis. Moreover, the algorithm and architecture design suggestions and preferences for the vital modules are discussed. Fourth, the composite performances of prevailing architectures are evaluated. The concerned target parameters including hardware logic cost, SRAM size, external memory bandwidth, throughput efficiency, power dissipation, and rate-distortion performance are taken as comparison factors. Finally, this paper provides explicit perspectives on future trends of video coder architecture design. The proposed paper can be taken as design reference for H.264/AVC coder hardware architecture, and offer further insight into algorithm and architecture optimization for the new emerging HEVC standard.

This article presents position statements and a question-and-answer session by panelists at the 4th Workshop on Computer Architecture Research Directions. The subject of the debate was new technologies and their impact on future architectures.

Recent advances in the Internet of Things (IoT) and pervasive and ubiquitous computing provide a glimpse into the future of our planet and reveal exciting visions of many smart things: smart cities, smart homes, smart cars, and other smart spaces such as malls, workplaces, hotels, schools, and much more. Driven by a technological revolution offering “low-power many things and wireless almost everything,” we could, in only a decade, envision and prototype impressive smart space systems that improve quality of life, enhance awareness of resources and the environment, and enrich users’ experience. However, prototyping is one thing and actual large-scale deployments are another. The massive scale of sensors and devices that will be deployed in smart cities of the future will be challenging. Without an ecosystem and a scalable architecture in place, it will be extremely difficult to manage or program such an expanding and massive IoT. In this paper, we introduce the Cloud-Edge-Beneath (CEB) architecture and present its salient scalability features. We also present a validation study based on an event-driven programming model demonstrating CEB’s scaling behavior in face of IoT expansion and under dynamically increasing loads.

This paper presents for the first time the Smart Grid Paradigm: the Link. Having a standardized structure, the Link can be applied to any partition of the power system: electricity production entity, storage entity, the grid or even the costumer plant. From this paradigm are extracted three architecture components: the “Grid-Link”, the “Producer-Link”, and the “Storage-Link”. The distributed Link-based architecture is designed. It allows a flat business model across the electrical industry and minimizes the amount of the data, which needs to be exchanged. It takes also into account the electricity market rules and the rigorous cyber security and privacy requirements. The interfaces between the all three architecture components are defined. The power system operation processes like load-generation balance, dynamic security and demand response are outlined to demonstrate the architecture applicability. To complete the big picture, the operator role, the corresponding information and communication architecture and the market accommodation are also described.

The article argues that humans are endowed with an inborn language faculty. The ‘Basic Property’ of language is defined as a finitely-specified procedure represented in the brain, which generates a discrete infinity of hierarchically structured expressions. These unordered structures are linked to two interfaces: (i) the sensorimotor interface and (ii) the conceptual-intentional interface. The sensorimotor interface externalizes and linearizes internal structures, usually in the sound modality. Externalization and linearization account for the structural diversity of the world’s languages. Human language did not evolve from simpler communication systems. The available evidence suggests that language is primarily an instrument of thought, not of communication.

In order to solve the problem of heterogeneity in multi-robot cooperation, a new service-oriented architecture is proposed for multi-robot cooperation. Service provision and energy consumption are the basic cooperative behaviors. A set of basic concepts of robot service are proposed. A layered multi-robot service-oriented architecture is designed. Finally, the experiments illustrate the superiority of the proposed architecture which makes robot's underlying functional components be transparently encapsulated and the services in upper layer be transparently invoked, which will effectively avoid the impact of heterogeneous characteristics in multi-robot cooperation and facilitate the system construction, expansion, restructuring and maintenance.

Monitoring life-long diseases requires continuous measurements and recording of physical vital signs. Most of these diseases are manifested through unexpected and non-uniform occurrences and behaviors. It is impractical to keep patients in hospitals, health-care institutions, or even at home for long periods of time. Monitoring solutions based on smartphones combined with mobile sensors and wireless communication technologies are a potential candidate to support complete mobility-freedom, not only for patients, but also for physicians. However, existing monitoring architectures based on smartphones and modern communication technologies are not suitable to address some challenging issues, such as intensive and big data, resource constraints, data integration, and context awareness in an integrated framework. This manuscript provides a novel mobile-based end-to-end architecture for live monitoring and visualization of life-long diseases. The proposed architecture provides smartness features to cope with continuous monitoring, data explosion, dynamic adaptation, unlimited mobility, and constrained devices resources. The integration of the architecture׳s components provides information about diseases׳ recurrences as soon as they occur to expedite taking necessary actions, and thus prevent severe consequences. Our architecture system is formally model-checked to automatically verify its correctness against designers׳ desirable properties at design time. Its components are fully implemented as Web services with respect to the SOA architecture to be easy to deploy and integrate, and supported by Cloud infrastructure and services to allow high scalability, availability of processes and data being stored and exchanged. The architecture׳s applicability is evaluated through concrete experimental scenarios on monitoring and visualizing states of epileptic diseases. The obtained theoretical and experimental results are very promising and efficiently satisfy the proposed architecture׳s objectives, including resource awareness, smart data integration and visualization, cost reduction, and performance guarantee.

In recent years, SDN (Software Defined Network) as a new network architecture has become the hot research point. Meanwhile, the well-known OpenFlow-based SDN got a lot of attention. But it can't provide a flexible and effective network resource description method. As an open programmable technology, ForCES (Forwarding and Control Element Separation) has also been concerned. However, ForCES is confined within a single network node and cannot be applied to the entire network. This paper proposes a new architecture - ForSA (ForCESbased SDN architecture). The architecture is added a configuration layer based on the traditional SDN architecture, which solves the problem that the northbound interface is not clear between the application layer and the control layer in the SDN architecture. ForSA also implements the compatibility within various forwarding devices in the forwarding layer.

This paper presents a software architecture-based methodological approach to develop collaborative applications. Today, the use of collaborative applications has spread to various domains, as they facilitate communication, collaboration, and coordination between several users. These applications require mechanisms to support and model communication activities and processing of information, vital in the dynamic nature to the group. In this paper, the use of a software architecture is recommended to develop collaborative applications. This architecture for specifying the structure and behavior through the application, providing a shared meeting space to simplify and agile the group work. Thus, it is possible to support dynamic group structure. In addition, specification tables are proposed to simplify the development of this kind of applications; since the developers to complete the table are analyzing the necessary elements required to build an application, so performing requirements analysis, design, and displayed as would the final application. A case study to validate the software architecture is proposed.

Software product line (SPL) engineering has proven to improve software quality and shorten development cycles, cost and time. In product line engineering, product derivation is concerned with the realization of the variability at the implementation level. However, the majority of research works focuses on instantiating the variants selected in the final product, while the derivation at the architecture level has been poorly explored. As product line engineers often customize the product architecture by hand during the application engineering phase, the derivation and customization processes of the product line architecture (PLA) might be in some cases error-prone. Consequently, in this research we present an Ontology-based product Architecture Derivation (OntoAD) framework which automates the derivation of product-specific architectures from an SPL architecture. Our solution uses a language-independent model to specify the product line architecture and a model-driven engineering approach for architecture derivation activities. We use an ontology formalism to reason about the automatic generation of model-to-model transformation rules based on the selection of features and we illustrate our approach using a voice over IP motivating example. Finally, we report results about scalability and performance regarding the size of the variability model.

The Mobile Computing is a vision of future that promises to modify the way people work and interact today. It has emerged as a new field, distinct from conventional distributed computing by its focus on mobility and its consequence. The physical and logical mobility allows the creation of applications with news requirements: built-in mobility, adaptability and flexibility. So, software production for this global mobility is complex. Challenges include designing applications which service levels and available resources are unpredictable, and the behavior is variable in time and space. To provide a system architecture that simplifies the task of implementing the mobile applications with adaptive behavior is the objective of the ongoing ISAM Project. In order to achieve its goal, ISAM uses as strategies: (a) integrated environment that provides a programming paradigm and its execution environment; (b) uniform treatment of adaptation through multilevel collaborative model, in which both the system and the application contribute for that. The scheduling process – the core of ISAM architecture, manages this collaboration. Introducing HoloLanguage abstractions that express adaptability makes the control of adaptation by part of application. So, adaptation is not fully transparent to applications. In this paper, we present the main decisions used for designing the ISAM Architecture. We also introduce a first taxonomy for mobile applications with adaptive behavior.

The cyber-physical system is the core concept of Industry 4.0 for building smart factories. We can rely on the ISA-95 architecture or the 5C architecture to build the cyber-physical system for smart factories. However, both architectures emphasize more on vertical integration and less on horizontal integration. This article proposes the 8C architecture by adding 3C facets into the 5C architecture. The 3C facets are coalition, customer, and content. The proposed 8C architecture is a helpful guideline to build the cyber-physical system for smart factories. We show an example of designing and developing, on the basis of the proposed 8C architecture, a smart factory cyber-physical system, including an Industrial Internet of Things gateway and a smart factory data center running in the cloud environment.

This book presents a distributed multiprocessor architecture that is faster, more versatile, and more reliable than traditional single-processor architectures. It also describes a simulation technique that provides a highly accurate means for building a prototype system in software. The system prototype is studied and analyzed using such DSP applications as digital filtering and fast Fourier transforms. The code is included as well, which allows others to build software prototypes for their own research systems. The design presented in Microprocessor-Based Parallel Architecture for Reliable Digital Signal Processing Systems introduces the concept of a dual-mode architecture that allows users a dynamic choice between either a conventional or fault-tolerant system as application requirements dictate. This volume is a "must have" for all professionals in digital signal processing, parallel and distributed computer architecture, and fault-tolerant computing.

With the current increase of distributed generation in distribution networks, line congestions and PQ issues are expected to increase. The smart grid may effectively coordinate DER, only when supported by a comprehensive architecture for automation. In IDE4L project such architecture is designed based on monitoring, control and business use cases. The IDE4L instance of SGAM architecture is derived and explained in details. The automation actor are specified in terms of interfaces, database and functions. The division in these three layers boosted the implementation phase as dedicated interfaces, databases or application has been developed in a modular way and can be installed in different HW/SW. Some implementation instances are presented and the main output of the architecture is discussed with regards to some indexes as communication traffic and level of distribution of automation functions. QC 20181002

The development and the use of learning environments, coupled with the evolution of mobile computing, have contributed significantly to the establishment of a new learning modality known as mobile learning (m-learning). In this new scenario, the educational environments, despite having many benefits and facilities with regard to teaching and learning, have problems and challenges that need to be addressed. One of the important aspects to be investigated concerns the establishment and adoption of architectural patterns. In fact, most of these environments are built in an isolated form, having their own architectures and structures, which may negatively impact the ability of standardization and support of architectural definition. The main goal of this paper is to investigate and define a service-oriented reference architecture for m-learning environments. The proposed architecture, named Ref-mLearning, aims to contribute to the evolution, reuse, and interoperability of such environments, enabling an increase in quality and cost reduction during their development, due to the use of features provided by service-oriented architecture. Ref-mLearning was also evaluated through qualitative and quantitative aspects: 1) in comparison with a reference architecture model and 2) with the support of specialists. The results showed that the proposed architecture comprises relevant elements with respect to a service-oriented reference architecture.

This paper describes the application of an Architectural Framework and System Architecture in the Rail and Road infrastructure. This is illustrated by addressing the state of the art of Systems Engineering in this domain, how the need for system architecture became apparent and finally what architecture framework was chosen and how that was applied in a real life rail example. The paper concludes with a view on the next steps to be taken to further mature the Architecture Framework and resulting system architectures. The main focus of this paper is on architecture for Rail Infrastructure systems, with some references to road infrastructure system.

This work presents the Intelligent Trading Architecture ITA, which is a new automated trading system architecture that supports multiple strategies for multiple market conditions through hierarchical trading signals generation. The central idea of the proposed system architecture is decomposing the trading problem into a set of tasks that are handled by distributed autonomous agents under a minimal central coordination. With this kind of architecture, we can take advantage of currently available and future high-performance computing systems. These systems, due to the way computer architecture has evolved in the recent past and foreseeable future, are composed of multiple processor cores. We are implementing the ITA software architecture employing the Carnegie Mellon Navigation CARMEN robot control software and using a publish/subscribe communication model. Together, CARMEN and this communication model allow the implementation of high-performance, scalable parallel computing systems that leverage the architecture of multi-core systems. For this work, we evaluated the data structures and algorithms employed by the symbol module of the ITA software architecture, which is responsible for maintaining the synchronized local copies of exchanges limit order books LOB for the instruments traded by the system. Our LOB implementation strongly outperformed a reference implementation in all evaluated parameters by more than one order of magnitude in some cases, achieving average throughputs of 4i¾?million orders/s when creating new orders, 3i¾?million orders/s when changing existing orders, and 17i¾?million orders/s when querying orders. Copyright © 2015 John Wiley & Sons, Ltd.

Internet is facing many challenges that cannot be solved easily through ad hoc patches. To address these challenges, many research programs and projects have been initiated and many solutions are being proposed. However, before we have a new architecture that can motivate Internet service providers (ISPs) to deploy and evolve, we need to address two issues: 1) know the current status better by appropriately evaluating the existing Internet; and 2) find how various incentives and strategies will affect the deployment of the new architecture. For the first issue, we define a series of quantitative metrics that can potentially unify results from several measurement projects using different approaches and can be an intrinsic part of future Internet architecture (FIA) for monitoring and evaluation. Using these metrics, we systematically evaluate the current interdomain routing system and reveal many “autonomous-system-level” observations and key lessons for new Internet architectures. Particularly, the evaluation results reveal the imbalance underlying the interdomain routing system and how the deployment of FIAs can benefit from these findings. With these findings, for the second issue, appropriate deployment strategies of the future architecture changes can be formed with balanced incentives for both customers and ISPs. The results can be used to shape the short- and long-term goals for new architectures that are simple evolutions of the current Internet (so-called dirty-slate architectures) and to some extent to clean-slate architectures.