Architectural Options Research Articles

Scalable edge cloud platforms for IoT services

Nowadays, online applications are moving to the cloud, and for delay-sensitive ones, the cloud is being extended with edge/fog domains. Emerging cloud platforms that tightly integrate compute and network resources enable novel services, such as versatile IoT (Internet of Things), augmented reality or Tactile Internet applications. Virtual infrastructure managers (VIMs), network controllers and upper-level orchestrators are in charge of managing these distributed resources. A key and challenging task of these orchestrators is to find the proper placement for software components of the services. As the basic variant of the related theoretical problem (Virtual Network Embedding) is known to be NP-hard, heuristic solutions and approximations can be addressed. In this paper, we propose two architecture options together with proof-of-concept prototypes and corresponding embedding algorithms, which enable the provisioning of delay-sensitive IoT applications. On the one hand, we extend the VIM itself with network-awareness, typically not available in today's VIMs. On the other hand, we propose a multi-layer orchestration system where an orchestrator is added on top of VIMs and network controllers to integrate different resource domains. We argue that the large-scale performance and feasibility of the proposals can only be evaluated with complete prototypes, including all relevant components. Therefore, we implemented fully-fledged solutions and conducted large-scale experiments to reveal the scalability characteristics of both approaches. We found that our VIM extension can be a valid option for single-provider setups encompassing even 100 edge domains (Points of Presence equipped with multiple servers) and serving a few hundreds of customers. Whereas, our multi-layer orchestration system showed better scaling characteristics in a wider range of scenarios at the cost of a more complex control plane including additional entities and novel APIs (Application Programming Interfaces).

Method for conceptualizing systematic studies of information security management systems

A method for conceptualizing system studies of information security management systems is proposed. Its development is based on a developed system approach by supplementing it with a model-oriented. This extension allowed to unify the ontological representation of system studies of information security management systems. First, identify the tasks as basic concepts and establish relations between them. Among them, four classes are defined: requirements analysis, function analysis, architecture synthesis, behavior synthesis. The inputs for requirements analysis are the needs of both internal and external stakeholders. They are followed by the correctness of requirements formulation, compliance with personal and group features. The relationships between the requirements for information security management systems are then determined. The requirements specification is used as input data when analyzing the functions of information security management systems. For each of them the inputs, outputs, constraints, and resources are established. Such a representation allowed to justify the definition of options for the use of information security management systems. The implementation of options for using information security management systems is achieved by synthesizing the architecture. For this purpose, blocks are selected, each of which maps the corresponding elements of the architecture and establishes the relationships between them. Its functional usability is determined by synthesizing the behavior of information security management systems. The input data for solving this problem is their architecture. In this case, the behavior of an individual element (block) or the information security management system can be synthesized. This is achieved through activities, interactions, and state changes. Due to this, the functional suitability/unsuitability of the synthesized architecture is found following the requirements of stakeholders. Unified views of separate tasks of system research of information security management systems are achieved using the system modeling language. Based on the results obtained, it is possible to determine alternative architecture options and select the best among them in terms of their functional suitability.

Blockchains

Blockchain technology has gained tremendous popularity both in practice and academia. The goal of this article is to develop a coherent overview of the state of the art in blockchain technology, using a systematic (i.e., protocol-based, replicable), multivocal (i.e., featuring both white and grey literature alike) literature review to (1) define blockchain technology, (2) elaborate on its architecture options and (3) tradeoffs, as well as to understand (4) the current applications and challenges, as evident from the state of the art. We derive a systematic definition of blockchain technology, based on a formal concept analysis. Further, we flesh out an overview of blockchain technology elaborated by means of Grounded-Theory.

Advancing evidence-based healthcare facility design: a systematic literature review.

Healthcare facility design is a complex process that brings together diverse stakeholders and ideally aligns operational, environmental, experiential, clinical, and organizational objectives. The challenges inherent in facility design arise from the dynamic and complex nature of healthcare itself, and the growing accountability to the quadruple aims of enhancing patient experience, improving population health, reducing costs, and improving staff work life. Many healthcare systems and design practitioners are adopting an evidence-based approach to facility design, defined broadly as basing decisions about the built environment on credible and rigorous research and linking facility design to quality outcomes. Studies focused on architectural options and concepts in the evidence-based design literature have largely employed observation, surveys, post-occupancy study, space syntax analysis, or have been retrospective in nature. Fewer studies have explored layout optimization frameworks, healthcare layout modeling, applications of artificial intelligence, and layout robustness. These operations research/operations management approaches are highly valuable methods to inform healthcare facility design process in its earliest stages and measure performance in quantitative terms, yet they are currently underutilized. A primary objective of this paper is to begin to bridge this gap. This systematic review summarizes 65 evidence-based research studies related to facility layout and planning concepts published from 2008 through 2018, and categorizes them by methodology, area of focus, typology, and metrics of interest. The review identifies gaps in the existing literature and proposes solutions to advance evidence-based healthcare facility design. This work is the first of its kind to review the facility design literature across the disciplines of evidence-based healthcare design research, healthcare systems engineering, and operations research/operations management. The review suggests areas for future study that will enhance evidence-based healthcare facility designs through the integration of operations research and management science methods.

Low-complexity blind polarization demultiplexing and frequency domain equalization for coherent passive optical network systems

Algorithmic and architectural options and trade-offs between performance and complexity/power dissipation are necessary to consider in the transfer of coherent technology from long-haul transmission to short-reach application. An adaptive equalization algorithm cascading polarization demultiplexing and frequency domain equalization is proposed to target passive optical network applications that feature extremely low computational complexity. Three coordinate rotation digital computer-based vector rotators are introduced to realize polarization demultiplexing without performing multiplications. A simplified gradient descent algorithm is proposed to search and trace the state of polarization. A nonbutterfly adaptive equalizer in the frequency domain for each polarization is designed to handle link chromatic dispersion and the imperfection of the transceiver frequency response. The performance of the proposed equalization scheme is experimentally verified by a 32-GBaud dual-polarization Nyquist quadrature phase-shift keying system over 20-km standard single-mode fiber transmission. With the proposed method, the number of hardened multipliers for field-programmable gate array realization is reduced by ∼85 % compared with a conventional 2 × 2 multiple-input multiple-output finite impulse response filter with the same receiver sensitivity.

Reexamining the Mission Architecture Decision of Project Apollo: A New Parametric Perspective

Although the historical and technical details of Project Apollo have been extensively documented in literature, current records indicate that there is still a lack of an early-design-phase, physics-based, parametric sizing quantification of the engineering decisions that made Apollo a success. Historical texts that explain the design decisions of Apollo do so in a predominantly qualitative manner, leaving out the physics-based Future Projects Office–type calculations, whereas technical texts tend to explain the design details at higher fidelity, overall leading the engineer away from the big picture design understanding. This paper reexamines the critical mission architecture (or mission mode) decision from a holistic and parametric perspective. After parametrically connecting a launch vehicle sizing process with an in-space element sizing process, a generic mission architecture solution space is generated that enables the visualization and comparison of the various Project Apollo architecture options. The mission planner can then consistently compare the competing architecture options like lunar orbit rendezvous or direct flight with each other based on their overall launch mass, launch performance, and launch vehicle cost. It is identified that the lunar orbit rendezvous approach is the clear winner in terms of launch vehicle size and cost.

LPWAN Technologies: Emerging Application Characteristics, Requirements, and Design Considerations

Low power wide area network (LPWAN) is a promising solution for long range and low power Internet of Things (IoT) and machine to machine (M2M) communication applications. This paper focuses on defining a systematic and powerful approach of identifying the key characteristics of such applications, translating them into explicit requirements, and then deriving the associated design considerations. LPWANs are resource-constrained networks and are primarily characterized by long battery life operation, extended coverage, high capacity, and low device and deployment costs. These characteristics translate into a key set of requirements including M2M traffic management, massive capacity, energy efficiency, low power operations, extended coverage, security, and interworking. The set of corresponding design considerations is identified in terms of two categories, desired or expected ones and enhanced ones, which reflect the wide range of characteristics associated with LPWAN-based applications. Prominent design constructs include admission and user traffic management, interference management, energy saving modes of operation, lightweight media access control (MAC) protocols, accurate location identification, security coverage techniques, and flexible software re-configurability. Topological and architectural options for interconnecting LPWAN entities are discussed. The major proprietary and standards-based LPWAN technology solutions available in the marketplace are presented. These include Sigfox, LoRaWAN, Narrowband IoT (NB-IoT), and long term evolution (LTE)-M, among others. The relevance of upcoming cellular 5G technology and its complementary relationship with LPWAN technology are also discussed.

On Leveraging Machine and Deep Learning for Throughput Prediction in Cellular Networks: Design, Performance, and Challenges

The highly dynamic wireless communication environment poses a challenge for many applications (e.g., adaptive multimedia streaming services). Providing accurate TP can significantly improve performance of these applications. The scheduling algorithms in cellular networks consider various PHY metrics, (e.g., CQI) and throughput history when assigning resources for each user. This article explains how AI can be leveraged for accurate TP in cellular networks using PHY and application layer metrics. We present key architectural components and implementation options, illustrating their advantages and limitations. We also highlight key design choices and investigate their impact on prediction accuracy using real data. We believe this is the first study that examines the impact of integrating network-level data and applying a deep learning technique (on PHY and application data) for TP in cellular systems. Using video streaming as a use case, we illustrate how accurate TP improves the end user's QoE. Furthermore, we identify open questions and research challenges in the area of AI-driven TP. Finally, we report on lessons learned and provide conclusions that we believe will be useful to network practitioners seeking to apply AI.

Disaggregated Data Centers: Challenges and Trade-offs

Disaggregated data centers (DCs) can offer high flexibility for resource allocation; hence, their resource utilization can be significantly improved. However, communications between different types of resources, in particular between CPU and memory, in fully disaggregated DCs face severe problems in terms of stringent requirements for ultra-low latency and ultra-high transmission bandwidth. Optical fiber communication is promising to provide high capacity and low latency, but it is still challenging for the state-of-the-art optical technologies to meet the requirements of fully disaggregated DCs. In this article, different levels of resource disaggregation are investigated. For fully disaggregated DCs, two architectural options are presented, where optical interconnects are necessary for the CPU-memory communications. We review the state-of-the-art optical transmission and switching technologies, and analyze pros and cons of their applicability in the disaggregated DCs. The results reveal that resource disaggregation does improve the resource utilization in DCs. However, the bandwidth provided by the state-of-the-art technologies is not always sufficient for fully disaggregated DCs. It calls for further advances in optical communications to fully utilize the advantages of fully disaggregated DCs.

Search-space Decomposition for System-level Design Space Exploration of Embedded Systems

The development of large-scale multi- and many-core platforms and the rising complexity of embedded applications have led to a significant increase in the number of implementation possibilities for a single application. Furthermore, rising demands on safe, energy-efficient, or real-time capable application execution make the problem of determining feasible implementations that are optimal with respect to such design objectives even more of a challenge. State-of-the-art Design Space Exploration (DSE) techniques for this problem demonstrably suffer from the vast and sparse search spaces posed by modern embedded systems, emphasizing the need for novel design methodologies in this field. Based on the idea of reducing problem complexity by a suitable decomposition of the system specification—in particular, by a reduction of target architecture or task mapping options—the work at hand proposes a portfolio of dynamic decomposition mechanisms that automatically decompose any system specification based on a short pre-exploration of the complete system. We present a two-phase approach consisting of (a) a set of novel data extraction and representation techniques combined with (b) a selection of filtering operations that automatically extract a decomposed system specification based on information gathered during pre-exploration. In particular, we employ heat map data structures and threshold as well as graph-partitioning filters to reduce problem complexity. The proposed decomposition procedure can seamlessly be integrated in any DSE flow, constituting a flexible extension for existing DSE approaches. Furthermore, it improves existing static decomposition techniques and other heuristics relying on information about the problem instance, since systems with irregular architectural topology or distribution of resource types can now be decomposed based on an automatic, problem-independent pre-exploration phase. We illustrate the efficiency of the proposed decomposition portfolio applied to state-of-the-art DSEs for many-core systems as well as networked embedded systems from the automotive domain. Experimental results show significant increases in optimization quality of up to 87% within constant DSE time compared to existing approaches.

A network tool to analyse and improve robustness of system architectures

The architecture of a system is decided at the initial stage of the design. However, the robustness of the system is not usually assessed in detail during the initial stages, and the exploration of alternative system architectures is limited due to the influence of previous designs and opinions. This article presents a novel network generator that enables the analysis of the robustness of alternative system architectures in the initial stages of design. The generator is proposed as a network tool for system architectures dictated by their configuration of source and sink components structured in a way to deliver a particular functionality. Its parameters allow exploration with theoretical patterns to define the main structure and hub structure, vary the number, size, and connectivity of hub components, define source and sink components and directionality at the hub level and adapt a redundancy threshold criterion. The methodology in this article assesses the system architecture patterns through robustness and modularity network based metrics and methods. Two naval distributed engineering system architectures are examined as the basis of reference for the simulated networks. The generator provides the capacity to create alternative complex system architecture options with identifiable patterns and key features, aiding in a broader explorative and analytical, in-depth, time and cost-efficient initial design process.

HPC Systems in the Next Decade – What to Expect, When, Where

HPC systems have seen impressive growth in terms of performance over a period of many years. Soon the next milestone is expected to be reached with the deployment of exascale systems in 2021. In this paper, we provide an overview of the exascale challenges from a computer architecture’s perspective and explore technological and other constraints. The analysis of upcoming architectural options and emerging technologies allow for setting expectations for application developers, which will have to cope with heterogeneous architectures, increasingly diverse compute technologies as well as deeper memory and storage hierarchies. Finally, needs resulting from changing science and engineering workflows will be discussed, which need to be addressed by making HPC systems available as part of more open e-infrastructures that provide also other compute and storage services.

Fast Methods of Coverage Evaluation for Tradespace Analysis of Constellations

Simulation of distributed space missions (DSMs) for the purpose of phase-A mission design studies and general tradespace analysis is computationally challenging owing to the necessity of evaluating thousands of architecture options. Machine learning and evolutionary optimization methods have enabled intelligent search of the architectural tradespace of DSMs, including spacecraft and instrument design specifications. A critical computational bottleneck in evaluating architectures is the ability to rapidly simulate orbits of many DSMs with varying parameters for global earth observation and compare their coverage-related performance. When design variables include heterogeneous payload types and characteristics, orbital characteristics, areas of interest, and user constraints, the parameter space may be in thousands. In this article, we describe the difficulty of coverage calculations for narrow field of view (FOV) and conical FOV sensors, and propose a novel algorithm, called quick search and correction (QSC), to overcome it. We also propose new temporal evaluation metrics to characterize the coverage performance of DSMs, as well as a uniform random sampling technique for fast evaluation of overall performance of DSMs. Performance of the proposed methods and metrics are verified on an example Landsat-derived DSM, showing ~100x improvement in computational speed due to the QSC algorithm and ~10-250x due to the sampling technique.

Sliceable BVT Evolution Towards Programmable Multi-Tb/s Networking

The sliceable bandwidth variable transceiver (S-BVT) is a key element in addressing the challenges and evolution of optical networks, and supporting the ever-increasing traffic volume, speed, and dynamicity driven by novel and broadband services and applications. Multiple designs and configurations are possible and are evolving towards supporting multi-Tb/s networking, thanks to the adoption of advanced and more mature photonic technologies. In this work, we review and analyze alternative S-BVT design architecture options that target different network segments and applications. We specifically focus on S-BVTs based on multicarrier modulation (MCM), which provide a wide range of granularity and more flexible spectral manipulation. A detailed description of the main elements in an S-BVT and their characteristics is provided in order to give design guidelines. The performance in a real testbed network is also reported, comparing a set of S-BVT configurations that adopt different technologies. Finally, an extensive discussion of the described architecture, functionalities, and results, including programmability aspects, is provided in view of S-BVT evolution towards future optical network requirements and needs.

An efficient adaptive equalization architecture for high-speed coherent PON systems

Algorithmic and architectural options and tradeoffs between performance and complexity/power dissipation are imperative to be considered in the transfer of coherent technology from long-haul transmission to passive optical network (PON) application. In this work, a novel low-complexity equalization architecture cascaded two frequency domain equalizers (FDEQs) and one 1-tap 2 × 2 butterfly equalizer is proposed targeting PON applications. FDEQ is designed to handle link chromatic dispersion (CD) and the imperfection of transceiver frequency response. The 1-tap 2 × 2 butterfly equalizer is introduced to realize polarization demultiplexing. A simplified FDEQ tap coefficient calculation method is designed. The performance of the proposed equalization architecture is experimentally verified by a 32-GBaud dual-polarization (DP) Nyquist-QPSK system over 20-km standard single-mode fiber (SSMF) transmission. With the proposed method, the number of hardened multipliers for field-programmable gate array (FPGA) realization is reduced by ∼90% compared with conventional 2 × 2 butterfly equalizer, at the expense of 0.5 dB receiver sensitivity.

Usage control architecture options for data sovereignty in business ecosystems

PurposeCurrent business challenges force companies to exchange critical and sensitive data. The data provider pays great attention to the usage of their data and wants to control it by policies. The purpose of this paper is to develop usage control architecture options to enable data sovereignty in business ecosystems.Design/methodology/approachThe architecture options are developed following the design science research process. Based on requirements from an automotive use case, the authors develop architecture options. The different architecture options are demonstrated and evaluated based on the case study with practitioners from the automotive industry.FindingsThis paper introduces different architecture options for implementing usage control (UC). The proposed architecture options represent solutions for UC in business ecosystems. The comparison of the architecture options shows the respective advantages and disadvantages for data provider and data consumer.Research limitations/implicationsIn this work, the authors address only one case stemming from the German automotive sector.Practical implicationsTechnical enforcement of data providers policies instead of relying on trust to support collaborative data exchange between companies.Originality/valueThis research is among the first to introduce architecture options that provide a technical concept for the implementation of data sovereignty in business ecosystems using UC. Consequently, it supports the decision process for the technical implementation of data sovereignty.

Architectures and Key Technical Challenges for 5G Systems Incorporating Satellites

Satellite Communication systems are a promising solution to extend and complement terrestrial networks in unserved or under-served areas. This aspect is reflected by recent commercial and standardisation endeavours. In particular, 3GPP recently initiated a Study Item for New Radio-based, i.e., 5G, Non-Terrestrial Networks aimed at deploying satellite systems either as a stand-alone solution or as an integration to terrestrial networks in mobile broadband and machine-type communication scenarios. However, typical satellite channel impairments, as large path losses, delays, and Doppler shifts, pose severe challenges to the realisation of a satellite-based NR network. In this paper, based on the architecture options currently being discussed in the standardisation fora, we discuss and assess the impact of the satellite channel characteristics on the physical and Medium Access Control layers, both in terms of transmitted waveforms and procedures for enhanced Mobile BroadBand (eMBB) and NarrowBand-Internet of Things (NB-IoT) applications. The proposed analysis shows that the main technical challenges are related to the PHY/MAC procedures, in particular Random Access (RA), Timing Advance (TA), and Hybrid Automatic Repeat reQuest (HARQ) and, depending on the considered service and architecture, different solutions are proposed.

Analysis of World Experience in Creating Parallel Computing Systems Designed to Effectively Solve DIS-tasks

Author describes world experience in creating parallel computing systems by example Cray XE6 and network chip Gemini, designed to effectively solve Data intensive tasks (DIS-tasks). Most often, in modern supercomputers (SC), architecture options with shared (shared) memory are used to provide effective solutions to problems of high capacitive complexity, including those that contain mostly irregular work with memory. It is possible to provide support for a programming model with shared (shared) memory in various ways using hardware, as well as using virtualization software. Different options for implementing a shared memory programming model may vary in functionality and timing of memory accesses. The problem of the “<i>memory wall</i>” is that if arithmetic-logical operations take several processor cycles, then operations directly with the memory take several hundred cycles. If the memory is formed from the memories of computing nodes connected by a communication network, then the execution time of such a call includes the time of operation with the network to transfer addresses and data. This already increases the memory access time to several thousand cycles. The problem is that such delays in accessing data cause idle functional units of the processor - they cannot perform arithmetic and logical operations on data, because they simply do not exist due to the large delays in performing operations with memory.

Model-Based Verification of Security and Non-Functional Behavior using AADL

Modeling of system quality attributes, including security, is often done with low fidelity software models and disjointed architectural specifications by various engineers using their own specialized notations. These models are typically not maintained or documented throughout the life cycle and make it difficult to obtain a system view. However, a single-source architecture model of the system that is annotated with analysis-specific information allows changes to the architecture to be reflected in the various analysis models with little effort. We describe how model-based development using the Architecture Analysis and Design Language (AADL) and compatible analysis tools provides the platform for multi-dimensional, multi-fidelity analysis and verification. A special emphasis is given to analysis approaches using Bell-LaPadula, Biba, and MILS approaches to security and that enable a system designer to exercise various architectural design options for confidentiality and data integrity prior to system realization.

BiN: A Two-Level Learning-Based Bug Search for Cross-Architecture Binary

With the popularity of IoT (Internet of Things) devices, the security risks of these devices are increasing. However, due to the multisource heterogeneity of IoT devices, there are significant differences between the vulnerability detection of the Internet of Things and the PC-based vulnerability search method. Therefore, determining how to accurate search for vulnerabilities in large-scale cross-platform binary executable files is an urgent problem to be solved. At present, the solution to this problem mostly calculates code similarities by generating a CFG (control flow graph) from binary code, but due to the choice of architecture, OS (operating system) or compilation options, the same source code will be compiled into different assembly codes. The performance of existing vulnerability search methods for cross-architecture binaries has been challenged. To alleviate the vast differences in the assembly codes caused by different compilation scenarios, this paper proposes a cross-platform large-scale binary vulnerability search method based on two-level feature semantic learning. The contribution is that we have defined a new functional structured signature method to mitigate the massive grammatical and structural differences of binary files caused by different compilation environments. Moreover, we reasonably integrate the hierarchical model of Structure2Vec and GAT (graph attention network) and implement training from the internal control flow characteristics of the function and the call relationship between functions to obtain a more accurate functional semantic expression.