Non-functional Properties Research Articles

Flexible Web services integration: a novel personalised social approach

Dynamic composition or integration remains one of the key objectives of Web services technology. This paper aims to propose an innovative approach of dynamic Web services composition based on functional and non-functional attributes and individual preferences. In this approach, social networks of Web services are used to maintain interactions between Web services in order to select and compose Web services that are more tightly related to user’s preferences. We use the concept of Web services community in a social network of Web services to reduce considerably their search space. These communities are created by the direct involvement of Web services providers.

A Web Service Composition Framework based on Functional Weight to Reach Maximum QoS

The recent trend in the web world is to accomplish almost all the user services in every field through the web portals of the respective organizations. But a specific task with series of actions cannot be completed by a single web service with limited functionality. Therefore, multiple web services with different functionalities are composed together to attain the result. Web service composition is an approach that combine various services to fulfill the Web related tasks with preferred quality. Composition of such services will become more challenging when these web services are with similar functionalities, varying Quality and from several providers. Hence, the overall QoS (Quality of Service) could be considered as the major factor for composition. Moreover, in most of the compositions the expected QoS cannot be attained when the task is finished. Sometimes the complete task may have affected by a poor performed single web service. So, while composition, at most care should be taken to select a particular web service. Composing web services dynamically is the main method used to overcome these difficulties. However, to reach the actual functionality of the specific task the quality of each individual service is very much necessary. The QoS of a web service normally evaluated using the non-functional attributes, such as response time, availability, reliability, throughput, etc. Also, while composition, the same level of quality is not expected for individual web services that are included in the chain. So, a framework proposed in this research paper, for web service composition by setting appropriate weightage for the non-functional parameters. Experimental results show that implementation of this method will definitely pave the way to reach the maximum performance of the composition with improved QoS.

ARMET: Behavior-Based Secure and Resilient Industrial Control Systems

In this paper, we introduce a design methodology to develop reliable and secure industrial control systems (ICSs) based on the behavior of their computational resources (i.e., process/application) and underlying physical resources (e.g., the controlled plant). The methodology has three independent, but complementary, components that employ novel approaches and techniques in the design of reliable and secure ICSs. First, we introduce reliable-and-secure-by-design development of secure industrial control applications through stepwise sound refinement of an executable specification, employing deductive synthesis to enforce functional and nonfunctional (e.g., security and safety) properties of ICS applications. Second, we present a runtime security monitor at the middleware level of ICSs that protects ICS operation in the field through comparison of the application execution and the application specification execution in real time; the runtime security monitor can be synthesized from the executable specification. Finally, based on the specification, we perform a vulnerability analysis for false data injection (FDI) attacks, which leads to ICS application designs that are resilient to this type of attacks. We demonstrate the methodology through its application to a basic and typical ICS example application, describing all the tools used and ARMET, the middleware monitor that constitutes the core component of the methodology.

An ontology-based cloud infrastructure service discovery and selection system

In recent years, due to global economic downfall, many of the organisations have resorted to downsizing their Information Technology (IT) expenses by adopting innovative computing models like cloud computing, which allows business houses to reduce their fixed IT costs by promising a greener, scalable, cost-effective alternative to utilise the IT resources. A growing number of pay-per-use cloud services are now available on the web in the form of Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). With the increase in the number of services, there has also been an increase in demand and adoption of cloud services making cloud service identification and discovery a challenging task. This is due to varied service, descriptions, non-standardised naming conventions, heterogeneity in type and features of cloud services. Thus, selecting an appropriate cloud service according to consumer requirements is a daunting task, especially for applications that use a composition of different cloud services. In this paper, we have designed an ontology-based cloud infrastructure service discovery and selection system that defines functional and non-functional concepts, attributes and relations of infrastructure services. We have shown how the system enables one to discover appropriate services optimally as requested by consumers.

Certification-Based Cloud Adaptation

Performance and dependability levels of cloud-based computations are difficult to guarantee by-design due to segregation of visibility and control between applications, data owners, and cloud providers. Lack of predictability increases users’ uncertainty about the service levels they will actually achieve. Cloud tenants compete for shared resources/services at all layers of the cloud stack, and pose heterogeneous and conflicting non-functional requirements over them. These requirements have implications for platform and infrastructure layers, which have to be configured to satisfy inter-tenants requirements. We argue that adaptation techniques can play a crucial role in providing a reliable cloud, supporting definite behavior of applications and stable quality of service. Existing adaptation techniques however are unsuitable for cloud use, since they mostly focus on single tenancy, performance requirements, and are based on unverifiable evidence, which is collected in an untrusted way. In this paper, we propose a multi-tenant, general-purpose adaptation technique for the cloud, based on evidence collected by means of a trustworthy certification process. We depart from traditional heavy and comprehensive certification processes, such as ISO/IEC 27017, and consider a flexible and lightweight certification process for the cloud. It is based on authentic evidence and provides accountable validation on the compliance of a cloud-based system. Our approach adapts the cloud at all layers to maintain stable non-functional properties in certificates over time, by continuously verifying certificate validity. We assess the performance and quality of our adaptation approach in a wide range of settings.

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data‐driven services using computational and storage resources close to the end devices at the edge of the current network. To achieve higher performance in this new paradigm, one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource‐constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis are used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource and less extensive towards the estimation, discovery, and sharing objectives. As for resource types, the most well‐studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of nonfunctional properties or to quantifying the footprint of resource management techniques, including edge‐specific means of migrating data and services.

Approaches to Addressing Service Selection Ties in Ad Hoc Mobile Cloud Computing

The ad hoc mobile cloud (AMC) allows mobile devices to connect together through a wireless connection or any other means and send a request for web services from one to another within the mobile cloud. However, one of the major challenges in the AMC is the occurrence of dissatisfaction experienced by the users. This is because there are many services with similar functionalities but varying nonfunctional properties. Moreover, another resultant cause of user dissatisfaction being coupled with runtime redundancy is the attainment of similar quality computations during service selection, often referred to as “service selection ties.” In an attempt to address this challenge, service selection mechanisms for the AMC were developed in this work. This includes the use of selected quality of service properties coupled with user feedback data to determine the most suitable service. These mechanisms were evaluated using the experimental method. The evaluation of the mechanisms mainly focused on the metrics that evaluate the satisfaction of users' interest via the quantitative evaluation. The experiments affirmed that the use of the shortest distance can help to break selection ties between potential servicing nodes. Also, a continuous use of updated and unlimited range of users' assessments enhances an optimal service selection.

QoS-Aware Rule-Based Traffic-Efficient Multiobjective Service Selection in Big Data Space

The number of Web services has increased dramatically during the last few years. This has resulted in an increase in the volume of candidate services for tasks in composition systems. This has led to growth in the variety of nonfunctional properties in service selection, resulting in uncertainty (veracity issues) among such properties, which has severely affected the NP-hard aspects of service selection. Despite this, consumers in many areas would like access to a variety of selection methods such as linear programming and dynamic programming techniques. An additional problem is that the composition length (the number of tasks) of the workflow has increased, with the incorporation of research domains such as data science. These trending composition issues are challenging the computational power of existing methods. Such concerns have opened the door to research involving Big Data space. We propose a flexible, distributed selection algorithm that facilitates heterogeneous-selection methods to satisfy multiobjective composition requirements rather than rigid, specific composition requirements. However, service-selection processes in a Big Data space will inevitably increase traffic congestion caused by the increased volume of internal communication, particularly external traffic, such as Zipf and Pareto phenomena, and internal traffic during shuffling. To address these concerns, we propose solutions for each case. Our experiments demonstrate that the proposed traffic-efficient multiobjective method is well behaved when selecting services in Big Data space.

Towards the systematic analysis of non-functional properties in Model-Based Engineering for real-time embedded systems

The real-time scheduling theory provides analytical methods to assess the temporal predictability of embedded systems. Nevertheless, their use is limited in a Model-Based Systems Engineering approach. In fact, the large number of applicability conditions makes the use of real-time scheduling analysis tedious and error-prone. Key issues are left to the engineers: when to apply a real-time scheduling analysis? What to do with the analysis results? This article presents an approach to systematize and then automate the analysis of non-functional properties in Model-Based Systems Engineering. First, preconditions and postconditions define the applicability of an analysis. In addition, contracts specify the analysis interfaces, thereby enabling to reason about the analysis process. We present a proof-of-concept implementation of our approach using a combination of constraint languages (REAL for run-time analysis) and specification languages (Alloy for describing interfaces and reasoning about them). This approach is experimented on architectural models written with the Architecture Analysis and Design Language (AADL).

Multidimensional context modeling applied to non-functional analysis of software

Context awareness is a first-class attribute of today software systems. Indeed, many applications need to be aware of their context in order to adapt their structure and behavior for offering the best quality of service even in case the software and hardware resources are limited. Modeling the context, its evolution, and its influence on the services provided by (possibly resource constrained) applications are becoming primary activities throughout the whole software life cycle, although it is still difficult to capture the multidimensional nature of context. We propose a framework for modeling and reasoning on the context and its evolution along multiple dimensions. Our approach enables (1) the representation of dependencies among heterogeneous context attributes through a formally defined semantics for attribute composition and (2) the stochastic analysis of context evolution. As a result, context can be part of a model-based software development process, and multidimensional context analysis can be used for different purposes, such as non-functional analysis. We demonstrate how certain types of analysis, not feasible with context-agnostic approaches, are enabled in our framework by explicitly representing the interplay between context evolution and non-functional attributes. Such analyses allow the identification of critical aspects or design errors that may not emerge without jointly taking into account multiple context attributes. The framework is shown at work on a case study in the eHealth domain.

A systematic review to merge discourses: Interoperability, integration and cyber-physical systems

Cyber-physical systems (CPS) are developed through the cooperation of several engineering disciplines. Powerful software tools are utilized by each individual discipline, but it remains challenging to connect these into tool chains for increased efficiency. To support this endeavour, the literature on interoperability assessment was surveyed to identify concepts valuable to transfer from the interoperability to the tool integration research field. Implementation options, types of interoperability and domains described in interoperability assessment models were concepts identified as directly transferable. To avoid the problems with uptake that plague the models identified, visual analytics is suggested as a vehicle for the transfer. Furthermore, based on the use of non-functional properties as an underlying motivation for these models, cost, performance and sustainability are suggested as a common base for future research in both discourses.

Reproducible Evaluation of System Efficiency With a Model of Architecture: From Theory to Practice

Current trends in high performance and embedded computing include design of increasingly complex hardware architectures with high parallelism, heterogeneous processing elements, and nonuniform communication resources. In order to take hardware and software design decisions, early evaluations of the system nonfunctional properties are needed. These evaluations of system efficiency require electronic system-level information on both algorithms and architecture. Contrary to algorithm models for which a major body of work has been conducted on defining formal models of computation (MoCs), architecture models from the literature are mostly empirical models from which reproducible experimentation requires the accompanying software. In this paper, a precise definition of a model of architecture (MoA) is proposed that focuses on reproducibility and abstraction and removes the overlap previously existing between the notions of MoA and MoC. A first MoA, called the linear system-level architecture model (LSLA), is presented. To demonstrate the generic nature of the proposed new architecture modeling concepts, we show that the LSLA model can be integrated flexibly with different MoCs. LSLA is then used to model the energy consumption of a state-of-the-art multiprocessor system-on-chip (MPSoC) when running an application described using the synchronous dataflow MoC. A method to automatically learn LSLA model parameters from platform measurements is introduced. Despite the high complexity of the underlying hardware and software, a simple LSLA model is demonstrated to estimate the energy consumption of the MPSoC with a fidelity of 86%.

Development of stratified approach to software defined networks simulation

The stratified approach to software defined networks simulation has been proposed. It is based on Discrete Event System Specification formalism, atomic and coupled models concepts usage. The approach is aimed at simulation within the Windows environment, with an accent on the easiness of model reconfiguration. The proposed approach is also devoted to simulation-related overheads decrease. The atomic models of active (controller, switch, host) and passive (link) network components have been proposed. The coupled model of a software defined network comprising atomic models of active and passive components has been proposed. The estimations of the resulting coupled model complexity, with respect to the number of components basic atomic models, have been given. During experimentation, the pingall command usage scenario has been considered. For this purpose, the emulation via Mininet environment and the simulation on a basis of the proposed approach have been conducted. It has been shown that discrete-event simulation on a basis of the proposed approach is significantly less time-consuming. During the approach usage within the Windows environment, the absence of the need to utilize the Xming X Server and PuTTY utility for the purpose of visualization has been faced. The validity of the approach has been proven on a basis of the obtained experimental data. The adequacy of the resulting coupled simulation model of the network has been proven with t-criterion. The proposed approach can be used for the purpose of software defined networks validation with an accent on non-functional properties

A survey on run-time supporting platforms for cyber physical systems

Cyber physical systems (CPSs) incorporate computation, communication, and physical processes. The deep coupling and continuous interaction between such processes lead to a significant increase in complexity in the design and implementation of CPSs. Consequently, whereas developing CPSs from scratch is inefficient, developing them with the aid of CPS run-time sup-porting platforms can be efficient. In recent years, much research has been actively conducted on CPS run-time supporting plat-forms. However, few surveys have been conducted on these platforms. In this paper, we analyze and evaluate existing CPS run-time supporting platforms by first classifying them into three categories from the viewpoint of software architecture: com-ponent-based platforms, service-based platforms, and agent-based platforms. Then, for each type, we detail its design philosophy, key technical problems, and corresponding solutions with specific use cases. Subsequently, we compare existing platforms from two aspects: construction approaches for CPS tasks and support for non-functional properties. Finally, we outline several im-portant future research issues.

Timing Analysis of Synchronous Programs using WCRT Algebra

Synchronous languages are ideal for designing safety-critical systems. Static Worst-Case Reaction Time (WCRT) analysis is an essential component in the design flow that ensures the real-time requirements are met. There are a few approaches for WCRT analysis, and the most versatile of all is explicit path enumeration. However, as synchronous programs are highly concurrent, techniques based on this approach, such as model checking, suffer from state explosion as the number of threads increases. One observation on this problem is that these existing techniques analyse the program by enumerating a functionally equivalent automaton while WCRT is a non-functional property. This mismatch potentially causes algorithm-induced state explosion. In this paper, we propose a WCRT analysis technique based on the notion of timing equivalence, expressed using WCRT algebra. WCRT algebra can effectively capture the timing behaviour of a synchronous program by converting its intermediate representation Timed Concurrent Control Flow Graph (TCCFG) into a Tick Cost Automaton (TCA), a minimal automaton that is timing equivalent to the original program. Then the WCRT is computed over the TCA. We have implemented our approach and benchmarked it against state-of-the-art WCRT analysis techniques. The results show that the WCRT algebra is 3.5 times faster on average than the fastest published technique.

Packageability as an ‘Ility’ for Systems Engineering

The usefulness of packageability as one of the ‘ilities’ for systems engineering was investigated. It was found that packageability plays an important role in a multitude of systems, and it was investigated in several ways. First, a brief analysis showed that at least two criteria must be met for something to be considered an ility. These criteria are that the ility often manifests itself after the system is deployed, and that the potential ility must not simply be a persistent physical characteristic. It was shown that packageability meets both requirements. Second, six different systems were examined, revealing nine general ways packageability is used. They provide a way for system engineers to recognize packageability as a non-functional system property. The usefulness of packageability as a top-level non-functional system property is shown, as well as for sub-systems and components. A working definition of packageability is then proposed. Finally, a detailed treatment of packageability is presented for radar systems with transmit–receive modules. Packageability was shown to be a useful ility category that can add value to stakeholders, and that captures real system features that are not captured by other ilities. This work demonstrates that packageability should be considered as an ility for systems engineers.

API governance support through the structural analysis of REST APIs

Today, REST APIs have established as a means for realizing distributed systems and are supposed to gain even more importance in the context of Cloud Computing, Internet of Things, and Microservices. Nevertheless, many existing REST APIs are known to be not well designed, resulting in the absence of desirable non-functional properties that truly RESTful systems entail. Although existing analysis show, that many REST APIs are not fully REST compliant, it is still an open issue how to improve this deficit and where to start. In this work, we apply structural analysis of REST APIs in order to support API governance, resulting in a set of basic and aggregated metrics that characterize an API set and also guide further governance tasks. We apply the structural analysis on a set of 286 real world APIs and then demonstrate how to derive suitable metrics that represent the perceived complexity of an API, complemented and validated by a survey of developers following the AHP process. As a result, we provide effective support for API governance, helping to identify and remedy problems in APIs.

Characterization of trade-off preferences between non-functional properties

Efficient design and evolution of complex software intensive systems rely on the ability to make informed decisions as early as possible in the life cycle. Such informed decisions should take both the intended functional and non-functional properties into account. Especially regarding the latter, it is both necessary to be able to predict properties and to prioritize them according to well-defined criteria. In this paper we focus on the latter problem, that is to say how to make trade-offs between non-functional properties of software intensive systems. We provide an approach based on the elicitation of utility functions from stake-holders and subsequent checks for consistency among these functions. The approach is exploitable through an easy-to-use GUI, which is also presented. Moreover, we describe the setup and the outcome of our two-fold validation based on exploratory elicitations with students and practitioners.

Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies

The Multi-Attribute Prediction Language (MAPL), an analysis metamodel for non-functional qualities of system architectures, is introduced. MAPL features automate analysis in five non-functional areas: service cost, service availability, data accuracy, application coupling, and application size. In addition, MAPL explicitly includes utility modeling to make trade-offs between the qualities. The article introduces how each of the five non-functional qualities are modeled and quantitatively analyzed based on the ArchiMate standard for enterprise architecture modeling and the previously published Predictive, Probabilistic Architecture Modeling Framework, building on the well-known UML and OCL formalisms. The main contribution of MAPL lies in the probabilistic use of multi-attribute utility theory for the trade-off analysis of the non-functional properties. Additionally, MAPL proposes novel model-based analyses of several non-functional attributes. We also report how MAPL has iteratively been developed using multiple case studies.

Online verification in cyber‐physical systems: Practical bounds for meaningful temporal costs

AbstractCyber‐physical systems (CPS) are highly dynamic and large scale systems integrated with the physical environment that they monitor and actuate on. CPS have to adapt online to the changing nature of the physical environment; this may require the online modification of their system model, but any change should preserve correct operation. Correctness by construction relies on using formal tools, which suffer from a considerable computational overhead. As the current system model of a CPS may adapt to the environment, the new system model must be verified before its execution to ensure that the properties are preserved. However, CPS development has mainly concentrated on the design‐time aspects, existing only few contributions that address their online adaptation. We research on the pros and cons of formal tools to support dynamic changes at runtime. We formalize the semantics of the adaptation logic of an autonomic manager (OLIVE) that performs online verification for a specific application, a dynamic virtualized server system. We explore the use of formal tools based on CLTLoc to express functional and nonfunctional properties of the system. We provide empirical results showing the temporal costs of our approach.