This study investigates whether cloud provider solutions offer cost advantages over private cloud infrastructures in large-scale government settings. Focusing on the case of Greek Governmental Cloud (GCloud), we conduct a comprehensive cost comparison across three deployment models: the existing on-premise infrastructure, an IaaS cloud provider solution and a PaaS cloud provider solution. The cost analysis considers a five-year operational time window and uses real procurement data and updated discount policies. We take into consideration that the organization already has data center infrastructure and explores the migration options to cloud provider solutions. The cost analysis findings show that although provider solution can match or slightly undercut on-premise costs under specific conditions where agility is important, there is no financial advantage regarding standard operation needs. This real-world case study of the Greek Government Cloud highlights that cloud migration decisions for large organizations, with existing IT infrastructures, should be taken after thorough cost evaluation, accurate workload analysis, and a deep understanding of dynamic pricing models. Moreover, this study offers practical recommendations to decision-makers that navigate complex infrastructure choices. While infrastructure choices involve factors such as performance, security, and operational flexibility, this study intentionally focuses solely on the cost, aiming to provide a clear and quantifiable economic comparison. In general, this study aims to open a discussion about whether Cloud solutions are a panacea, especially in government settings.

IoT paradigm has revolutionized our daily routine life, connecting a plethora of smart devices, sensors, frameworks, intelligent systems and humans, in order to provide innovative solutions to everyday problems. With the advent of emerging technologies, Cyber-Physical Systems (CPSs) shown great potential in latest years in various application areas, such as healthcare, urban environments, agriculture, transportation, environment monitoring, home automation e.t.c. As they comprise of parts interacting with the physical environment and others having computing and communication capabilities, they constitute a prominent example of systems-of-systems, while the autonomous operation of their components should be ensured. Autonomous components should be smart enough to adjust in the environment they operate, while learning from their peers. The presentation targets at open issues in CPS engineering to promote their autonomy utilizing AI tools and methods and discusses ongoing projects on smart CPS in three different levels: 1) Smart aggregators to manage sensor and actuators and collaborate within each at the edge with no central control. The principles of developing a self-control management middleware for this purpose along with implementation results will be explored. 2) Service integration in a smart CPS environment ensuring the quality of complex services provided to users. A quality-aware event-based platform for the coordination of micro-services aiming at the development of CPS applications and the notion of event fabrication to manage missing events from sensors will be presented. 3) The integration of humans into smart CPS and their wiliness to become part of them. A multi-view design approach focusing on human concerns towards smart systems and the concept of human critically will be discussed. These efforts are presented in the context of specific case studies from prominent CPS domains, targeting smart building management, smart farm management and remote patient monitoring.

Large Language Models (LLMs) are pivotal in generative AI applications. Consequently, major cloud providers, such as Amazon, Azure, and Google, introduce the offering of LLM-as-a-Service (LLMaaS) products to enable businesses to leverage NLP, data analysis, and predictive modeling in their cloud solutions. This paper explores the incorporation of LLM-as-a-Service solutions into business workflows with a focus on inference costs. We review various LLMaaS offerings and conduct a comparative analysis based on a real-world case study of an AI chatbot.

Compliance to regulatory requirements is a critical concern in information system development projects. Managing this aspect is increasingly challenging while failures impose costly consequence on the organizations world-wide. However, how a legislation may or may not affect information system development projects is often not easily identifiable due to lack of clear understanding and guidelines. This paper presents compliant information system development (CISMET) ontology, exploiting concepts from 21 existing ontologies (regarding regulatory compliance and information system development). The key findings are the six parent classes in the CISMET ontology describing the system development goals, services, process, activities, artifacts, and resources. Also, there are 26 sub classes and 21 class properties that describe various concepts and their relationships in regulatory compliant information system development. The General Data Protection Regulation (GDPR) of the European Union has been instantiated in the proposed framework to indicate how regulatory requirements compliance concepts are mapped to system development projects. Thus, involved stakeholders (information system researchers and system developers) may identify dependencies and actions needed with relation to various rules in the regulation and their link to the system elements through a relevant software application. The latter enables users to easily submit queries towards the backend ontology through a specialized front-end application that can aid in formulating and submitting these queries.

Systems Modeling Language (SysML) is an object management group standard for systems-of-systems engineering. It enables the description of complex system models; however, it cannot effectively support all system engineering activities. For instance, system performance evaluation is usually performed via simulation. In this case, the transformation of SysML system models to executable simulation models for specific simulation methodologies and tools is required. Model transformation is a key component for addressing the challenges of seamless integration of SysML model simulation in model-based system engineering. In this paper, we explore a declarative approach, based on the query/view/transformation-relations (QVT-R) standard, for the transformation of SysML models to executable simulation models, fully adhering model-driven architecture (MDA) concepts. It is supported by a framework implemented to provide executable simulation model and code generation. Methodological guidelines, for the effective use of a declarative language as QVT-R, for model transformation, are provided, emphasizing the utilization of existing domain-specific SysML profiles, as well as executable simulation library components. The experience obtained from two different domains, namely, enterprise information and railway transportation systems, modeled as systems-of-systems via SysML, is discussed, based on a quantitative analysis of the respective QVT-R transformations.

This Paper presents an Internet of Things (IoT) based framework to monitor ECG for biometric recognition and acceleration for fall detection. To this end, an-IoT based Remote Elderly Monitoring System (REMS) platform is described. REMS consists of a Shimmer3TM device transmitting physiological signal wirelessly to a nearby gateway which routes the data to a remote IoT-platform, able to accommodate dynamically changing configurations. The Shimmer firmware has been modified to send data based on the compressive sensing theory in order to ameliorate energy consumption in addition of real data, and the analysis and processing are done locally on a heterogeneous multicore edge device in order to solve latency issues related to cloud reliance. Subsequently the framework has been designed to handle the different parameter settings and multiple scenarios in a user-friendly way. Furthermore, it allows the user to monitor physiological data and acquire some feedback related to their analysis. Depending on a scenario (energy save, secure communication) the system can be configured manually or automatically to monitor ECG or acceleration data and displays them, it can also identify the subject based on ECG recognition and detect fall if it occurs.

The amount of sources and sheer volumes of spatiotemporal data have met an unprecedented growth during the last decade. As a consequence, a rapidly increasing number of applications are seeking to generate value by crunching those data. The development of a system that will tap into the potential value of the spatiotemporal big data analysis for a multitude of applications remains one of the biggest challenges in computer engineering. This paper delves into the key-characteristics of the most prominent suchlike systems. In particular, it provides a thorough analysis of NoSQL datastores as well as a traditional relational database system in terms of their geospatial querying capabilities.

Economic growth in Europe has been, strongly associated with urbanization, overwhelming cities with vehicles. This renders mobility inside cities problematic, since it is often associated with large waste of time in traffie congestions, environmental pollution and accidents. Cities struggle to invent and deploy “smart” solutions in the domain of urban mobility, so as to offer innovative services to citizens and visitors and improve the overall quality of life. In this context, the paper discusses on the fundamental challenges that cities face when trying to become smarter, focusing on the particular area of smart buildings and the management of multi-core, smart building architectures and presents some key research achievements and relevant research challenges.

Model-based Systems Engineering (MBSE) promises efficient and effective systems development, by providing integrated system model views and streamlining the transition between different development activities. For instance, system testing with simulation should be provided as a simple facility for the performance evaluation of complex systems. Transportation systems are complex and their behavior is determined by dynamic factors. However, research efforts define simulation models for transportation systems, using custom or simulation-specific notation. Additionally, model-based approaches for transportation systems emphasize peripheral issues, such as safety conditions and environmental impact. In this work, a framework that enables seamless performance evaluation of Railway Transportation System (RTS) models via simulation is proposed. The de facto standard for MBSE modeling, Systems Modeling Language (SysML), is selected as the modeling infrastructure, while other standards, like Query/View/Transformation (QVT), are used for the generation of executable simulation models. The latter can be simulated in Discrete Event System Specification (DEVS) simulators and the simulation results are returned in the RTS SysML model. Additionally, the application of the framework in the public RTS of Athens and the obtained simulation results are presented.

The Future Internet (FI) era dictates the deployment of high complexity systems having a variety of properties such as adaptivity, self configuration and self optimization. This paper discusses on the design and deployment of an autonomic management framework, targeting real-time optimization of operational properties in a smart building cognitive environment. The architecture of an autonomous smart building system is described, focusing on diverse requirement satisfaction, including response time, energy efficiency and users' satisfaction. The main systems' components are introduced along with a indicative operation scenario that demonstrates multi - criticality issues explored. The scope of the paper is a) to point out challenges in building an autonomic smart building environment to support multi-critical applications and b) to indicate efficient solutions for dealing with them, promoting self-configuration and self-optimisation properties.

Enterprise social networks are gaining momentum as a platform for collaboration between members of an enterprise, leading to the notion of Enterprise 2.0. Participant collaboration includes communication, information and data dissemination and also application execution, leading to task completion. This paper presents an approach extending social network data model to promote participant collaboration through collaborative application execution and management. The proposed extensions support not only process monitoring but actual execution, management and composition of applications within the context of the social network, in a uniform way. In order to achieve this effectively, external services must be wrapped and integrated in the social network environment as applications, and consequently they must be mapped to business tasks executed in each participant profile, according to their actual role and responsibilities in the enterprise. The social network framework must take into account the actual roles, relationships and responsibilities of the members of an enterprise, which, combined, dictate enterprise workflow schemes and policies. To explore the potential of the proposed approach, a prototype social network platform is discussed as a case study.

Web service discovery on the web is not a trivial task as the number of available web service descriptions continuously increases, and global UDDI registries are no longer available. As discovery through conventional, general-purpose search engines does not yield satisfactory results, a more promising alternative should be explored through specialized search engines. This paper explores the design and implementation of such a framework, resulting in WESS, a search engine targeted to discovering and retrieving web service descriptions. The presented system features an adaptive web service description collection process, through specialized and directed crawling, as well as an enhanced indexing and retrieval mechanism, which handles description documents as semi-structured text, separating actual information from tags and annotations. The paper also presents experiments and use cases regarding different search scenarios, in addition to performance results.

The paper presents an integrated approach for automated semantic web service composition using AI planning techniques. An important advantage of this approach is that the composition process, as well as the discovery of the atomic services that take part in the composition, are significantly facilitated by the incorporation of semantic information. OWL-S web service descriptions are transformed into a planning problem described in a standardized fashion using PDDL, while semantic information is used for the enhancement of the composition process as well as for approximating the optimal composite service when exact solutions are not found. Solving, visualization, manipulation, and evaluation of the produced composite services are accomplished, while, unlike other systems, independence from specific planners is maintained. Implementation was performed through the development and integration of two software systems, namely PORSCE II and VLEPPO. PORSCE II is responsible for the transformation process, semantic enhancement, and management of the results. VLEPPO is a general-purpose planning system used to automatically acquire solutions for the problem by invoking external planners. A case study is also presented to demonstrate the functionality, performance, and potential of the approach.

Information system architecture design is a complex task depending on both functional and non-functional requirements. Since system architecture definition is strongly related to system performance, non-functional requirements play a significant role during enterprise information system design. To explore the effect of non-functional requirements on system design process, a model-based approach emphasizing non-functional requirements is proposed. To facilitate the designer to effectively define and handle requirements during architecture design, a number of system views are offered, each of them focusing on discrete design issues and satisfying different kind of requirements. A consistent requirement model is defined representing how non-functional requirements are related between them and to system components forming the overall system architecture. SysML has been adopted as the modeling language, since it enables requirement definition and can be formally extended. Moreover, requirement derivation process is discussed and a case study where the proposed concepts are applied in practice while redesigning the legacy system of a large-scale organization is presented.

Discrete event simulation specification (DEVS) is a formalism facilitating hierarchical and modular description of the models executed using DEVS simulators. Lack of standardized, easy-to-use interface enabling simulation practitioners to define their models is an important drawback, since in most cases DEVS models are defined as C++ or Java programs based on existing simulator-specific DEVS libraries. Standard MDA concepts can be applied for the construction of DEVS models executed in different programming environments. DEVS models can be defined using DEVSML, a platform-independent, XML-based format. SysML is proposed as a standardized, graphical representation language of DEVS models stored in DEVSML, consequently transformed into executable code for existing DEVS Simulators, as DEVSJava and DEVSim++. The first step toward this endeavor, is the formal definition of the DEVS SysML profile proposed in this paper.

Extension mechanisms offered by UML 2.0 are often explored in order to define UML profiles that serve specific modeling purposes. These UML 2.0 profiles should be effectively accommodated by standard UML-based modeling tools, which provide the means for applying them in practice. Almost every UML 2.0 modeling tool supports the definition of stereotypes and the description of constraints in Object Constraint Language. However, implementing a profile in practice often entails the development of additional functionality. This requirement mainly stems from the fact that when dealing with complex models it is more efficient for end-users to help them enforce a constraint rather than notify them when it is broken. Such issues, encountered when developing a UML 2.0 profile for enterprise information systems engineering using Rational Software Modeler as a standard UML 2.0 modeling tool, are discussed in the paper.

System engineering is the process of defining the desired architecture of a system and exploring performance requirements, ensuring that all system components are identified and properly allocated and system resources can provide the desired performance. A consistent framework for enterprise information engineering, compatible to Zachman framework is proposed. It consists of a metamodel describing different system views and the relations between them, a corresponding methodology of discrete stages, performed by the system designer or software tools, and a UML 2.0 profile for view representation

Enterprise Information Systems can be described according to the Open Distributed Processing Reference Model (RM-ODP), where five different viewpoints are specified analyzing various aspects of the system. Configuration issues are explored in the Engineering Viewpoint of RM-ODP. In practice, configuration issues are explored in discrete stages, supported by autonomous software tools, each of which adopts its own metamodel for system representation. We propose a platform independent framework, which focuses on the Engineering Viewpoint of Enterprise Information Systems managing application configuration and network design issues independently of application development progress. In order to apply this framework using existing tools, model exchangeability and tool coordination must be supported by standard, open methods. Thus, a common metamodel is proposed to generate enterprise information system models, which are stored in XML. A UML 2.0 profile is defined to visualize these models, facilitate the designer to interact with them and coordinate specific tool invocation.

Enterprise information systems consist of interrelated intranet-based and Internet-based applications, thus the Web platform serves well as the middleware for their development. Even though, in many cases, discrete applications operate efficiently, the overall system performance is less than expected. A potential cause is that, configuration issues although interrelated are solved in isolation. The architecture and performance characteristics of the underlying network affect application configuration. Thus, the symbiotic relationship between application and network architecture must also be explored. We argue that, in order to effectively configuring and evaluating enterprise information systems, network infrastructure restrictions must be incorporated within application configuration process and vice versa. An effective four-stage methodology is proposed for this purpose. It is important to note the significance of a consistent model for the representation of system entities throughout all stages. UML-like notation is used for system representation. Alternative views of the system emphasizing specific configuration stages are offered through UML package representation. Since the modelling scheme is extendable, the adaptation of UML constructs simplifies the process of extending or customizing the model. A case study where the proposed methodology is used for the configuration a large-scale medical information system and the experience obtained are also presented.

Athens Medical School is one of the largest medical research institutions in Greece, where educational activities are combined with every-day practice in the University Hospital. The laboratories operating in the University Hospital produce a large amount of research material, mainly consisting of medical images and videos in digital format. In this paper, we present the Digital Library System built to support the collections of Athens Medical School laboratories. The system facilitates access through the Web to medical research material and on-line presentations/lessons. Laboratory collections have different requirement regarding digital material structure and metadata modelling. Thus, while designing the Digital Library architecture, the organisation and administration of dynamically created collections was explored We introduced the term dynamic collection management to denote the support of automated collection definition and management within an integrated Digital Library environment. Laboratory staff is responsible for selecting the material to be added in the library, while they also participate in metadata creation. Furthermore, they use this material to create presentation or on-line tutorials, also stored in the Digital Library. To facilitate the aforementioned functionality the Digital Library system also supports a complex workflow environment.

In faster-than-real-time simulation (FRTS), a valid model may be maintained in real time through comparing simulation results with the corresponding system observations at regular time intervals. As, in the general case, simulation does not reach a steady state within each such interval, experiments must involve multiple replications, which must be completed (i.e. reach predictions) within the given time. In the past, methods have been introduced for examining the possibility of executing a specific number of replications, based on measurements obtained from a number of initial replications. We discuss how such a method may be applied, both in sequential and distributed simulation, for determining the maximum number of replications that may be executed in the given time. Nevertheless, n may be less than a minimum n/sub min/ required to support the reliability of results. To deal with this case, we need to decrease the time period for which predictions are made, to save up execution time. We propose method extensions for determining the time interval for which results may be reached by n/sub min/ replications. Experimental results from various models are presented to substantiate the validity and effectiveness of the proposed method.

Using simulation to support reaching conclusions for real-time processes imposes that models are thoroughly validated. This paper discusses widely adopted techniques for testing the validity of simulation results against real observations and proposes a more effective comparison technique for the case where a single system data set and multiple model data sets are available. To apply this technique, we consider the system data set as a discrete signal and use M-fold decimation, fulfilling the essential requirements Imposed according to signal processing theory. Experimental results are also presented to exhibit the applicability and effectiveness of the proposed technique.

Complexity of applications operating in a network environment has been considerably increased, since numerous architectural models, such as the client/server model and its extensions, have lately emerged. When dealing with distributed applications, network modeling is not so demanding and modeling solutions for widely used network components are already adopted by commercial tools. We introduce a modeling approach for distributed systems, putting the emphasis on distributed applications. This approach enables the analytical description of applications on the basis of predetermined, high-level operations (or actions) which can be customized to conform to specific architectural models. Operations are ultimately expressed in terms of primitive actions. Through this multi-layer decomposition scheme, in-depth analysis of application mechanisms is promoted. The modeling approach is oriented towards performance evaluation through simulation and a simulation tool has been constructed for this purpose. Modeling examples and a case study for a distributed database banking system are also presented.