Smart cities have deployed a myriad of devices to sense the status of the city and its citizens in order to reconfigure different elements to improve the quality of life. However, the analysis and reconfiguration of these elements on the fly can lead to unforeseen problems. The digital twin paradigm has risen as a promising technology to analyze and test these re-configurations before their execution. These digital twins are usually centralized in the cloud. However, the emulation of highly distributed systems can lead to scalability, response time, and security and privacy problems. In this paper, we propose a hierarchical and distributed architecture for digital twins, deployed over the Cloud-to-Thing Continuum. The proposal is illustrated by means of a case study about public transportation in smart cities.

Urban Digital Twins (UDT) represent a powerful tool to effectively make cities smart. Generally, UDTs are linked with other Digital Twins to build ecosystems where the citizen is at the heart of the ecosystem. This is why citizens should be considered first-class entities in the UDTs. At the same time, citizens’ privacy cannot be compromised. In this paper, we propose to integrate citizens’ digital twin in UDTs through their digital avatars (DAs). DAs allow exploiting citizens’ information, behavioral habits and personal preferences, while allowing them to have full control of their own data. We present our architecture that makes use of the Cloud-to-Thing Continuum to optimize available processing resources. We focus on a case study of the public transport service of the city of Malaga (Spain) and describe how we are approaching its implementation. Finally, we validate such UDT implementation through tests that evaluate its accuracy and the factors affecting its performance.

The exaggerated use of smartphones and growing informatization of the environment allows modeling people’s behavior as a process, namely, a social workflow, where both individual actions and interactions with other people are captured. This modelling includes actions that are part of an individual’s routine, as well as less frequent events. Although infrequent actions may provide relevant information, it is routine behaviors that characterize users. However, the extraction of this knowledge is not simple. Current process mining techniques face problems when analyzing large amounts of traces generated by many users. When very different behavioral patterns are integrated, the resulting social workflow does not clearly depict their behavior, either individually or as a group. Proposals based on frequent pattern mining aim to distinguish traces that characterize frequent behaviors from the rest. However, tools that allow grouping/filtering of users with a common behavior pattern are needed beforehand, to analyze each of these groups separately. This study presents the so-called federated process mining and an associated tool, SOWCompact, based on this concept. Its potential is validated through the case study called activities of daily living (ADL). Using federated process mining, along with current process mining techniques, more compact processes using only the social workflow’s most relevant information are obtained, while allowing (event enabling) the analysis of these social workflows.

Summary During the last decade, the mobile application market has grown steadily thanks to the massive use of smartphones and the emergence of cloud computing for offloading computation tasks and improving the quality of experience. With the more recent deployment of Internet of Things (IoT) devices, this cloud‐based architectural design and the corresponding communication flow has been maintained. Nevertheless, the increasing amount of information exchanged, the stringent requirements of many IoT applications, and the need for these applications to adapt their behavior in real time to the user's context set these architectural assumptions a challenge. Paradigms such as mobile, mist, and edge computing have recently been proposed to exploit the computational and storage capabilities of current smartphones and IoT devices in order to onload some tasks onto them, reducing the overhead on both the cloud and the network. Currently, the application of these paradigms requires much attention from skilled developers to create ad hoc systems, as there lack standards and tools facilitating their use. This communication introduces Human Microservices as a framework facilitating the deployment of APIs on companion devices in order to provide personal and updated information that can be consumed by other entities. The framework improves the integration of humans in the IoT loop and facilitates the deployment of computation units in devices closer to end users, enhancing system response time by reducing the stress on cloud and network infrastructure. The proposed framework is based on existing standards in order to improve software quality and shorten the learning curve.

Population ageing, together with the desire to maintain an autonomous lifestyle, poses today’s societies with a challenge that technological advances can help considerably to cope with. The widespread use of smartphones and their increasing computing power and storage capacity make them the ideal tool to achieve this goal. In this paper, we present Digital Avatars, a software framework adapted to the needs of older adults who wish to preserve their lifestyle, but who require assistance through technology. Building on previous work on the People as a Service model, Digital Avatars takes advantage of a smartphone’s capabilities and services to collect information about the people who own them. To do this, it applies Complex Event Processing techniques extended with uncertainty to infer the habits, preferences, and needs of the device owner to build with them an enhanced virtual profile of the user. These virtual profiles are the mechanism for monitoring the quality of life of older adults: analyzing their patterns of activity, reminding them of medication schedules, or detecting risky situations that generate alerts to relatives, caregivers, or the community health system.

The number of devices connected to the internet is constantly increasing. This large amount of devices can be used to improve people's interaction with their environment. However, this also implies an increase in the complexity when interacting with so many heterogeneous devices. Automating this process is key to keep up with this growth. This is the purpose of the People as a Service model (PeaaS), which works towards developing virtual profiles for every user in their own mobile devices under their full control. These profiles allow to establish preferences and predefined parameters, which are then used by the devices they connect to. By integrating both the information in the users' virtual profiles and the information given by the devices they connect to, we can create a context in which to make smart decisions and apply them to the devices, all of this in a decentralised way. This allows for a programmatically configuration of the devices without the need of the user's intervention. In order to put the proposal in action, we have developed a treasure hunting game as a proof of concept to bring to the spotlight the utility of an environment with programmatically adapted devices.

The different implementations of cloud computing services developed by each cloud vendor have resulted in a heterogeneity of APIs and libraries which most developers of cloud-based applications must fight to understand. This so called vendor lock-in effect leads to a substantial increment on the development effort required to switch the initially selected cloud service used by an application to a different one. Different initiatives have emerged to solve this problem, such as standardization attempts, and intermediate systems or middlewares. Instead, our approach makes use software adaptation techniques for tackling the vendor lock-in problem and facilitating the development of cloud applications that are not coupled to any specific platform. In this paper, a case study application is presented in order to illustrate how the vendor lock-in effect appears and to make an estimation of the effort required for its migration to a different platform. This way we show the benefits of our approach for reducing the cloud service migration efforts. Such solution is sketched briefly, and the main steps of the adaptation process are described.

Cloud computing is a new paradigm that allows users to access computing resources in a dynamic, flexible and scalable manner. It has drawn the interest of multiple users, and in a short period of time it has experienced a notorious hype. However, its numerous strengths are mitigated by the lack of standardization which the technology suffers from. Different cloud vendors provide and manage similar resources in a different manner, thereby coupling the application to its targeted cloud. Companies that consume cloud services are locked-in to a single cloud vendor due to the high costs of migrating software in the cloud, preventing them from changing their cloud provider or having multiple providers. In this paper we explore a solution to the cloud vendor lock-in problem based on the use of model-driven engineering and software adaptation techniques. The proposed solution is both cloud vendor and user friendly as it allows the former to freely define their own cloud policies, whilst users continue to be free to choose a cloud provider, even after the application has been developed.

Adaptation is of utmost importance in systems developed by assembling reusable software services accessed through their public interfaces. This process aims at solving, as automatically as possible, mismatch cases which may be given at the different interoperability levels among interfaces by synthesizing a mediating adaptor. In this paper, we present a toolbox that fully supports the adaptation process, including: (i) different methods to construct adaptation contracts involving several services; (ii) simulation and verification techniques which help to identify and correct erroneous behaviours or deadlocking executions; and (iii) techniques for the generation of centralized or distributed adaptor protocols based on the aforementioned contracts. Our toolbox relates our models with implementation platforms, starting with the automatic extraction of behavioural models from existing interface descriptions, until the final adaptor implementation is generated for the target platform.

Component-Based Software Engineering focuses on the reuse of existing software components. In practice, most components cannot be integrated directly into an application-to-be, because they are incompatible. Software Adaptation aims at generating, as automatically as possible, adaptors to compensate mismatch between component interfaces, and is therefore a promising solution for the development of a real market of components promoting software reuse. In this article, we present our approach for software adaptation which relies on an abstract notation based on synchronous vectors and transition systems for governing adaptation rules. Our proposal is supported by dedicated algorithms that generate automatically adaptor protocols. These algorithms have been implemented in a tool, called Adaptor, that can be used through a user-friendly graphical interface.

Aspect oriented software development provides a suitable support for software system evolution. The system properties are better encapsulated resulting in easier manipulation. Besides, new properties or changes can be added to the systems as new aspects, reducing cost, effort and time. However, adding new aspects to an existing AO system could produce unexpected behaviour. In particular, when there is an aspect already operating in the same joint point that the new one, the two aspects may interfere each other. In this context, TITAN is a framework that supports system evolution through aspect oriented techniques, allowing to verify whether the added behaviour produces the expected results. The starting point is the UML specification of both the initial system and the aspects. From that point, the specification is validated generating a CCS algebraic description of the system. Next, extended (finite) state machines are automatically generated to verify, simulate, and test the modelled system behaviour. Additionally, the result of that process can also be compared with the behaviour of the new running system.

Reuse of software entities such as components or web services raise composition issues since, most of the time, they present mismatching behavioural interfaces. Here, we particularly focus on systems for which the number of transactions is unbounded, and unknown in advance. This is typical in pervasive systems where a new client may show up at any moment to request or access a specific service. Hence, we advocate for the use of the pi-calculus to specify component interfaces. The pi-calculus is particularly suitable for creating new component instances and channels dynamically. The unbounded number of transactions and the use of the pi-calculus obliges to apply the composition at run-time. In this paper, we propose a run-time composition engine that solves existing mismatches.

Traditional IDLs were defined for describing the services that objects offer, but not those services they require from other objects, nor the relative order in which they expect their methods to be called. Some of the existing proposals try to add protocol information to object interfaces, but most of them fail to do so in a modular way. In this paper we propose an extension of the CORBA IDL that uses a sugared subset of the polyadic /spl pi/-calculus for describing object service protocols, based on the concept of roles. Roles allow the modular specification of the observable behavior of CORBA objects, reducing the complexity of the compatibility tests. Our main aim is the automated checking of protocol interoperability between CORBA objects in open component-based environments, using similar techniques to those used in software architecture description and analysis. In addition, our proposal permits the study of substitutability between CORBA objects, as well as the realization of dynamic compatibility tests during their runtime execution.

Traditional IDLs were defined for describing the services that objects offer, but not those services they require from other objects, nor the relative order in which they expect their methods to be called. In this paper we propose an extension of the Common Object Request Broker Architecture (CORBA) interface description language (IDL) that uses a sugared subset of the polyadic $\pi$-calculus for describing object service protocols, aimed at the automated checking of protocol interoperability between CORBA objects in open component-based environments. In addition, some advantages and disadvantages of our proposal are discussed, as well as some of the practical limitations encountered when trying to implement and use this sort of IDL extension in open systems.