Context: Quantum computing is rapidly evolving, offering new opportunities for solving problems in optimization, cryptography, and simulation. However, the limited availability of quantum resources makes efficient utilization of quantum hardware a current challenge. Today’s paradigms often lead to under-utilization of qubits, increased costs, and execution delays, especially in the NISQ era. Objective: This work aims to improve the utilization of quantum hardware by introducing an execution model that integrates multiprogramming at circuit level with quantum shot-wise distribution in a single policy-driven pipeline. Methods: An architecture has been implemented that combines circuit scheduling and shot distribution techniques to aggregate multiple circuits and distribute their shots across heterogeneous QPUs. The approach was empirically validated on actual IBM Quantum devices using a diverse set of reference circuits. Results: The proposal achieved a reduction in cost of 95% and a reduction in tasks 92%. Moreover, the fidelity analysis of the results showed an increase in noise, with an average increase of approximately 20% using different statistical distances. Conclusions: This research provides a usable and extensible solution to increase the efficiency, cost effectiveness, and resilience of quantum workload execution in heterogeneous and dynamic cloud environments. These results obtained suggest that users should weigh the implications of fidelity versus cost (and time) savings based on the application requirements and their goals.

Quantum software engineering has gained a lot of attention recently. Multiple traditional software engineering events have introduced a quantum software track, or a co-located quantum related workshop or other side event, indicating that quantum software is becoming a popular research topic, with more and more software engineering researchers contributing to its evolution. In this paper, we address software engineering research that aims at solving problems that emerge when quantum programs are used on industry domains. The paper is based on the keynote at the IEEE Symposium on Quantum Software: Quantum Software Engineering 2025, which took place in Helsinki, Finland, Summer of 2025. In particular, we address the state of research in quantum software engineering, its novel aspects as well as its connections to other branches of software engineering. Furthermore, in the light of this research, we also assess the maturity of quantum software engineering in the light of industry expectations.

Achieving a balance between interoperability and security in blockchain systems has led to the development of various integration mechanisms. These include the use of specialized smart contracts to facilitate cross-chain interactions, enabling reliable connections and secure transfers of information and assets. While technical interoperability is effectively addressed at lower layers, achieving semantic interoperability at the application layer remains a significant challenge. This paper proposes a mechanism to address this challenge by leveraging a model-driven approach. Metamodels, models, and transformations are created, and smart contracts are defined abstractly and then semi-automatically generated for specific blockchain platforms. The proposed approach was validated by generating contracts between Ethereum and Hyperledger, enabling semantically compatible transactions. The mechanism was further evaluated using the Technology Acceptance Model with expert participants. This evaluation demonstrated its effectiveness in specifying and transforming contracts and fostering semantic interoperability across blockchains.

The Internet of Things enhances the quality of life by automating tasks and streamlining human-device interactions. However, manual device management remains time-consuming, especially in multiple or new environments that demand new settings and interactions. Learning systems aid in automating task management, but their learning times hinder personalization and struggle when the system has to interact with multiple IoT environments, impacting user experience. This paper aims to optimize knowledge sharing for IoT environments, proposing a framework that utilizes recommender systems to find optimal and reusable configurations among IoT environments and users. To that end, this work leverages teacher-student relationships in Knowledge Distillation, facilitating knowledge sharing and enhancing knowledge reuse in learning models. In addition, real-time processing eliminates training time. This approach achieves a remarkable 93.15% accuracy.

Grover’s algorithm is a well-known contribution to quantum computing . It searches one value within an unordered sequence faster than any classical algorithm. A fundamental part of this algorithm is the so-called oracle, a quantum circuit that marks the quantum state corresponding to the desired value. A generalisation of it is the oracle for Amplitude Amplification, that marks multiple desired states. In this work we present a classical algorithm that builds a phase-marking oracle for Amplitude Amplification. This oracle performs a less-than operation, marking states representing natural numbers smaller than a given one. Results of both simulations and experiments are shown to prove its functionality. This less-than oracle implementation works on any number of qubits and does not require any ancilla qubits . Regarding depth, the proposed implementation is compared with the one generated by Qiskit automatic method, Diagonal . We show that the depth of our less-than oracle implementation is always lower. In addition, a comparison with another method for oracle generation in terms of gate count is also conducted to prove the efficiency of our method. The result presented here is part of a research work that aims to achieve reusable quantum operations that can be composed to perform more complex ones. The final aim is to provide Quantum Developers with tools that can be easily integrated in their programs/circuits.

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective—key qualities of any industry-grade software—mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differences between classical and quantum software make it challenging to directly apply classical software engineering methods to quantum systems. This challenge has led to the emergence of Quantum Software Engineering (QSE) as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyze in depth the current state of QSE research. From this analysis, the key areas of QSE are identified and explored in order to determine the most relevant open challenges that should be addressed in the next years. These challenges help identify necessary breakthroughs and future research directions for advancing QSE.

Opportunistic Mobile Ad Hoc Networks (MANETs) offer versatile solutions in contexts where the Internet is unavailable. These networks facilitate the transmission between endpoints using a store-carry-forward strategy, thereby allowing information to be stored during periods of disconnection. Consequently, selecting the next hop in the routing process becomes a significant challenge for nodes, particularly because of its impact on Quality of Service (QoS). Therefore, routing strategies are crucial in opportunistic MANETs; however, their deployment and evaluation in real scenarios can be challenging. In response to this context, this paper introduces a monitoring software-driven tool designed to evaluate the QoS of routing algorithms in physical opportunistic MANETs. The implementation and its components are detailed, along with a case study and the outcomes provided by an implementation of the proposed solution. The results demonstrate the effectiveness of the implementation in enabling the analysis of routing protocols in real scenarios, highlighting significant differences with simulation results: mobility patterns in simulations tend to be inaccurate and overly optimistic, leading to a higher delivery probability and lower latency than what is observed in the real testbed.

Progress in the realm of quantum technologies is paving the way for a multitude of potential applications across different sectors. However, the reduced number of available quantum computers, their technical limitations, and the high demand for their use are posing some problems for developers and researchers. Mainly, users trying to execute quantum circuits on these devices are usually facing long waiting times in the task queues. In this context, this work proposes a Service-Oriented architecture to reduce waiting times and optimize quantum computer usage by scheduling the circuits from different users into combined circuits that are executed at the same time. To validate this proposal, different widely known quantum algorithms have been selected and executed in combined circuits. The obtained results are then compared with the results of executing the same algorithms in an isolated way. This allowed us to measure the impact of the use of the scheduler against quantum noise. Among the obtained results, it has been possible to verify that the noise suffered by executing a combination of circuits through the proposed scheduler does not critically affect the outcomes.

Quantum computing plays a crucial role in solving complex problems for which classical supercomputers require an impractical amount of time. This emerging paradigm has the potential to revolutionize various fields such as cryptography, chemistry, and finance, making it a highly relevant area of research and development. Major companies such as Google, Amazon, IBM, and Microsoft, along with prestigious research institutions such as Oxford and MIT, are investing significant efforts into advancing this technology. However, the lack of a standardized approach among different providers poses challenges for developers to effectively access and utilize quantum computing resources. In this study, we propose a quantum orchestrator that is designed to facilitate the orchestration and execution of quantum circuits across multiple quantum service providers. The proposed solution aims to simplify the process for developers and facilitate the execution of quantum tasks using resources offered by different providers. The proposal is validated with the implementation of the proposed orchestrator for Amazon Braket and IBM Quantum. It can support both quantum and classical developers in defining, configuring, and executing circuits independently of the selected provider.

Abstract Early advances in quantum computing have provided new opportunities to tackle intricate problems in diverse areas such as cryptography, optimization, and simulation. However, current methodologies employed in quantum computing often require, among other things, a broad understanding of quantum hardware and low‐level programming languages, posing challenges to software developers in effectively creating and implementing quantum services. This study advocates the adoption of software engineering principles in quantum computing, thereby establishing a higher level of hardware abstraction that allows developers to focus on application development. With this proposal, developers can design and deploy quantum services with less effort, which is similar to the facilitation provided by service‐oriented computing for the development of conventional software services. This study introduces a continuous deployment strategy adapted to the development of quantum services that covers the creation and deployment of such services. For this purpose, an extension of the OpenAPI specification is proposed, which allows the generation of services that implement quantum algorithms. The proposal was validated through the creation of an application programming interface with diverse quantum algorithm implementations and evaluated through a survey of various developers and students who were introduced to the tool with positive results.

Abstract After decades of advances, mainly theoretical, in recent years quantum computing has begun to show its first practical applications. This new and revolutionary technology aims to enhance essential areas such as cybersecurity, financial services, or medicine. The growth of this technology has encouraged different research centers and big companies such as IBM, Amazon, and Google to dedicate considerable efforts to developing new technologies that bring quantum computing to the market. However, these technologies are not yet mature and create a significant vendor lock-in problem. Therefore, new tools are needed that facilitate access to this technology and that allow developers to increase the abstraction level at which they work. Given that the integration of quantum software should not be very different from that of classical services, we can take advantage of the knowledge acquired and use current techniques of service-oriented computing. In this work, we have carried out a technical comparison between different quantum computing service providers using a case study, by performing empirical tests based on the Travelling Salesman Problem. This study highlights the differences between the main providers. To address these differences and reduce the vendor lock-in effect, we propose an extension of the Quantum API Gateway to support the different providers and the casuistry that each one presents. This would allow programmers to deploy quantum code without vendor-specific knowledge of the major providers, which would facilitate access and simplify the development of quantum applications.

The rapid advancements in quantum computing have opened new possibilities for solving complex problems in various fields, including cryptography, optimization, and simulation. However, the current approaches to quantum computing often require a deep understanding of quantum hardware and low-level programming languages, making it difficult for software developers to create and deploy quantum services. This paper argues for the adaptation of Service-Oriented Computing principles to quantum computing, enabling a level of abstraction from hardware that allows developers to focus on application development. This will allow developers to create and deploy quantum services, similarly to how Service-Oriented Computing has made it easier to develop traditional software services. This paper presents a Continuous Deployment approach for quantum service development, which involves the generation and deployment of quantum services. To do that, we propose an extension of the OpenAPI specification to generate services implementing a quantum algorithm. To validate the feasibility of the proposed process, we use a variety of quantum algorithm implementations to test their generation and deployment of quantum services.

The Internet of Things has brought digitalization to intensive domains through the automation of their real-world processes. However, the criticality of these processes is reflected in high Quality of Service (QoS) requirements for the application to work properly. Moreover, business-level QoS, such as the operational cost, are also key to the feasibility of these applications. This QoS depends on three, closely-related dimensions: the application software, the computing devices and the communication network, which provide high flexibility to obtain different performances at different costs. Thus, to achieve optimal QoS in these scenarios, the application, computing and networking dimensions must be optimized, considering their crucial interplay in a joint effort. Furthermore, this solution must allow multi-objective optimization, finding the optimal trade-off between operational cost and application performance. In this paper, we present Multi-Objective SDN Fog Optimization (MO-SFO), a holistic framework that allows for the optimization of both the response time and the deployment cost. MO-SFO is evaluated over an emulated smart city case study, showing the cost and performance trade-off achieved in different topologies.

The irruption of the Internet of Things (IoT) has attracted the interest of both the industry and academia for their application in intensive domains, such as healthcare. The strict Quality of Service (QoS) requirements of the next generation of intensive IoT applications require the QoS to be optimized considering the interplay of three key dimensions: 1) computing; 2) networking; and 3) application. This optimization requirement motivates the use of paradigms that provide virtualization, flexibility, and programmability to IoT applications. In the computing dimension, paradigms, such as edge or fog computing, software-defined networks in the networking dimension, along with micro-services architectures for the application dimension, are suitable for QoS-strict IoT scenarios. In this work, we present a framework, named Next-gen IoT Optimization (NIoTO), that considers these three dimensions and their interplay to place microservices and networking resources over an infrastructure, optimizing the deployment in terms of average response time and deployment cost. The evaluation of NIoTO in a healthcare case study reveals a response time speed up of up to 5.11 and a reduction in cost of up to 9% with respect to other state-of-the-art techniques.

The main goal of the Web of Things (WoT) is to improve people’s quality of life by automating tasks and simplifying human–device interactions with ubiquitous systems. However, the management of devices still has to be done manually, which wastes a lot of time as their number increases. Thus, the expected benefits are not achieved. This management overhead is even greater when users change environments, new devices are added, or existing devices are modified. All this requires time-consuming customization of configurations and interactions. To facilitate this, learning systems help manage automation tasks. However, these require extensive learning times to achieve customization and cannot manage multiple environments so new approaches are needed to manage multiple environments dynamically. This work focuses on knowledge distillation and teacher–student relationships to transfer knowledge between IoT environments in a model-agnostic manner, allowing users to share their knowledge each time they encounter a new environment. This work allowed us to eliminate training times and achieve an average accuracy of 94.70%, making model automation effective from the acquisition in proactive WoT multi-environments.

Abstract There are contexts where communication with TCP/IP protocol is not possible due to the lack of infrastructure or a reliable and continuous data transmission. In this cases, alternatives such as Opportunistic Networks (OPPNets) are valid. Such challenging conditions are common in rural areas and are a significant obstacle for the deployment of eHealth technologies for older adults. Considering this context, the present work introduces Interest-based System for Communication in Isolated Areas (ISCA), an OPPNet architecture for remote monitoring and emergency detection in ageing people who live alone. For this, the energetic requirements are considered, providing efficient and sustainable operation. The proposal makes use of a routing algorithm based on interests which enables asynchronous communication among entities. ISCA is evaluated over a realistic scenario and compared with similar state-of-the-art solutions. Experimental results show that ISCA notably improves the delivery probability with an enhancement of 52.25% in comparison to the second best alternative and provides a suitable average latency. Moreover, it also achieves better performance in terms of overhead and hops number compared to the other studied protocols

The pervasive presence of the Internet results in an increasing number of people and systems interacting with each other. However, since each system only captures its own representation of reality, the information of the involved actors is scattered and even duplicated. This scattering generates problems by itself since only a small fragmented vision of the actors’ reality is available for each system. At the same time, the duplication of information in different systems can lead to inconsistencies that impede the correct integration of different systems. In this paper, we present an architecture based on the use of an upper blockchain in charge of federating a set of lower-level blockchains. This way, actor-centered data integration is achieved, offering a single, global vision of the dispersed information of each actor. This solution, called FedBlocks, relies on the blockchains’ federation concept where all interconnected systems are communicated and can share authorized data of their actors, providing a benefit for these systems and for the actors themselves. The proposed implementation has been successfully tested integrating 5689 records from 50 different institutions, belonging to 1156 actors.

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.

The Internet of Things (IoT) is more present in our daily lives than ever before, turning everyday physical objects into smart devices. However, these devices often need excessive human interaction before reaching their best performance, making them time-consuming and reducing their usability. Nowadays, Artificial Intelligence (AI) techniques are being used to process data and to find ways to automate different behaviours. However, achieving learning models capable of handling any situation is a challenging task, worsened by time training restrictions. This paper proposes a Federated Learning solution to manage different IoT environments and provide accurate predictions, based on the user’s preferences. To improve the coexistence between devices and users, this approach makes use of other users’ previous behaviours in similar environments, and proposes predictions for newcomers to the federation. Also, for existing participants, it provides a closer personalization, immediate availability and prevents most manual interactions. The approach has been tested with synthetic and real data and identifies the actions to be performed with 94% accuracy on regular users.

Abstract The development that quantum computing technologies are achieving is beginning to attract the interest of companies that could potentially be users of quantum software. Thus, it is perfectly feasible that during the next few years hybrid systems will start to appear integrating both the classical software systems of companies and new quantum ones providing solutions to problems that still remain unmanageable today. A natural way to support such integration is Service-Oriented Computing. While conceptually the invocation of a quantum software service is similar to that of a classical one, technically there are many differences and technological limitations, which refer to platform independence, decoupling, scalability, etc. To highlight these differences and the difficulties to develop quality quantum services, this paper takes a well-known problem to which a quantum solution can be provided, integer factorization, making use of the Amazon Braket quantum service platform. The exercise of trying to provide the factorization as a quantum service is carried out following the best practices, design patterns and standards existing in the implementation of classical services. This case study is used to highlight the rough edges and limitations that arise in the integration of classical-quantum hybrid systems using service-oriented computing. The conclusion of the study allows us to point out directions in which to focus research efforts in order to achieve effective quantum service-oriented computing.

The application of Internet of Things (IoT)-based solutions to intensive domains has enabled the automation of real-world processes. The critical nature of these domains requires for very high Quality of Service (QoS) to work properly. These applications often use computing paradigms such as fog computing and software architectures such as the Microservices Architecture (MSA). Moreover, the need for transparent service discovery in MSAs, combined with the need for network scalability and flexibility, motivates the use of Software-Defined Networking (SDN) in these infrastructures. However, optimizing QoS in these scenarios implies an optimal deployment of microservices, fog nodes, and SDN controllers. Moreover, the deployment of each of the different elements affects the optimality of the others, which calls for a joint solution. In this paper, we motivate the joining of these three optimization problems into a single effort and we present Umizatou, a holistic deployment optimization solution that makes use of Mixed Integer Linear Programming. Finally, we evaluate Umizatou over a healthcare case study, showing its scalability in topologies of different sizes.

Leveraging the Internet of Things (IoT) in intensive domains, such as in the Industrial Internet of Things (IIoT) or Internet of Medical Things (IoMT), provides automation and sensing solutions for complex environments through the interconnection of different sensors and actuators. However, these scenarios usually demand to meet stringent Quality of Service (QoS) requirements to work properly. Fog computing, a paradigm that brings computation and storage closer to the edge, and Software-Defined Networking (SDN), a networking paradigm that enables for network scalability and flexibility, can be combined. To do so, fog nodes that integrate both, computation resources and SDN capabilities, are leveraged to meet these stringent needs. Clearly, the placement of such fog nodes plays a key role in the achieved QoS. In this paper, an optimal fog node placement formulation is evaluated in an emulated fog and SDN environment. Results show that an optimal fog node placement can achieve a reduction of up to 59% in the network latency with a minimal jitter compared with other well-known placement methods.

The current trend of smart environments is leading towards a world where everything is considered as a service. Internet-connected smart devices make these environments largely manageable and controllable through services. In these environments, not only devices offer services, but lately, people through their smartphones can also offer services such as personal information provided by the name, the preferences, or the location, promoting the offer of almost anything as a service. However, this high supply of services makes it more difficult for IoT systems to identify which services to use to solve a particular need. This paper proposes a solution to characterize services homogeneously and a service selection mechanism is outlined considering the properties of the services and the context in which they are found. With this proposal, services are defined commonly to facilitate a smart selection by IoT applications.

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.

This artifact is a guideline for the generation of APIs through the APIGEND (API Generator for End Devices) tool. This tool is an extension of the OpenAPI Generator [1] . It originally allows developers to create both the client and server side through an OpenAPI Specification with a ServerCentric style in different languages. The extension developed also allows one to generate APIs for end devices, specifically for Android devices and ESP32 Microcontrollers, making the application of the Edge [2] and Mobile-Centric [3] paradigms easier.

We introduce our solution developed for data privacy, and specifically for cognitive security that can be enforced and guaranteed using blockchain technology in SAAL (Smart Ambient Assisted Living) environments. Personal clinical and demographic information segments to various levels that assures that it can only be rebuilt at the interested and authorized parties and no profiling can be extracted from the blockchain itself. Using our proposal the access to a patient's clinical process resists tampering and ransomware attacks that have recently plagued the HIS (Hospital Information Systems) in various countries. The core of the blockchain model assures non-repudiation possible by any of the involved information producers thus maintaining ledger fidelity of the enclosed historical process information. One important side effect of this data infrastructure is that it can be accessed in open form, for research purposes for instance, since no individual re-identification or group profiling is possible by any means.

In 2012, the startup Gloin began to develop a new social mobile application, called BeeFun, allowing users to communicate with each other based on their contextual information, i.e., their history, location, preferences, etc. For two years the company invested a great amount of resources to develop the idea, to specify the business plan and to implement the product. In the last phase, seeking funding to launch the product, Gloin was finalist of the 2013 LaunchPad Denmark Business Plan Cup. The finalists won the access to an acceleration program to get funding and launch their products in Denmark. In this process, some flaws in the idea and in the business plan that endangered the project success were detected. In this paper, we detail the process of developing BeeFun, the major failings, the lessons learnt and how Gloin pivoted to develop a new product called nimBees. A product that is currently getting the attention of medium and large enterprises. In addition, some of the barriers that the promoters of the idea, as researchers, had to overcome are also detailed.