Everton Cavalcante

On the interplay of Internet of Things and Cloud Computing

The Internet of Things (IoT) is a novel paradigm relying on the interaction of smart objects (things) with each other and with physical and/or virtual resources through the Internet. Despite the recent advances that have made IoT a reality, there are several challenges to be addressed towards exploiting its full potential and promoting tangible benefits to society, environment, economy, and individual citizens. Recently, Cloud Computing has been advocated as a promising approach to tackle some of the existing challenges in IoT while leveraging its adoption and bringing new opportunities. With the combination of IoT and Cloud Computing, the cloud becomes an intermediate layer between smart objects and applications that make use of data and resources provided by these objects. On the one hand, IoT can benefit from the almost unlimited resources of Cloud Computing to implement management and composition of services related to smart objects and their provided data. On the other hand, the cloud can benefit from IoT by broadening its operation scope to deal with real-world objects. In spite of this synergy, the literature still lacks of a broad, comprehensive overview on what has been investigated on the integration of IoT and Cloud Computing and what are the open issues to be addressed in future research and development. The goal of this work is to fill this gap by systematically collecting and analyzing studies available in the literature aiming to: (i) obtain a comprehensive understanding on the integration of IoT and Cloud Computing paradigms; (ii) provide an overview of the current state of research on this topic; and (iii) identify important gaps in the existing approaches as well as promising research directions. To achieve this goal, a systematic mapping study was performed covering papers recently published in journals, conferences, and workshops, available at five relevant electronic databases. As a result, 35 studies were selected presenting strategies and solutions on how to integrate IoT and Cloud Computing as well as scenarios, research challenges, and opportunities in this context. Besides confirming the increasing interest on the integration of IoT and Cloud Computing, this paper reports the main outcomes of the performed systematic mapping by both presenting an overview of the state of the art on the investigated topic and shedding light on important challenges and potential directions to future research.

A Web Platform for Interconnecting Body Sensors and Improving Health Care

The Internet of Things (IoT) is a paradigm in which smart objects actively collaborate among them and with other physical and virtual objects available in the Web in order to perform high-level tasks for the benefit of end-users. In the e-health scenario, these communicating smart objects can be body sensors that enable a continuous real-time monitoring of vital signs of patients. Data produced by such sensors can be used for several purposes and by different actors, such as doctors, patients, relatives, and health care centers, in order to provide remote assistance to users. However, major challenges arise mainly in terms of the interoperability among several heterogeneous devices from a variety of manufacturers. In this context, we introduce EcoHealth (Ecosystem of Health Care Devices), a Web middleware platform for connecting doctors and patients using attached body sensors, thus aiming to provide improved health monitoring and diagnosis for patients. This platform is able to integrate information obtained from heterogeneous sensors in order to provide mechanisms to monitor, process, visualize, store, and send notifications regarding patients’ conditions and vital signs at real-time by using Internet standards. In this paper, we present blueprints of our proposal to EcoHealth and its logical architecture and implementation, as well as an e-health motivational scenario where such a platform would be useful.

A systematic survey of service identification methods

One of the major challenges for the adoption of the service-oriented architecture (SOA) is the service identification phase that aims to determine which services are appropriate to be implemented. In the last decade, several service identification methods (SIMs) were proposed. However, the service identification phase still remains a challenge to organizations due to the lack of systematic methods and comprehensive approaches that support the examination of the businesses from multiple perspectives and consider service quality attributes. This work aims to provide an overview of existing SIMs by detailing which service’s perspectives, stated as relevant by the industry, are addressed by the SIMs and also by synthesizing the identification techniques used by them. We have performed a systematic survey over publications about SIMs from 2002 to June 2013, and 105 studies were selected. A detailed investigation on the analyzed SIMs revealed that the identification techniques applied by them have a correlation on how they address many of the service’s perspectives. In addition, they are supporting the SOA adoption by handling many perspectives of the OASIS’ reference architecture for SOA. However, most of them do not explicitly address service quality attributes and few studies support the evaluation of both. Therefore, future research should follow the direction toward hybrid methods with mechanisms to elicit business and service’s quality attributes.

Exploiting software product lines to develop cloud computing applications

With the advance of the Cloud Computing paradigm, new challenges in terms of models, tools, and techniques to support developers to design, build and deploy complex software systems that make full use of the cloud technology arise. In the heterogeneous scenario of this new paradigm, the development of applications using cloud services becomes hard, and the software product lines (SPL) approach is potentially promising for this context since specificities of the cloud platforms, such as services heterogeneity, pricing model, and other aspects can be catered as variabilities to core features. In this perspective, this paper (i) proposes a seamless adaptation of the SPL-based development to include important features of cloud-based applications, and (ii) reports the experience of developing HW-CSPL, a SPL for the Health Watcher (HW) System, which allows citizens to register complaints and consult information regarding the public health system of a city. Several functionalities of this system were implemented using different Cloud Computing platforms, and run time specificities of this application deployed on the cloud were analyzed, as well as other information such as change impact and pricing.

Supporting Dynamic Software Architectures: From Architectural Description to Implementation

Dynamic software architectures are those that describe how components and connectors can be created, interconnected, and/or removed during system execution. Most existing architecture description languages (ADLs) provide a limited support to expressively describe these architectures and entail architectural mismatches and inconsistencies between architecture and implementation due to their decoupling from implementation. In this paper, we introduce the dynamic reconfiguration support provided by π-ADL, a formal, well-founded theoretically language for describing dynamic software architectures under structural and behavioral viewpoints. π-ADL provides architectural-level primitives for specifying programmed dynamic reconfigurations, i.e., Foreseen changes described at design time and triggered at runtime. In addition, π-ADL allows enacting dynamic reconfiguration by means of: (i) an exogenous approach, in which it is possible to control all elements of the software architectures and to apply the changes on the whole structure, and (ii) an endogenous approach, in which the architectural elements can manage dynamic reconfiguration actions. Furthermore, π-ADL is integrated with the Go programming language, thus enabling to automatically generate implementation code from architectural descriptions, thus tackling the existing gap between them. We hereby use a real-world flood monitoring system as an illustrative example of how to describe dynamic software architectures in π-ADL and automatically generate source code in Go.

Towards an IoT ecosystem

In the near future, it will be possible that every object on Earth can be identifiable and addressable. Such objects will be able to be monitored and monitor their physical environments, and of executing actions on such environments in benefit of human users. Moreover, these so-called smart objects will be endowed with wireless communication capabilities. By being uniquely addressed, wireless endowed and through the use of existing protocols and standardized formats, smart things can be integrated in the Internet and accessed as any other Web resource. In this context, the Internet of Things (IoT) emerges as a paradigm in which smart things actively collaborate among them and with other physical and virtual objects available in the Web, providing value-added information and functionalities for users. The IoT paradigm has recently showed its potential of considerably impacting the daily lives of human beings mainly due to the use and interaction of physical devices in several domains, including complex systems composed of other systems. In this paper we discuss the IoT paradigm from the perspective of Systems-of-Systems and present EcoDiF, a IoT platform that integrates heterogeneous devices to provide real-time data control, visualization, processing, and storage. In EcoDiF, devices, information, users and applications are integrated to create an IoT ecosystem in which new ideas and products can be developed in an organic way.

Statistical Model Checking of Dynamic Software Architectures

The critical nature of many complex software-intensive systems calls for formal, rigorous architecture descriptions as means of supporting automated verification and enforcement of architectural properties and constraints. Model checking has been one of the most used techniques to automatically verify software architectures with respect to the satisfaction of architectural properties. However, such a technique leads to an exhaustive exploration of all possible states of the system, a problem that becomes more severe when verifying dynamic software systems due to their typical non-deterministic runtime behavior and unpredictable operation conditions. To tackle these issues, we propose using statistical model checking (SMC) to support the verification of dynamic software architectures while aiming at reducing computational resources and time required for this task. In this paper, we introduce a novel notation to formally express architectural properties as well as an SMC-based toolchain for verifying dynamic software architectures described in \(\pi \)-ADL, a formal architecture description language. We use a flood monitoring system to show how to express relevant properties to be verified. We also report the results of some computational experiments performed to assess the efficiency of our approach.

An Analysis of Reference Architectures for the Internet of Things

The Internet of Things (IoT) is a paradigm in which smart objects actively collaborate with other physical and virtual resources available in the Internet. IoT environments are characterized by a high degree of heterogeneity, encompassing devices with different capabilities, functionalities, and network protocols. To address such a heterogeneity, some platforms have been proposed aiming at abstracting away the specificities of such devices and promoting interoperability among them. Nevertheless, the lack of standardization in IoT makes these platforms to often not properly address several important requirements in this context. In this context, reference architectures can de ne an initial set of building blocks for IoT environments and to provide a solid foundation for leveraging its wide adoption. In this paper, we introduce two recent reference architectures for IoT, namely the IoT Architectural Reference Model and the architecture proposed by WSO2. By analyzing the characteristics of these architectures, we intend to shed light on important issues for future research on reference architectures for IoT.

A Platform for Integrating Physical Devices in the Internet of Things

The Internet of Things (IoT) has emerged as a paradigm in which smart things actively collaborate among them and with other physical and virtual objects available in the Web in order to perform high-level tasks. IoT environments are typically characterized by a high degree of heterogeneity, thus encompassing devices with different capabilities, functionalities, and network protocols. In such a scenario, it is necessary to provide abstractions for physical devices and services to applications and end-users, as well as means to manage the interoperability between such heterogeneous elements. In this context, we introduce EcoDiF (Web Ecosystem of Physical Devices), a Web-based platform for integrating heterogeneous physical devices with applications and users in order to provide services to support real-time data control, visualization, processing, and storage. In this paper, we present the main features of EcoDiF and detail its architecture and implementation, which is based on well-known Web technologies such as HTTP, REST, EEML, and EMML. Furthermore, we present a preliminary evaluation of an EcoDiF prototype through proof-of-concept applications from different domains as well as a performance analysis of the platform.

A Branch-and-Bound Algorithm for Autonomic Adaptation of Multi-cloud Applications

Adaptation is an important concern in cloud-based applications composed of services provided by different cloud providers since cloud services can suffer from Quality of Services(QoS) fluctuations. Other conditions that can also trigger an adaptation process at runtime are the unavailability of services or the violation of user-defined policies. Moreover, the detection and reaction on such changes must be done in an autonomic way, without the need of user intervention. This paper presents a dynamic adaptation approach for multi-cloud applications supported by a Branch-and-Bound (B&B) algorithm in order to optimize the adaptation process itself when selecting the services to be deployed within the application. Computational experiments comparing the B&B algorithm with another algorithm that evaluates all possible configurations for adapting an application showed that the B&B algorithm is faster than the previous version. This new algorithm brings benefits to the scalability of the adaptation process, which can deal with large configurations of multi-cloud applications composed by a plethora of cloud services.