The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things.

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Internet of things: Vision, applications and research challenges

Software systems dealing with distributed applications in changing environments normally require human supervision to continue operation in all conditions. These (re-)configuring, troubleshooting, and in general maintenance tasks lead to costly and time-consuming procedures during the operating phase. These problems are primarily due to the open-loop structure often followed in software development. Therefore, there is a high demand for management complexity reduction, management automation, robustness, and achieving all of the desired quality requirements within a reasonable cost and time range during operation. Self-adaptive software is a response to these demands; it is a closed-loop system with a feedback loop aiming to adjust itself to changes during its operation. These changes may stem from the software system's self (internal causes, e.g., failure) or context (external events, e.g., increasing requests from users). Such a system is required to monitor itself and its context, detect significant changes, decide how to react, and act to execute such decisions. These processes depend on adaptation properties (called self-a properties), domain characteristics (context information or models), and preferences of stakeholders. Noting these requirements, it is widely believed that new models and frameworks are needed to design self-adaptive software. This survey article presents a taxonomy, based on concerns of adaptation, that is, how, what, when and where, towards providing a unified view of this emerging area. Moreover, as adaptive systems are encountered in many disciplines, it is imperative to learn from the theories and models developed in these other areas. This survey article presents a landscape of research in self-adaptive software by highlighting relevant disciplines and some prominent research projects. This landscape helps to identify the underlying research gaps and elaborates on the corresponding challenges.

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Self-adaptive software: Landscape and research challenges

Smartphones have exploded in popularity in recent years, becoming ever more sophisticated and capable. As a result, developers worldwide are building increasingly complex applications that require ever increasing amounts of computational power and energy. In this paper we propose ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud. ThinkAir exploits the concept of smartphone virtualization in the cloud and provides method-level computation offloading. Advancing on previous work, it focuses on the elasticity and scalability of the cloud and enhances the power of mobile cloud computing by parallelizing method execution using multiple virtual machine (VM) images. We implement ThinkAir and evaluate it with a range of benchmarks starting from simple micro-benchmarks to more complex applications. First, we show that the execution time and energy consumption decrease two orders of magnitude for a N-queens puzzle application and one order of magnitude for a face detection and a virus scan application. We then show that a parallelizable application can invoke multiple VMs to execute in the cloud in a seamless and on-demand manner such as to achieve greater reduction on execution time and energy consumption. We finally use a memory-hungry image combiner tool to demonstrate that applications can dynamically request VMs with more computational power in order to meet their computational requirements.

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ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading

The paper discusses the Gaia metaoperating system which extends the reach of traditional operating systems to manage ubiquitous computing habitats and living spaces as integrated programmable environments. Gaia exports services to query, access, and use existing resources and context, and provides a framework to develop user-centric, resource-aware, multidevice, context-sensitive, and mobile applications.

A middleware infrastructure for active spaces

Software-based systems today are increasingly expected to dynamically self-adapt to accommodate resource variability, changing user needs, and system faults. Recent work uses closed-loop control based on external models to monitor and adapt system behavior at run time. Taking this externalized approach, the Rainbow framework we have developed uses software architectural models to dynamically monitor and adapt a running system. A key goal and primary challenge of this framework is to support the reuse of adaptation strategies and infrastructure across different systems. We show that the separation of a generic adaptation infrastructure from system-specific adaptation knowledge makes this reuse possible.

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Rainbow: architecture-based self-adaptation with reusable infrastructure

This paper discusses the automated application of architectural patterns for tuning the quality of service of service-oriented software. The paper first presents an overview of prior work in self-architecting, SASSY, and a motivating example in the emergency response domain. After summarizing the heuristic used for self-architecting, the paper discusses a number of architectural patterns and the corresponding quantitative models for two concrete aspects of quality of service: availability and response time. A case study illustrates the role of patterns in the application of the self-architecting heuristic to the motivating example.

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Qos architectural patterns for self-architecting software systems

Recently there has been increasing interest in developing systems that can adapt dynamically to cope with changing environmental conditions and unexpected system errors. Most efforts for achieving self-adaptation have focused on the mechanisms for detecting opportunities for improvement and then taking appropriate action. However, such mechanisms beg the question: what is the system trying to achieve? In a given situation there may be many possible adaptations, and knowing which one to pick is a difficult question. In this paper we advocate the use of explicit representation of user task as a critical element in addressing this missing link.

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Task-based self-adaptation

The proliferation of smart spaces and emergence of new standards, such as Web Services, have paved the way for a new breed of software systems. Often the complete functional and QoS requirements of such software systems are not known a priori at design-time, and even if they are, they may change at run-time. Unfortunately, the majority of existing software engineering techniques rely heavily on human reasoning and manual intervention, making them inapplicable for automatic composition of such software systems at run-time. Moreover, these approaches are primarily intended to be used by technically knowledgeable software engineers, as opposed to domain users. In this paper, we present Service Activity Schemas (SAS) , an activity-oriented language for modeling software system's functional and QoS requirements. SAS targets service-oriented software systems, and relies on an ontology to provide domain experts with modeling constructs that are intuitively understood. SAS forms the centerpiece of a framework intended for user-driven composition and adaptation of service-oriented software systems in a pervasive setting. We provide a detailed description of SAS in the context of a case study and formally specify its structural and dynamic properties.

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A Modeling Language for Activity-Oriented Composition of Service-Oriented Software Systems

An emerging trend in the engineering of complex systems is the use of component integration frameworks. Such a framework prescribes an architectural design that permits flexible composition of thirdparty components into applications. A good example is Sun Microsystems' Enterprise JavaBeans™ (EJB) framework, which supports object-oriented, distributed, enterprise-level applications, such as account management systems. One problem with frameworks like EJB is that they are documented informally, making it difficult to understand precisely what is provided by the framework, and what is required to use it. We believe formal specification can help, and in this paper show how a formal architectural description language can be used to describe and provide insight into such frameworks.

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Formal Modeling of the Enterprise JavaBeansTM Component Integration Framework

This paper presents a framework for engineering resource-adaptive software systems targeted at small mobile devices. The proposed framework empowers users to control tradeoffs among a rich set of service- specific aspects of quality of service. After motivating the problem, the paper proposes a model for capturing user preferences with respect to quality of service, and illustrates prototype user interfaces to elicit such models. The paper then describes the extensions and integration work made to accommodate the proposed framework on top of an existing software infrastructure for ubiquitous computing. The research question addressed here is the feasibility of coordinating resource allocation and adaptation policies in a way that end-users can understand and control in real time. The evaluation covered both systems and the usability perspectives, the latter by means of a user study. The contributions of this work are: first, a set of design guidelines for resource-adaptive systems, including APIs for integrating new applications; second, a concrete infrastructure that implements the guidelines. And third, a way to model quality of service tradeoffs based on utility theory, which our research indicates end-users with diverse backgrounds are able to leverage for guiding the adaptive behaviors towards activity-specific quality goals.

https://apollo.smu.edu.sg/papers/C2_247_Sousa.pdf

João Pedro Sousa

Papers

Qos architectural patterns for self-architecting software systems

Task-based self-adaptation

A Modeling Language for Activity-Oriented Composition of Service-Oriented Software Systems

Formal Modeling of the Enterprise JavaBeansTM Component Integration Framework

User guidance of resource-adaptive systems