Realizing Emergent Configurations in the Internet of Things

Abstract

The Internet of Things (IoT) is a fast-spreading technology that enables new types of services in several domains such as transportation, health, and building automation. To exploit the potential of the IoT effectively, several challenges have to be tackled, including the following ones that we study in this thesis. First, the proposed IoT visions provide a fragmented picture, leading to a lack of consensus about IoT systems and their constituents. To piece together the fragmented picture of IoT systems, we systematically identified their characteristics by analyzing existing taxonomies. More specifically, we identified seventeen characteristics of IoT systems, and grouped them into two categories, namely, elements and quality aspects of IoT systems. Moreover, we conducted a survey to identify the factors that drive the deployment decisions of IoT systems in practice. A second set of challenges concerns the environment of IoT systems that is often dynamic and uncertain. For instance, due to the mobility of users and things, the set of things available in users' environment might change suddenly. Similarly, the status of IoT systems’ deployment topologies (i.e., the deployment nodes and their interconnections) might change abruptly. Moreover, environmental conditions monitored and controlled through IoT devices, such as ambient temperature and oxygen levels, might fluctuate suddenly. The majority of existing approaches to engineer IoT systems rely on predefined processes to achieve users’ goals. Consequently, such systems have significant shortcomings in coping with dynamic and uncertain environments. To address these challenges, we used the concept of Emergent Configurations (ECs) to engineer goal-driven IoT systems. An EC is an IoT system that consists of a dynamic set of things that cooperate temporarily to achieve a user goal. To realize ECs, we proposed an abstract architectural approach, comprising an architecture and processes, as well as six novel approaches that refine the abstract approach. The developed approaches support users to achieve their goals seamlessly in arbitrary environments by enabling the dynamic formation, deployment, enactment, and self-adaptation of IoT systems. The approaches exploit different techniques and focus on different aspects of ECs. Moreover, to better support users in dynamic and uncertain environments, we investigated the automated configuration of those environments based on users' preferences.

ASSERT: A Blockchain-Based Architectural Approach for Engineering Secure Self-Adaptive IoT Systems

“…C1: Most approaches proposed to engineer self-adaptive and goal-driven IoT systems that operate in dynamic and uncertain environments do not consider security as a primary concern [17].…”

“…Architectural Concerns. Several studies have presented functional requirements that goal-driven and self-adaptive IoT systems should meet [9,17]. Moreover, they have developed several approaches to allow goal-driven and self-adaptive systems to meet those requirements.…”

“…Several approaches have been proposed to engineer goal-driven and self-adaptive IoT systems by exploiting different techniques and notions, including multi-agent systems [7,8], the web of things [9,10], feedback loops [6,8], service-oriented architectures [11,12], a microservices architecture [13], AI planning [6,14], model-driven engineering [15], and business processes [16]. However, the majority of the existing approaches focus mostly on the functional requirements and do not consider security as a main concern [17]. Moreover, most of the existing approaches developed to engineer secure self-adaptive systems adopt centralized architectures and thus are not suitable for the distributed and dynamic IoT environments [18].…”

“…Indeed, there has been an increasing interest in leveraging agents' technology to develop IoT systems [33]. However, further efforts are required to engineer self-adaptive MAS in a goal-directed manner [17,34].…”

“…Existing approaches developed to realize goal-driven MAS exploit other technologies and notions, including rule-based programming [36], ensembles [37,38], and interactionoriented programming [39,40]. To summarize, exploiting agents' technology to develop goal-driven and self-adaptive IoT systems that can operate in dynamic and uncertain environments contributes to a promising unexplored research direction in both the IoT and MAS [17,33,41].…”