An ontological architecture for principled and automated system of systems composition

2022 9th International Conference on Future Internet of Things and Cloud (FiCloud)

2022

Smart home systems have developed rapidly in recent years, entering many people's daily lives. However, it is difficult for products from different manufacturers to work together due to different hardware, wireless protocols and APIs. These barriers limit the interoperability between IoT devices.We introduce the open-source HolonCraft framework by applying the Holon ontology to smart home systems. We enable different systems to share device descriptions so that devices can recognize each other, understand each other's functions, and work together as needed, composing a system of systems (SoS) at runtime, in order to fulfill the needs of a given user workflow. Further, HolonCraft implements a cross-platform graphical programming editor for smart home automation. HolonCraft automatically transforms device capabilities (in the form of holon descriptions) into visual programming elements, enabling users without programming backgrounds to design smart home automation through simple drag-and-drop operations while also supporting advanced programming features such as branches, loops and even functions and variables. It then type-checks the composed workflow and, accordingly, generates code to actualize the workflow. Consequently, HolonCraft dramatically improves the abstraction and expressiveness of automation. As a result, HolonCraft enhances the efficiency and reliability of automation development while lowering the entry barrier to users.

Section: A Background: What Are Holons?mentioning

confidence: 99%

HolonCraft – An Architecture for Dynamic Construction of Smart Home Workflows

Wang

2022 9th International Conference on Future Internet of Things and Cloud (FiCloud)

2022

“…The definition needs to include all the concepts and properties of a device in order to provide its comprehensive description. For this, we build on our previous work in which we provided an ontological model in the literature that was designed to describe systems [4,12,21]. This holonic ontology is based on the CoDAMOS standard ontology [22], which is flexible and extensible for describing context-aware computing infrastructures.…”

Section: Holon Ontology Automaticmentioning

confidence: 99%

“…The above challenges together highlight that composing systems that make use of a variety of technologies is difficult to design, maintain and adapt. Therefore, system engineering efforts to support post-deployment composition is needed [12,30]. This calls for approaches that address these challenges and are able to (i) identify independent systems with their unique characteristics and contexts; (ii) recognize the need to compose with other systems; (iii) detect the need for mediation logistics; and (iv) set in action any support roles needed to actuate mediation.…”

Section: Introductionmentioning

confidence: 99%

A Middleware for Automatic Composition and Mediation in IoT Systems

Proceedings of the 12th International Conference on the Internet of Things

Bouloukakis

et al. 2022

This paper presents Hetero-Genius, a middleware architecture that enables construction and mediation in Internet of Things (IoT) systems. IoT systems are deployed across physical spaces such as urban parks, residential areas, and highways. The services provided by such IoT deployments are constrained to specific devices and deployment contexts. While existing interoperability solutions enable the "design time" development and deployment of IoT systems, it is often essential to dynamically compose systems that consist of other "small scale" IoT systems. To achieve this, post-deployment composition is needed, i.e., runtime composition of diverse IoT devices and capabilities. Hetero-Genius supports system and service discoverability, as well as automatic composability. We demonstrate this using a real-world Internet of Vehicles (IoV) scenario. Our experimental evaluation shows that developers can save up to 47% of their time when using Hetero-Genius, as well as improve code correctness by 55% on average. CCS CONCEPTS• Networks → Cloud computing; In-network processing; • Computer systems organization → Self-organizing autonomic computing.

“…Other solutions include HTTP, AMQP [3], XMPP [2], among others. Despite these attempts to standardize communication protocols, different IoT vendors still use varying messaging protocols [14,27], which hampers IoT engineers from building more complex systems (e.g., [16,28]). As such, mediation between devices of different vendors is a common approach.…”

Section: The Need For Mediation In Iot Systemsmentioning

confidence: 99%

Energy-Aware Placement of Device-to-Device Mediation Services in IoT Systems

Service-Oriented Computing

2021

Self Cite

Internet-of-Things (IoT) systems are becoming increasingly complex, heterogeneous and pervasive, integrating a variety of physical devices, virtual services, and communication protocols. Such heterogeneity presents an obstacle especially for interactions between devices of different systems that encounter each other at run time. Mediation services have been proposed to facilitate such direct communication by translating between messaging protocols, interfacing different middlewares, etc. However, the decision of where to place a mediation service within an IoT topology has repercussions and is in some cases critical for satisfying system objectives. In this paper, we propose an integer linear programming solution to optimize the placement decision specifically in terms of energy consumption. Our solution takes into account the energy consumed by each interaction at each device along the data transfer paths. Through simulations that use topologies of real-world IoT systems, we show the effect of our approach on energy consumption, messaging delay, and placement decision time. Our algorithm outperforms a state-of-theart solution in terms of reducing energy consumption by almost a third in large-scale typologies. We also demonstrate the feasibility of our approach in terms of overhead.