Heterogeneous Internet Of Things Platforms Research Articles

Transparent and Tamper-Proof Event Ordering in the Internet of Things Platforms

Today, the audit and diagnosis of the causal relationships between the events in a trigger-action-based event chain (e.g., why is a light turned on in a smart home?) in the Internet of Things (IoT) platforms are untrustworthy and unreliable. The current IoT platforms lack techniques for transparent and tamper-proof ordering of events due to their device-centric logging mechanism. In this article, we develop a framework that facilitates tamper-proof transparency and event order in an IoT platform by proposing a Blockchain protocol and adopting the vector clock system, both tailored for the resource-constrained heterogeneous IoT devices, respectively. To cope with the unsuited storage (e.g., ledger) and computing power (e.g., proof-of-work puzzle) requirements of the Blockchain in the commercial off-the-shelf IoT devices, we propose a partial consistent cut protocol and engineer a modular arithmetic-based lightweight proof of work puzzle, respectively. To the best of our knowledge, this is the first Blockchain designed for resource-constrained heterogeneous IoT platforms. Our event ordering protocol based on the vector clock system is also novel for the IoT platforms. We implement our framework using an IoT gateway and 30 IoT devices. We experiment with ten concurrent trigger-action-based event chains while each chain involves 20 devices, and each device participates in five different chains. The results show that our framework may order these events in 2.5 s while consuming approximately 140 mJ of energy per device. The results, hence, demonstrate the proposed platform as a practical choice for many IoT applications, such as smart home, traffic monitoring, and crime investigation.

Resource identifier interoperability among heterogeneous IoT platforms

Many standards, projects, and platforms are being developed as the Internet of Things (IoT) is adopted in a wide range of fields. However, because each IoT platform is based on a different resource identifier (ID), it is difficult to identify each device and use the service among heterogeneous IoT platforms. To solve this problem, we propose an interoperability framework that includes an IoT resource name system (RNS) based on analysis of the resource IDs (i.e., device ID and resource request formats) of five selected IoT platforms: oneM2M, Oliot, Watson IoT, IoTivity, and FIWARE. The IoT RNS converts a specific resource path into a resource request format for each platform. The converted resource path is shared among IoT RNSs for each platform, and users can request services from other platforms using converted resource paths. We also present an example of interoperability scenario among heterogeneous IoT platforms using the proposed IoT RNS in a smart city. The scenario includes each stage, such as resource registration and deletion, sharing mapping tables, converting resource addresses, and service requests. Furthermore, to prove the aims of the proposed approach, we implemented the resource interoperability scenario between oneM2M and FIWARE. In the experiments, resources can interwork in the two platforms through resource path conversion. Based on the results, we performed a qualitative evaluation of the IoT RNS with the current studies. In conclusion, our proposal overcomes the issues of building an existing integrated platform or specific central ontology and duplicating resources inside the platform. In addition, we separate the functions of the root and local IoT RNSs to solve communication traffic and memory capability issues.

IoT Platforms and Security: An Analysis of the Leading Industrial/Commercial Solutions.

For simplifying and speeding up the development of the Internet of Things (IoT) ecosystem, there has been a proliferation of IoT platforms, built up according to different design principles, computing paradigms, technologies, and targets. This paper proposes a review of main examples populating the wide landscape of IoT platforms and their comparison based on the IoT-A reference architecture. In such a way, heterogeneous IoT platforms (both current and future) can be analyzed regardless of their low-level specifications but exclusively through the lens of those key functionalities and architectural building blocks that enable the interplay among devices, data flow, software, and stakeholders within the IoT ecosystem. Among these, security by design (i.e., the inclusion of security design principles, technology, and governance at every level) must be integrated into every tier, component, and application to minimize the risk of cyber threats and preserve the integrity of the IoT platforms, not only within individual components but also for all the components working together as a whole.

Designing Automated Deployment Strategies of Face Recognition Solutions in Heterogeneous IoT Platforms

In this paper, we tackle the problem of deploying face recognition (FR) solutions in heterogeneous Internet of Things (IoT) platforms. The main challenges are the optimal deployment of deep neural networks (DNNs) in the high variety of IoT devices (e.g., robots, tablets, smartphones, etc.), the secure management of biometric data while respecting the users’ privacy, and the design of appropriate user interaction with facial verification mechanisms for all kinds of users. We analyze different approaches to solving all these challenges and propose a knowledge-driven methodology for the automated deployment of DNN-based FR solutions in IoT devices, with the secure management of biometric data, and real-time feedback for improved interaction. We provide some practical examples and experimental results with state-of-the-art DNNs for FR in Intel’s and NVIDIA’s hardware platforms as IoT devices.

Data Spine: A Federated Interoperability Enabler for Heterogeneous IoT Platform Ecosystems.

Today, the Internet of Things (IoT) is pervasive and characterized by the rapid growth of IoT platforms across different application domains, enabling a variety of business models and revenue streams. This opens new opportunities for companies to extend their collaborative networks and develop innovative cross-platform and cross-domain applications. However, the heterogeneity of today’s platforms is a major roadblock for mass creation of IoT platform ecosystems, pointing at the current absence of technology enablers for an easy and innovative composition of tools/services from the existing platforms. In this paper, we present the Data Spine, a federated platform enabler that bridges IoT interoperability gaps and enables the creation of an ecosystem of heterogeneous IoT platforms in the manufacturing domain. The Data Spine allows the ecosystem to be extensible to meet the need for incorporating new tools/services and platforms. We present a reference implementation of the Data Spine and a quantitative evaluation to demonstrate adequate performance of the system. The evaluation suggests that the Data Spine provides a multitude of advantages (single sign-on, provision of a low-code development environment to support interoperability and an easy and intuitive creation of cross-platform applications, etc.) over the traditional approach of users joining multiple platforms separately.

An Interoperable Access Control Framework for Diverse IoT Platforms Based on OAuth and Role.

Due to the rapid development of Internet of Things (IoT), IoT platforms that can provide common functions for things are becoming increasingly important. However, access control frameworks in diverse IoT platforms have been developed for individual security goals, designs, and technologies. In particular, current OAuth-based access control frameworks that are widely used in IoT research have not been providing interoperability among IoT platforms even though sharing resources and services is a critical issue for IoT platforms. Therefore, we analyze the main requirements for an IoT access control framework to properly design our framework and propose an interoperable access control framework based on OAuth 2.0 and Role. Our approach describes a new extended authorization grant flow to issue an Interoperable Access Token (IAT) that has a global access scope across IoT platforms using multiple pairs of clients’ credentials. With the IAT and proposed framework, we can access client-specific domains in heterogeneous IoT platforms, then valuable resources (e.g., data and services) in the domains can be accessed by validating the roles, which will greatly simplify permission management. Furthermore, IAT supports a simple token management (e.g., token issuance, refreshing, and revocation) by managing only one token for diverse IoT platforms. In addition, we implement our interoperable access control framework on Mobius and FIWARE, which are promising open-source IoT platforms, and test an interoperability scenario to demonstrate our approach with the implementation. Furthermore, the proposed framework is compared with other IoT access control approaches based on the selected requirements in this paper.

Device Identification Interoperability in Heterogeneous IoT Platforms.

With the continuous improvement of Internet of Things (IoT) technologies, various IoT platforms are under development. However, each IoT platform is developed based on its own device identification system. That is, it is challenging to identify each sensor device between heterogeneous IoT platforms owing to the resource request format (e.g., device identifier) varying between platforms. Moreover, despite the considerable research focusing on resource interoperability between heterogeneous IoT platforms, little attention is given to sensor device identification systems in diverse IoT platforms. In order to overcome this problem, the current work proposes an IoT device name system (DNS) architecture based on the comparative analysis of heterogeneous IoT platforms (i.e., oneM2M, GS1 ‘Oliot’, IBM ‘Watson IoT’, OCF ‘IoTivity’, FIWARE). The proposed IoT DNS analyzes and translates the identification system of the device and resource request format. In this process, resource requests between heterogeneous IoT platforms can be reconfigured appropriately for the resources and services requested by the user, and as a result, users can use heterogeneous IoT services. Furthermore, in order to illustrate the aim of the proposed architecture, the proposed IoT DNS is implemented and tested on a microcomputer. The experimental results show that a oneM2M-based device successfully performs a resource request to a Watson IoT and FIWARE sensor devices.

Breaking Vendors and City Locks through a Semantic-enabled Global Interoperable Internet-of-Things System: A Smart Parking Case.

The Internet of Things (IoT) is unanimously identified as one of the main technology enablers for the development of future intelligent environments. However, the current IoT landscape is suffering from large fragmentation with many platforms and vendors competing with their own solution. This fragmented scenario is now jeopardizing the uptake of the IoT, as investments are not carried out partly because of the fear of being captured in lock-in situations. To overcome these fears, interoperability solutions are being put forward in order to guarantee that the deployed IoT infrastructure, independently of its manufacturer and/or platform, can exchange information, data and knowledge in a meaningful way. This paper presents a Global IoT Services (GIoTS) use case demonstrating how semantic interoperability among five different smart city IoT deployments can be leveraged to develop a smart urban mobility service. The application that has been developed seamlessly consumes data from them for providing parking guidance and mobility suggestions at the five locations (Santander and Barcelona in Spain and Busan, Seoul and Seongnam in South Korea) where the abovementioned IoT deployments are installed. The paper is also presenting the key aspects of the system enabling the interoperability among the three underlying heterogeneous IoT platforms.

IoT-Lite: a lightweight semantic model for the internet of things and its use with dynamic semantics

Over the past few years, the semantics community has developed several ontologies to describe concepts and relationships for internet of things (IoT) applications. A key problem is that most of the IoT-related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time, and therefore, they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis and assess IoT-Lite against another solution in terms of round trip time performance for query-response times. We have linked IoT-Lite with stream annotation ontology, to allow queries over stream data annotations, and we have also added dynamic semantics in the form of MathML annotations to IoT-Lite. Dynamic semantics allows the annotation of spatio-temporal values, reducing storage requirements and therefore the response time for queries. Dynamic semantics stores mathematical formulas to recover estimated values when actual values are missing.

Semantic interoperability in the Internet of Things: An overview from the INTER-IoT perspective

The Internet of Things (IoT) idea, explored across the globe, brings about an important issue: how to achieve interoperability among multiple existing (and constantly created) IoT platforms. In this context, in January 2016, the European Commission has funded seven projects that are to deal with various aspects of interoperability in the Internet of Things. Among them, the INTER-IoT project is aiming at the design and implementation of, and experimentation with, an open cross-layer framework and associated methodology to provide voluntary interoperability among heterogeneous IoT platforms. While the project considers interoperability across all layers of the software stack, we are particularly interested in answering the question: how ontologies and semantic data processing can be harnessed to facilitate interoperability across the IoT landscape. Henceforth, we have engaged in a “fact finding mission” to establish what is currently at our disposal when semantic interoperability is concerned. Since the INTER-IoT project is initially driven by two use cases originating from (i) (e/m)Health and (ii) transportation and logistics, these two application domains were used to provide context for our search. The paper summarizes our findings and provides foundation for developing methods and tools for supporting semantic interoperability in the INTER-IoT project (and beyond).