The past decade has seen a rise in complexity and scale of software systems, particularly with the emerging of the Internet of Thing consisting of large scale and heterogeneous entities which results in difficulties in providing trustworthy services. To overcome such challenges, providing high quality information for IoT service provider as well as monitoring trust relationship of end-users toward the services are paramount. Such trust relationships are user-oriented and subjective phenomenon that hook on specific quality of data. Following this catalyst, we propose a mechanism to evaluate quality of information (QoI) for streaming data from sensor device; then use the QoI evaluation score as an indicator of trust. Concepts and assessment methodology for QoI along with a trust monitoring system are described. We also develop a framework that classifies streaming of data based on semantic context and generate QoI score as a relevant input for a trust monitoring component. This framework enables a dynamic trust management in the context of IoT for both end-users and services that empowers service providers to deliver trustworthy and high quality IoT services. Challenges encountered during implementation and contribution in standardization are discussed. We believe this paper offers better understanding on QoI and its importance in trust evaluation in IoT applications; also provides detailed implementation of the QoI and Trust components for real-world applications and services.
The first-generation of the Internet-of-Things (IoT) was developed and deployed all over the world by connecting devices with common functionalities that were not sufficiently efficient or reliable for use in dynamic situations that require adaptive solutions. However, these fundamental IoT functions and services mainly targeted stable environments; there is consequently a strong need for the next generation of IoT services to be smarter, faster, and more reliable. We believe that the hyper-connected IoT ecosystem on Fog platforms with contextual AI technologies is a promising solution. In this work, we introduce the Elastic-IoT-Fog (EiF), a flexible Fog computing framework that runs on IoT gateways with adaptive AI services fostered on the Cloud. Our approach can be viewed as an integration of three emerging technologies, namely IoT, Fog, and AI. Generally, EiF virtualizes an IoT service layer platform for fog nodes and provides functions to manage and orchestrate various fog nodes; upon service virtualization and orchestration, AI services are fostered within both the federated Cloud and distributed edge side and are deployed on fog nodes. We demonstrate the feasibility of EiF via the example of intelligent traffic flow monitoring and management.
The emerging Blockchain (BC) and Distributed Ledger technologies have come to impact a variety of domains, from capital market sectors to digital asset management in the Internet of Things (IoT). As a result, more and more BC-based decentralized applications for numerous cross-domain services have been developed. These applications implement specialized decentralized computer programs called Smart Contracts (SCs) which are deployed into BC frameworks. Although these SCs are open ato public, it is challenging to discover and utilize such SCs for a wide range of usages from both systems and end-users because such SCs are already compiled in form of byte-codes without any associated meta-data. This motivates us to propose a solution called Semantic SC (SSC) which integrates RESTful semantic web technologies in SCs, deployed on the Ethereum Blockchain platform, for indexing, browsing and annotating such SCs. The solution also exposes the relevant distributed ledgers as Linked Data for enhancing the discovery capability. To achieve this goal, the OWLS service ontology is extended by incorporating some domain specific terminologies, which are used in the development of the proposed SSCs. As a result, SSC can be utilized to enrich queries for a domain-specific terms across multiple distributed ledgers, which greatly increases the discovery capability of decentralized IoT applications and services. Contribution in standardization is also discussed. We believe that our research work takes the first steps towards connecting BC-based decentralized services with semantic web services in order to provide better IoT ecosystems.
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