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Register a new userDesigning Sensing as a Service (S2aaS) Ecosystem for Internet of Things
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Added by
Charith Perera
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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The Internet of Things (IoT) envisions the creation of an environment where everyday objects (e.g. microwaves, fridges, cars, coffee machines, etc.) are connected to the internet and make users lives more productive, efficient, and convenient. During this process, everyday objects capture a vast amount of data that can be used to understand individuals and their behaviours. In the current IoT ecosystems, such data is collected and used only by the respective IoT solutions. There is no formal way to share data with external entities. We believe this is very efficient and unfair for users. We believe that users, as data owners, should be able to control, manage, and share data about them in any way that they choose and make or gain value out of them. To achieve this, we proposed the Sensing as a Service (S2aaS) model. In this paper, we discuss the Sensing as a Service ecosystem in terms of its architecture, components and related user interaction designs. This paper aims to highlight the weaknesses of the current IoT ecosystem and to explain how S2aaS would eliminate those weaknesses. We also discuss how an everyday user may engage with the S2aaS ecosystem and design challenges.
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We propose a roadmap for leveraging the tremendous opportunities the Internet of Things (IoT) has to offer. We argue that the combination of the recent advances in service computing and IoT technology provide a unique framework for innovations not yet envisaged, as well as the emergence of yet-to-be-developed IoT applications. This roadmap covers: emerging novel IoT services, articulation of major research directions, and suggestion of a roadmap to guide the IoT and service computing community to address key IoT service challenges.
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User privacy concerns are widely regarded as a key obstacle to the success of modern smart cyber-physical systems. In this paper, we analyse, through an example, some of the requirements that future data collection architectures of these systems should implement to provide effective privacy protection for users. Then, we give an example of how these requirements can be implemented in a smart home scenario. Our example architecture allows the user to balance the privacy risks with the potential benefits and take a practical decision determining the extent of the sharing. Based on this example architecture, we identify a number of challenges that must be addressed by future data processing systems in order to achieve effective privacy management for smart cyber-physical systems.
In mobile Internet ecosystem, Mobile Users (MUs) purchase wireless data services from Internet Service Provider (ISP) to access to Internet and acquire the interested content services (e.g., online game) from Content Provider (CP). The popularity of intelligent functions (e.g., AI and 3D modeling) increases the computation-intensity of the content services, leading to a growing computation pressure for the MUs resource-limited devices. To this end, edge computing service is emerging as a promising approach to alleviate the MUs computation pressure while keeping their quality-of-service, via offloading some computation tasks of MUs to edge (computing) servers deployed at the local network edge. Thus, Edge Service Provider (ESP), who deploys the edge servers and offers the edge computing service, becomes an upcoming new stakeholder in the ecosystem. In this work, we study the economic interactions of MUs, ISP, CP, and ESP in the new ecosystem with edge computing service, where MUs can acquire the computation-intensive content services (offered by CP) and offload some computation tasks, together with the necessary raw input data, to edge servers (deployed by ESP) through ISP. We first study the MUs Joint Content Acquisition and Task Offloading (J-CATO) problem, which aims to maximize his long-term payoff. We derive the off-line solution with crucial insights, based on which we design an online strategy with provable performance. Then, we study the ESPs edge service monetization problem. We propose a pricing policy that can achieve a constant fraction of the ex-post optimal revenue with an extra constant loss for the ESP. Numerical results show that the edge computing service can stimulate the MUs content acquisition and improve the payoffs of MUs, ISP, and CP.
The Internet of Things combines various earlier areas of research. As a result, research on the subject is still organized around these pre-existing areas: distributed computing with services and objects, networks (usually combining 6lowpan with Zigbee etc. for the last-hop), artificial intelligence and semantic web, and human-computer interaction. We are yet to create a unified model that covers all these perspectives - domain, device, service, agent, etc. In this paper, we propose the concept of cells as units of structure and context in the Internet of things. This allows us to have a unified vocabulary to refer to single entities (whether dumb motes, intelligent spimes, or virtual services), intranets of things, and finally the complete Internet of things. The question that naturally follows, is what criteria we choose to demarcate boundaries; we suggest various possible answers to this question. We also mention how this concept ties into the existing visions and protocols, and suggest how it may be used as the foundation of a formal model.
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