Towards an IoT ecosystem

Delicato, Flávia C.; Pires, Paulo F.; Batista, Thaís; Cavalcante, Everton; Costa, Bruno; Barros, Thomaz

doi:10.1145/2489850.2489855

Cited by 55 publications

(26 citation statements)

References 8 publications

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“…The IoT has been described as a System of Systems (SoS) or ecosystem [141], which may be defined as:…”

Section: Industry Investment In Iot-an Application Of the Multimethodmentioning

confidence: 99%

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Research Challenges for the Internet of Things: What Role Can OR Play?

Ryan

Watson²

2017

Systems

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Abstract:The Internet of Things (IoT) is an extension of the Internet in which large numbers of "things", including sensors, actuators and processors, in addition to human users, are networked and able to provide high resolution data on their environment and exercise a degree of control over it. It is still at an early stage of development, and many problems/research challenges must be solved before it is widely adopted. Many of these are technical, including interoperability and scalability, as billions of heterogeneous devices will be connected, but deciding on how to invest in the IoT is a challenge for business, and there are also major social, legal and ethical challenges, including security and privacy of data collection, which must be resolved. As the future IoT will be a multi-national, multi-industry, multi-technology infrastructure, the paper reviews the global standardization efforts that are underway to facilitate its worldwide creation and adoption. The main purpose of the paper is to give a broad survey, based on published literature, of the methods of Operations Research (OR), both the mathematical tools and techniques of "hard" OR, and the various approaches of Systems Thinking, including "soft" OR, which may assist in dealing with these problems. A subset of these is described in greater depth to better convey what might be involved in applying OR and Systems Thinking to the IoT. It is suggested that OR has a role to play in balancing the technical and non-technical research challenges which confront the IoT.

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“…The IoT has been described as a System of Systems (SoS) or ecosystem [141], which may be defined as:…”

Section: Industry Investment In Iot-an Application Of the Multimethodmentioning

confidence: 99%

“…Research into the Multimethodology approach has been scarce [140] and the OR/Systems Thinking community must address the need for better education and research in this approach in the future. The IoT has been described as a System of Systems (SoS) or ecosystem [141], which may be defined as:…”

Section: Industry Investment In Iot-an Application Of the Multimethodmentioning

confidence: 99%

Research Challenges for the Internet of Things: What Role Can OR Play?

Ryan

Watson²

2017

Systems

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“…The rise of cheap sensors, new wireless communication technologies, sensor and actuator networks, and cloud computing has resulted in the application of these technologies to several vertical markets, creating heterogeneity [17]. Therefore, as emphasized by Delicato [18], the need emerges for IoT solutions to scale with millions of devices, as well as for the ability to deal with software and hardware heterogeneity, uncertainty detection and conflict resolution. In a similar manner, Biswas et al [19] claims that in order to realize IoT vision targeting future markets, several requirements have to be taken into account, including ubiquitous accessibility and connectivity, as well as commonly agreed APIs and standards.…”

Section: Related Workmentioning

confidence: 99%

Network Analysis of Platform Ecosystems: The Case of Internet of Things Ecosystem

Toivanen

Mazhelis

Luoma

2015

Lecture Notes in Business Information Processing

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Abstract. Software platform providers are often seen as the cornerstone of their business ecosystem, where the other ecosystem players utilize the platform's standardized components together with complementary components for making applications. These platforms are also becoming a cornerstone of the emerging Internet of Things (IoT) business ecosystem comprised of the companies who provide Internet-enabled devices, applications, connectivity solutions, and the platforms for the IoT usage. While a number of enabling technologies for IoT is available, the question remains what kind of ecosystem emerges around IoT platform providers and whether this ecosystem is evolving in line with the theoretical models describing business ecosystem development. In order to address this question, we constructed a network model for the IoT ecosystem and considered how it had changed over the period of a year and a half. Our findings indicate that the ecosystem is still in early evolutionary phase, although some signs of consolidation are starting to appear. A mainstream solution is still missing and many vendors are trying to make their platform a dominating one.

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“…In general, these data collectors are logically tied and strongly coupled to the middleware architecture, as in, for example, EcoDif [6], Xively [7], OpenIoT [8], RestThing [9], WSO2 [10] and Kaa [11]. In a common structure for an IoT system instance, one or more of these middleware will manage IoT devices that must send data to an Internet application server, this being the application server and the managed devices owned by the same organization.…”

Section: Introductionmentioning

confidence: 99%

Distributed Data Service for Data Management in Internet of Things Middleware

Huacarpuma

Sousa

Holanda

et al. 2017

Sensors

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The development of the Internet of Things (IoT) is closely related to a considerable increase in the number and variety of devices connected to the Internet. Sensors have become a regular component of our environment, as well as smart phones and other devices that continuously collect data about our lives even without our intervention. With such connected devices, a broad range of applications has been developed and deployed, including those dealing with massive volumes of data. In this paper, we introduce a Distributed Data Service (DDS) to collect and process data for IoT environments. One central goal of this DDS is to enable multiple and distinct IoT middleware systems to share common data services from a loosely-coupled provider. In this context, we propose a new specification of functionalities for a DDS and the conception of the corresponding techniques for collecting, filtering and storing data conveniently and efficiently in this environment. Another contribution is a data aggregation component that is proposed to support efficient real-time data querying. To validate its data collecting and querying functionalities and performance, the proposed DDS is evaluated in two case studies regarding a simulated smart home system, the first case devoted to evaluating data collection and aggregation when the DDS is interacting with the UIoT middleware, and the second aimed at comparing the DDS data collection with this same functionality implemented within the Kaa middleware.

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Towards an IoT ecosystem

Cited by 55 publications

References 8 publications

Research Challenges for the Internet of Things: What Role Can OR Play?

Research Challenges for the Internet of Things: What Role Can OR Play?

Network Analysis of Platform Ecosystems: The Case of Internet of Things Ecosystem

Distributed Data Service for Data Management in Internet of Things Middleware

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