894 research outputs found

    Middleware Technologies for Cloud of Things - a survey

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    The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

    Middleware Technologies for Cloud of Things - a survey

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    The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

    Analyzing data in the Internet of Things

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    The Internet of Things (IoT) is growing fast. According to the International Data Corporation (IDC), more than 28 billion things will be connected to the Internet by 2020—from smartwatches and other wearables to smart cities, smart homes, and smart cars. This O’Reilly report dives into the IoT industry through a series of illuminating talks and case studies presented at 2015 Strata + Hadoop World Conferences in San Jose, New York, and Singapore. Among the topics in this report, you’ll explore the use of sensors to generate predictions, using data to create predictive maintenance applications, and modeling the smart and connected city of the future with Kafka and Spark. Case studies include: Using Spark Streaming for proactive maintenance and accident prevention in railway equipment Monitoring subway and expressway traffic in Singapore using telco data Managing emergency vehicles through situation awareness of traffic and weather in the smart city pilot in Oulu, Finland Capturing and routing device-based health data to reduce cardiovascular disease Using data analytics to reduce human space flight risk in NASA’s Orion program This report concludes with a discussion of ethics related to algorithms that control things in the IoT. You’ll explore decisions related to IoT data, as well as opportunities to influence the moral implications involved in using the IoT
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