6,077 research outputs found
Middleware Technologies for Cloud of Things - a survey
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
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
Semantic Gateway as a Service architecture for IoT Interoperability
The Internet of Things (IoT) is set to occupy a substantial component of
future Internet. The IoT connects sensors and devices that record physical
observations to applications and services of the Internet. As a successor to
technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has
stumbled into vertical silos of proprietary systems, providing little or no
interoperability with similar systems. As the IoT represents future state of
the Internet, an intelligent and scalable architecture is required to provide
connectivity between these silos, enabling discovery of physical sensors and
interpretation of messages between things. This paper proposes a gateway and
Semantic Web enabled IoT architecture to provide interoperability between
systems using established communication and data standards. The Semantic
Gateway as Service (SGS) allows translation between messaging protocols such as
XMPP, CoAP and MQTT via a multi-protocol proxy architecture. Utilization of
broadly accepted specifications such as W3C's Semantic Sensor Network (SSN)
ontology for semantic annotations of sensor data provide semantic
interoperability between messages and support semantic reasoning to obtain
higher-level actionable knowledge from low-level sensor data.Comment: 16 page
Katakan tidak pada rasuah
Isu atau masalah rasuah menjadi topik utama sama ada di peringkat antarabangsa mahupun di peringkat dalam negara. Pertubuhan Bangsa- bangsa Bersatu menegaskan komitmen komuniti antarabangsa bertegas untuk mencegah dan mengawal rasuah melalui buku bertajuk United Nations Convention against Corruption. Hal yang sama berlaku di Malaysia. Melalui pernyataan visi oleh mantan Perdana Menteri Malaysia, Tun Dr. Mahathir bin Mohamed memberikan indikasi bahawa kerajaan Malaysia komited untuk mencapai aspirasi agar Malaysia dikenali kerana integriti dan bukannya rasuah. Justeru, tujuan penulisan bab ini adalah untuk membincangkan rasuah dari beberapa sudut termasuk perbincangan dari sudut agama Islam, faktor-faktor berlakunya gejala rasuah, dan usaha-usaha yang dijalankan di Malaysia untuk membanteras gejala rasuah. Perkara ini penting bagi mengenalpasti penjawat awam menanamkan keyakinan dalam melaksanakan tanggungjawab dengan menghindari diri daripada rasuah agar mereka sentiasa peka mengutamakan kepentingan awam
In-Network Distributed Solar Current Prediction
Long-term sensor network deployments demand careful power management. While
managing power requires understanding the amount of energy harvestable from the
local environment, current solar prediction methods rely only on recent local
history, which makes them susceptible to high variability. In this paper, we
present a model and algorithms for distributed solar current prediction, based
on multiple linear regression to predict future solar current based on local,
in-situ climatic and solar measurements. These algorithms leverage spatial
information from neighbors and adapt to the changing local conditions not
captured by global climatic information. We implement these algorithms on our
Fleck platform and run a 7-week-long experiment validating our work. In
analyzing our results from this experiment, we determined that computing our
model requires an increased energy expenditure of 4.5mJ over simpler models (on
the order of 10^{-7}% of the harvested energy) to gain a prediction improvement
of 39.7%.Comment: 28 pages, accepted at TOSN and awaiting publicatio
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