641 research outputs found
Semantic-driven Configuration of Internet of Things Middleware
We are currently observing emerging solutions to enable the Internet of
Things (IoT). Efficient and feature rich IoT middeware platforms are key
enablers for IoT. However, due to complexity, most of these middleware
platforms are designed to be used by IT experts. In this paper, we propose a
semantics-driven model that allows non-IT experts (e.g. plant scientist, city
planner) to configure IoT middleware components easier and faster. Such tools
allow them to retrieve the data they want without knowing the underlying
technical details of the sensors and the data processing components. We propose
a Context Aware Sensor Configuration Model (CASCoM) to address the challenge of
automated context-aware configuration of filtering, fusion, and reasoning
mechanisms in IoT middleware according to the problems at hand. We incorporate
semantic technologies in solving the above challenges. We demonstrate the
feasibility and the scalability of our approach through a prototype
implementation based on an IoT middleware called Global Sensor Networks (GSN),
though our model can be generalized into any other middleware platform. We
evaluate CASCoM in agriculture domain and measure both performance in terms of
usability and computational complexity.Comment: 9th International Conference on Semantics, Knowledge & Grids (SKG),
Beijing, China, October, 201
Investigating IoT Middleware Platforms for Smart Application Development
With the growing number of Internet of Things (IoT) devices, the data
generated through these devices is also increasing. By 2030, it is been
predicted that the number of IoT devices will exceed the number of human beings
on earth. This gives rise to the requirement of middleware platform that can
manage IoT devices, intelligently store and process gigantic data generated for
building smart applications such as Smart Cities, Smart Healthcare, Smart
Industry, and others. At present, market is overwhelming with the number of IoT
middleware platforms with specific features. This raises one of the most
serious and least discussed challenge for application developer to choose
suitable platform for their application development. Across the literature,
very little attempt is done in classifying or comparing IoT middleware
platforms for the applications. This paper categorizes IoT platforms into four
categories namely-publicly traded, open source, developer friendly and
end-to-end connectivity. Some of the popular middleware platforms in each
category are investigated based on general IoT architecture. Comparison of IoT
middleware platforms in each category, based on basic, sensing, communication
and application development features is presented. This study can be useful for
IoT application developers to select the most appropriate platform according to
their application requirement
MOSDEN: An Internet of Things Middleware for Resource Constrained Mobile Devices
The Internet of Things (IoT) is part of Future Internet and will comprise
many billions of Internet Connected Objects (ICO) or `things' where things can
sense, communicate, compute and potentially actuate as well as have
intelligence, multi-modal interfaces, physical/ virtual identities and
attributes. Collecting data from these objects is an important task as it
allows software systems to understand the environment better. Many different
hardware devices may involve in the process of collecting and uploading sensor
data to the cloud where complex processing can occur. Further, we cannot expect
all these objects to be connected to the computers due to technical and
economical reasons. Therefore, we should be able to utilize resource
constrained devices to collect data from these ICOs. On the other hand, it is
critical to process the collected sensor data before sending them to the cloud
to make sure the sustainability of the infrastructure due to energy
constraints. This requires to move the sensor data processing tasks towards the
resource constrained computational devices (e.g. mobile phones). In this paper,
we propose Mobile Sensor Data Processing Engine (MOSDEN), an plug-in-based IoT
middleware for mobile devices, that allows to collect and process sensor data
without programming efforts. Our architecture also supports sensing as a
service model. We present the results of the evaluations that demonstrate its
suitability towards real world deployments. Our proposed middleware is built on
Android platform
Sensor Search Techniques for Sensing as a Service Architecture for The Internet of Things
The Internet of Things (IoT) is part of the Internet of the future and will
comprise billions of intelligent communicating "things" or Internet Connected
Objects (ICO) which will have sensing, actuating, and data processing
capabilities. Each ICO will have one or more embedded sensors that will capture
potentially enormous amounts of data. The sensors and related data streams can
be clustered physically or virtually, which raises the challenge of searching
and selecting the right sensors for a query in an efficient and effective way.
This paper proposes a context-aware sensor search, selection and ranking model,
called CASSARAM, to address the challenge of efficiently selecting a subset of
relevant sensors out of a large set of sensors with similar functionality and
capabilities. CASSARAM takes into account user preferences and considers a
broad range of sensor characteristics, such as reliability, accuracy, location,
battery life, and many more. The paper highlights the importance of sensor
search, selection and ranking for the IoT, identifies important characteristics
of both sensors and data capture processes, and discusses how semantic and
quantitative reasoning can be combined together. This work also addresses
challenges such as efficient distributed sensor search and
relational-expression based filtering. CASSARAM testing and performance
evaluation results are presented and discussed.Comment: IEEE sensors Journal, 2013. arXiv admin note: text overlap with
arXiv:1303.244
A Sleep Scheme Based on MQ Broker Using Subscribe/Publish in IoT Network
Constrained Application Protocol (CoAP) is a transfer protocol that is used for Internet of Things (IoT) devices such as sensors and actuators equip with low power supply, limited computing processor, and constrained network environment. For the constrained devices of CoAP based IoT network, we present a sleepy scheme based on a Message Queue (MQ) broker that supports the subscribe/publish communication architecture in the IoT middleware to enable the devices having better energy consumption. The IoT middleware is a server that providing services for storing and retrieving information of IoT node using Resource Directory (RD) functionality, and supporting the sleepy scheme using MQ broker functionality. The RD provides HTTP services to the HTTP client based application for discovering and looking up information of IoT nodes which are registered to the RD. The functionality of MQ broker is used for performs store-and-forward messaging. The MQ provides the service for IoT nodes to publish data to the middleware. The data shall be subscribed by the client application. The IoT node in the sleep mode that cannot be accessed by the client. Through the IoT middleware, the client can subscribe the IoT node for getting the result from IoT node after wake up. Once the IoT node wakes-up from the sleep status, the IoT middleware publishes the subscribed result to the client
IoT Middleware Platforms for Smart Energy Systems: An Empirical Expert Survey
Middleware platforms are key technology in any Internet of Things (IoT) system, considering their role in managing the intermediary communications between devices and applications. In the energy sector, it has been shown that IoT devices enable the integration of all network assets to one large distributed system. This comes with significant benefits, such as improving energy efficiency, boosting the generation of renewable energy, reducing maintenance costs and increasing comfort. Various existing IoT middlware solutions encounter several problems that limit their performance, such as vendor locks. Hence, this paper presents a literature review and an expert survey on IoT middleware platforms in energy systems, in order to provide a set of tools and functionalities to be supported by any future efficient, flexible and interoperable IoT middleware considering the market needs. The analysis of the results shows that experts currently use the IoT middleware mainly to deploy services such as visualization, monitoring and benchmarking of energy consumption, and energy optimization is considered as a future application to target. Likewise, non-functional requirements, such as security and privacy, play vital roles in the IoT platforms’ performances
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
End-to-End Privacy for Open Big Data Markets
The idea of an open data market envisions the creation of a data trading
model to facilitate exchange of data between different parties in the Internet
of Things (IoT) domain. The data collected by IoT products and solutions are
expected to be traded in these markets. Data owners will collect data using IoT
products and solutions. Data consumers who are interested will negotiate with
the data owners to get access to such data. Data captured by IoT products will
allow data consumers to further understand the preferences and behaviours of
data owners and to generate additional business value using different
techniques ranging from waste reduction to personalized service offerings. In
open data markets, data consumers will be able to give back part of the
additional value generated to the data owners. However, privacy becomes a
significant issue when data that can be used to derive extremely personal
information is being traded. This paper discusses why privacy matters in the
IoT domain in general and especially in open data markets and surveys existing
privacy-preserving strategies and design techniques that can be used to
facilitate end to end privacy for open data markets. We also highlight some of
the major research challenges that need to be address in order to make the
vision of open data markets a reality through ensuring the privacy of
stakeholders.Comment: Accepted to be published in IEEE Cloud Computing Magazine: Special
Issue Cloud Computing and the La
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