6,051 research outputs found
Enabling High-Level Application Development for the Internet of Things
Application development in the Internet of Things (IoT) is challenging
because it involves dealing with a wide range of related issues such as lack of
separation of concerns, and lack of high-level of abstractions to address both
the large scale and heterogeneity. Moreover, stakeholders involved in the
application development have to address issues that can be attributed to
different life-cycles phases. when developing applications. First, the
application logic has to be analyzed and then separated into a set of
distributed tasks for an underlying network. Then, the tasks have to be
implemented for the specific hardware. Apart from handling these issues, they
have to deal with other aspects of life-cycle such as changes in application
requirements and deployed devices. Several approaches have been proposed in the
closely related fields of wireless sensor network, ubiquitous and pervasive
computing, and software engineering in general to address the above challenges.
However, existing approaches only cover limited subsets of the above mentioned
challenges when applied to the IoT. This paper proposes an integrated approach
for addressing the above mentioned challenges. The main contributions of this
paper are: (1) a development methodology that separates IoT application
development into different concerns and provides a conceptual framework to
develop an application, (2) a development framework that implements the
development methodology to support actions of stakeholders. The development
framework provides a set of modeling languages to specify each development
concern and abstracts the scale and heterogeneity related complexity. It
integrates code generation, task-mapping, and linking techniques to provide
automation. Code generation supports the application development phase by
producing a programming framework that allows stakeholders to focus on the
application logic, while our mapping and linking techniques together support
the deployment phase by producing device-specific code to result in a
distributed system collaboratively hosted by individual devices. Our evaluation
based on two realistic scenarios shows that the use of our approach improves
the productivity of stakeholders involved in the application development
The SATIN component system - a metamodel for engineering adaptable mobile systems
Mobile computing devices, such as personal digital assistants and mobile phones, are becoming increasingly popular, smaller, and more capable. We argue that mobile systems should be able to adapt to changing requirements and execution environments. Adaptation requires the ability-to reconfigure the deployed code base on a mobile device. Such reconfiguration is considerably simplified if mobile applications are component-oriented rather than monolithic blocks of code. We present the SATIN (system adaptation targeting integrated networks) component metamodel, a lightweight local component metamodel that offers the flexible use of logical mobility primitives to reconfigure the software system by dynamically transferring code. The metamodel is implemented in the SATIN middleware system, a component-based mobile computing middleware that uses the mobility primitives defined in the metamodel to reconfigure both itself and applications that it hosts. We demonstrate the suitability of SATIN in terms of lightweightedness, flexibility, and reusability for the creation of adaptable mobile systems by using it to implement, port, and evaluate a number of existing and new applications, including an active network platform developed for satellite communication at the European space agency. These applications exhibit different aspects of adaptation and demonstrate the flexibility of the approach and the advantages gaine
A network-aware framework for energy-efficient data acquisition in wireless sensor networks
Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN
Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues
The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain
Context-awareness for mobile sensing: a survey and future directions
The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions
Quality assessment technique for ubiquitous software and middleware
The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future
Logic-centred architecture for ubiquitous health monitoring
One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for\ud
multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework\ud
with customizable wireless interfaces and plug‘n’play capability to easily interconnect third party sensor devices. It caters to wireless\ud
body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment\ud
that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual\ud
development and remote deployment model. The complementary visual InferenceEngineEditor that comes with the package enables\ud
artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components\ud
and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a\ud
discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications
Implementation of Middleware for Internet of Things in Asset Tracking Applications: In-lining Approach
ThesisInternet of Things (IoT) is a concept that involves giving objects a digital identity and limited
artificial intelligence, which helps the objects to be interactive, process data, make decisions,
communicate and react to events virtually with minimum human intervention. IoT is intensified
by advancements in hardware and software engineering and promises to close the gap that exists
between the physical and digital worlds. IoT is paving ways to address complex phenomena,
through designing and implementation of intelligent systems that can monitor phenomena,
perform real-time data interpretation, react to events, and swiftly communicate observations. The
primary goal of IoT is ubiquitous computing using wireless sensors and communication
protocols such as Bluetooth, Wireless Fidelity (Wi-Fi), ZigBee and General Packet Radio
Service (GPRS).
Insecurity, of assets and lives, is a problem around the world. One application area of IoT is
tracking and monitoring; it could therefore be used to solve asset insecurity. A preliminary
investigation revealed that security systems in place at Central University of Technology, Free
State (CUT) are disjointed; they do not instantaneously and intelligently conscientize security
personnel about security breaches using real time messages. As a result, many assets have been
stolen, particularly laptops. The main objective of this research was to prove that a real-life application built over a generic
IoT architecture that innovatively and intelligently integrates: (1) wireless sensors; (2) radio
frequency identification (RFID) tags and readers; (3) fingerprint readers; and (4) mobile phones,
can be used to dispel laptop theft. To achieve this, the researcher developed a system, using the
heterogeneous devices mentioned above and a middleware that harnessed their unique
capabilities to bring out the full potential of IoT in intelligently curbing laptop theft.
The resulting system has the ability to: (1) monitor the presence of a laptop using RFID reader
that pro-actively interrogates a passive tag attached to the laptop; (2) detect unauthorized
removal of a laptop under monitoring; (3) instantly communicate security violations via cell
phones; and (4) use Windows location sensors to track the position of a laptop using Googlemaps.
The system also manages administrative tasks such as laptop registration, assignment and withdrawal which used to be handled manually. Experiments conducted using the resulting
system prototype proved the hypothesis outlined for this research
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