Mario Siller

Using lightweight virtual machines to achieve resource adaptation in middleware

Current middleware does not offer enough support to cover the demands of emerging application domains, such as embedded systems or those featuring distributed multimedia services. These kinds of applications often have timeliness constraints and yet are highly susceptible to dynamic and unexpected changes in their environment. There is then a clear need to introduce adaptation in order for these applications to deal with such unpredictable changes. Resource adaptation can be achieved by using scheduling or allocation algorithms, for large-scale applications, but such a task can be complex and error-prone. Virtual machines (VMs) represent a higher-level approach, whereby resources can be managed without dealing with lower-level details, such as scheduling algorithms, scheduling parameters and so on. However, the overhead penalty imposed by traditional VMs is unsuitable for real-time applications. On the other hand, virtualisation has not been previously exploited as a means to achieve resource adaptation. This study presents a lightweight VM framework that exploits application-level virtualisation to achieve resource adaptation in middleware for soft real-time applications. Experimental results are presented to validate the approach.

Node localization in WSN using trigonometric figures

Wireless Sensor Network for their rapid deployment can be used in habitat monitoring for detecting fire and in disaster for helping rescue teams. Node localization is key factor for some applications. We propose the Triangular Centroid Localization algorithm (TCL). It is based in simple trigonometric figures and it does not require special hardware or synchronization time. In our simulations using the received signal strength indicator; TCL improves the accuracy of Centroid Localization (CL) in 54% and Weighted Centroid Localization (WCL) in 64%; using the link quality indicator it improves to CL in 38% and WCL in 64.98%.

A fingerprinting indoor localization algorithm based deep learning

Fingerprinting in essence uses a machine to infer physicals locations from radio map data. This machines are usually either probabilistic and neural networks consisting of one layer. In this propose we use deeper machines (DNN, DBN and GB-DBN) to increase the estimation accuracy and reduce generalization error on dynamic indoor environment. Also we investigated the impact of pre-training algorithm on fingerprinting indoor location systems. Experimental results demonstrate that deep models provide an efficient generalization performance on indoor environments. They have the disadvantage that demand high processing resources when they are trained on off-line phase, however, deep models are swift to predict during on-line phase.

An Ontology for the Quality of Experience framework

Agents need a formal representation of knowledge. This is modelled in an ontology. We present a survey of ontologies in the area of QoS management. From the survey we identified that improvements can be done in the Ontology of the Quality of Experience framework. We believe that with the extension full QoS Management capabilities can be then supported in the context of Quality of Experience. We focus in the appropriate QoS mechanism selection, network monitoring and QoS adaptation. With the additional concepts and actions the QoE ontology meets three key requirements for a QoS ontology: (i) decide which QoS mechanisms is better to fits the user needs; (ii) perform QoS monitoring and detection of SLA violations; and (iii) carry out QoS adaptation. Two experimental scenarios are currently being conducted. In scenario 1 the original ontology is used whilst for scenario 2 the extended version is employed. An initial comparative analysis is performed.

Wireless Sensor Networks Formation: Approaches and Techniques

Nowadays, wireless sensor networks (WSNs) emerge as an active research area in which challenging topics involve energy consumption, routing algorithms, selection of sensors location according to a given premise, robustness, efficiency, and so forth. Despite the open problems in WSNs, there are already a high number of applications available. In all cases for the design of any application, one of the main objectives is to keep the WSN alive and functional as long as possible. A key factor in this is the way the network is formed. This survey presents most recent formation techniques and mechanisms for the WSNs. In this paper, the reviewed works are classified into distributed and centralized techniques. The analysis is focused on whether a single or multiple sinks are employed, nodes are static or mobile, the formation is event detection based or not, and network backbone is formed or not. We focus on recent works and present a discussion of their advantages and drawbacks. Finally, the paper overviews a series of open issues which drive further research in the area.

A big picture on localization algorithms considering sensor logic location

Wireless sensor networks (WSNs) have been applied in areas such as military surveillance, environmental monitoring, habitat and structural monitoring, domotics, battlefield surveillance and robotics. The aim of this survey is to present the state-of-the-art in localization algorithms which consider the combination of different factors such as localization schemes, propagation models, communication protocols, traffic patterns analysis and sensor logic location. The latter represents the inherent characteristic of the object to which the sensor is attached to. We believe that the precision of the localization algorithms can be improved when these factors are considered as whole rather than isolated effects. A classification and the main solutions for each factor are presented. The advantages, performance issues and the relation of the solutions with the other factors are discussed. The article concludes with opened research questions and possible further research directions.

A node localization scheme for zigbee-based sensor networks

The localization problem consists in estimating the position of the nodes within the network. This is a crucial issue for location-dependant applications. This paper presents an implementation of a localization scheme based only on the received signal strength (SS) in a Zigbee-based sensor network. This is done by taking advantage of the inherent radio communication capability present in each node. The algorithm is intended for an outdoor environment. It is based in a model, which infers distance between neighboring nodes using the SS. A coordinate system is then derived employing a multidimensional scaling (MDS) technique. The signal power level variability due to ground reflection is approached using Lloyd Effect (from optics) and incorporated in the model.

A Peer-to-Peer Architecture for Real-Time Distributed Visualization of 3D Collaborative Virtual Environments

A 3D collaborative virtual environment (CVE) is a distributed simulation of a 3D virtual environment (VE) in which a large number of users located in different geographical places can interact with each other in real-time. In order to collaborate in a 3D CVE, it is necessary to send update messages corresponding to the change in the state of a shared object among involved users. In this paper, we present a new system for real-time distributed visualization of 3D CVEs. This distribution is carried out on a grid of heterogeneous computers implementing a communication based on a hybrid peer-to-peer (P2P) architecture. Our system ensures a coherent visualization in according to a consistent updating of 3D VE for all involved users. In this way, each user can visualize in real-time the changes done by other users.

OpenAG: A Globally Distributed Network of Food Computing

With natural resource scarcity, flattening yields, loss of biodiversity, changing climates, environmental degradation, and booming urban populations, the current food system is rapidly approaching its natural limit. What will define the next agricultural revolution, and how will it impact and shape global societies? This is the central research question of the Open Agriculture (OpenAG) Initiative at the MIT Media Lab. The goal is an alternative distributed farming system based on new methods of communication, sensing, data collection, and automation that will enable network effect advantages in the next generation of food production. This department is part of a special issue on pervasive food.

Internet of vehicles: Cloud and fog computing approaches

Some of the mobility challenges in the cities can be approached with the Internet of Things, Cloud Computing, and Fog Computing. In this work we consider the city as a system of systems and focus on the interaction of those entities with the mobility systems. A key element that allows this interaction is a vehicle on-board unit. In this work we address the interconnection, enabling technologies, interoperability, scalability, geo-distribution and time constrains aspects in the architectural design of mobility systems. For this we propose the On-Board Unit architecture and cover three different levels of technification in information and communication technologies. Based on this differentiation we are able to include Cloud and Fog Computing into our proposed designs.