Elena Meshkova

Modeling the home environment using ontology with applications in software configuration management

The rapid development of the network technologies has enabled the construction of heterogeneous home networks. However, the control of the smart home environment that ensures the conflict-free, up-to-date and smooth functioning of the home environment is not trivial. It is necessary to track the state of the numerous devices which compose the home environment, as well as the respective services installed on them, to ensure conflict-free seamless operation of the system. In this paper we present an ontology-enabled knowledge base for home networks. The knowledge base allows to depict complex relations between devices and services working in a home environment, for example issues to be considered before installing a new software version on a certain device, such as the user profile, interference with existing devices, etc. The knowledge base is a part of the COMANCHE system, which aims to provide a software configuration management infrastructure which can be used in the home automation domain. To the best of our knowledge, the presented system provides a first comprehensive framework for reasoning about services in the home environment realized in close collaboration with the relevant industry.

Experimental spectrum sensor testbed for constructing indoor Radio Environmental Maps

In this paper we describe an experimental testbed to empirically study the construction of Radio Environmental Maps (REMs) in indoor environments. The testbed allows investigating the characteristics and modeling of the radio environment for indoor scenarios. The deployed system is a network of over 80 heterogeneous wireless spectrum sensors with significantly different measurement capabilities in an office building consisting of multiple rooms. As application examples we consider two scenarios, one illustrating the indoor propagation conditions and another showing temporal aspects of primary node activities as observed by sensing devices. The observed phenomena strongly indicate that development of general radio environment map solutions for indoor use are extremely challenging, unless heterogeneity of spectrum sensors and non-linearity of propagation conditions is considered. Our measurement results advocate dynamic construction of REMs instead of static solutions. We strongly believe that the deployed testbed and obtained experimental data can further facilitate research in the area of REMs.

Implementation and Performance Evaluation of nanoIP Protocols: Simplified Versions of TCP, UDP,HTTP and SLP for Wireless Sensor Networks

We present the implementation architecture and performance evaluation of the nanoIP protocol stack. The stack consists of miniaturized versions of UDP, TCP, SLP and HTTP protocols with reduced header sizes and complexity to make the protocols usable in wireless sensor networks. Similarity to the TCP/IP stack facilitates the development of gateways towards IP-based networks and makes the use of the stack easier for developers accustomed to network programming. Our implementation work and experiments show that the footprint of the stack is acceptable even for the most resource constrained sensor nodes.

Using cognitive radio principles for wireless resource management in home networking

The demand for higher data rates, capacity and better quality-of-service is constantly growing for home networks. Therefore, there is a pressing need for efficient use of wireless network resources. In this context, the application of cognitive radio principles that enable network nodes to characterize their environment and control their resources based on the acquired knowledge, is the prominent solution for next generation home networks. In this paper we present an architecture and a prototype implementation based on these principles. The proposed system is able to autonomously optimize the performance of network nodes in a dynamic environment according to the goals, restrictions and policy regulations formulated by network stakeholders. The obtained results show the momentous and suitability of the cognitive framework for home networking.

Cognitive Radio for Home Networking

Cognitive Radios have emerged as one the most promising methods to increase wireless system efficiency through dynamic spectrum access combined with other cross-layer optimization methods. Most of the research prototypes and demonstrations have so far focused on either general platforms or scenarios that are predominantly taken from military or emergency communications domain. In this demonstration we show the prototype environment that is build around realistic home networking scenarios. The demonstration has two purposes. First, it demonstrates how a set of different implemented and integrated components can achieve local area optimization both in frequency allocation and other domains. Second, it shows the viability and attractiveness of cognitive radio methods for future commercial home networking devices. The demonstration showcases dynamic spectrum allocation and policy based behavioral changes in a home environment, where several multimedia stream and data communication connections are competing against each other.

Self-organizing home networking based on cognitive radio technologies

The increasing complexity of the future wireless networks leads to the requirement for self-organization. This is true especially in home networking where users are typically not networking professionals and cannot be expected to perform complex optimization and management tasks. In this context, cognitive radio concept combining cross-layer optimization and learning mechanisms is a promising solution. We demonstrate a cognitive home networking prototype, which addresses practical problems users face with the present-day wireless networks at home. The prototype shows how nodes using IEEE 802.11 radios and WARP boards operate under the Cognitive Resource Manager (CRM). The nodes achieve the desired performance by handling network dynamics and controlling parameters taking independent or cooperative decisions and operating in different layers of the protocol stack. This is done using multiple control loops which are supported by the CRM architecture. We demonstrate the use of machine learning for online estimation of network activity patterns to enable more efficient Dynamic Spectrum Access (DSA) using Hidden Semi-Markov Models (HSMM). The demonstration showcases dynamic spectrum allocation and policy-based behavioral changes in a home environment, where several multimedia streams and data communication flows are competing against each other and against external, also primary, interferers.

Indoor coverage estimation from unreliable measurements using spatial statistics

Estimating the coverage of a wireless network is one of the key problems in network planning and management. In outdoor environments this is usually done using modern network planning tools combined with intensive drive tests. However, in indoor environments the problem is much more difficult. Solutions based on propagation modeling require precise building information for accuracy, and even then their performance is highly varying. Refining such predictions using measurements from mobile terminals is a promising possibility, but is not straightforward due to the noisy and unreliable measurement quality. In this paper we study the performance of spatial statistics techniques for coverage prediction in indoor environments. Using data collected in an indoor testbed with 60 low cost radio receivers, we show that such techniques can yield accurate coverage predictions provided suitable preprocessing and filtering of the data is performed. Further, a simple optimization approach enables high prediction accuracy to be achieved using only a small subset of the available measurement devices. These results are also highly relevant to the minimization of drive tests (MDT) approach currently being developed in 3GPP to enable mobile terminals carry out coverage measurements for wireless networks.

MoteMaster: A Scalable Sensor Network Testbed for Rapid Protocol Performance Evaluation

Testbeds are necessary to evaluate the performance of network applications for a wide range of deployment scenarios. Especially in wireless sensor networks, where the performance highly depends on environmental conditions, traditional computer-based simulations provide validity to only limited extent. Different approaches have been carried out to develop generic testbeds for protocol evaluation, but they suffer from automation deficiencies such as the ability for fast iterations over different topologies or parameter settings. Those features are nevertheless necessary to study the performance of a developed solution in a variety of conditions. Furthermore, the legacy data storage of other testbeds make later processing less tractable. We present a scalable wireless sensor network testbed that provides a generic interface which can easily be incorporated into existing network research and data mining software. It uses a generic data storage format that allows ease of analysis. Higher utilization of resources by means of parallelisation of individual user tasks and multi-user support makes this testbed a valuable tool. It consists of inexpensive commercial off-the-shelf hardware and as it is open-source, requires no additional investment in legacy software.

An extendible metadata specification for component-oriented networks with applications to WSN configuration and optimization

Currently there is no widely accepted formalized description or metadata that represents networks, their components and interrelations between them. There is also no de facto classification of network parameters, models and services. The network community lacks a metadata specification similar to WSDL that represents networks in clear and unified manner and includes software, hardware and networking parts of the system description. This limits the advance of the frameworks aiming to assist the development of complex non-established network systems, such as wireless sensor, cognitive and heterogeneous networks. Additionally a standard metadata would enhance the interoperability and acceptance of various middleware, service discovery schemes and cross-layer optimization solutions. In this paper we suggest a simple, but comprehensive extensible metadata specification and a corresponding metamodel that allows to describe a wide range of network components and network configurations. We describe metadata and metamodel on the example of wireless sensor networks. In this field the need for standard metadata is particularly pressing due to the high number of available protocol solutions and lack of standardization.

CONFab: component based optimization of WSN protocol stacks using deployment feedback

Wireless sensor networks are characterized by a large number of non-standardized protocols and varying application requirements. This creates need for a systematic approach to rapidly design and optimize deployment specific protocol stacks. We employ component based optimization as a candidate solution, and use it as a basis for an extensible software framework called CONFab. We treat a particular protocol stack as a collection of interdependent configurable components. CONFab captures a deployment scenario description, relates it to the desired performance metrics, and correspondingly suggests suitable protocol stacks and parameter settings. It utilizes ontology centric knowledge base to select components from a pool of alternatives, reason on their compatibility and, thus create appropriate protocol stacks. The framework is equipped with a number of additional plugins that allow, for instance, to incorporate feedback from deployed systems and user inputs to anticipate network performance. We use a set of well-known MAC and routing protocols to validate the framework on the Indriya testbed in different user specified application and deployment conditions. The results indicate that CONFab with its component based approach helps in obtaining suitable protocol stacks and thereby achieving high performance characteristics.