Routing and scheduling approaches for energy-efficient data gathering in wireless sensor networks

Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2011.Thesis (Ph. D.) -- Bilkent University, 2011.Includes bibliographical references leaves 99-108.A wireless sensor network consists of nodes which are capable of sensing an environment and wirelessly communicating with each other to gather the sensed data to a central location. Besides the advantages for many applications, having very limited irreplaceable energy resources is an important shortcoming of the wireless sensor networks. In this thesis, we present effective routing and node scheduling solutions to improve network lifetime in wireless sensor networks for data gathering applications. Towards this goal, we first investigate the network lifetime problem by developing a theoretical model which assumes perfect data aggregation and power-control capability for the nodes; and we derive an upper-bound on the functional lifetime of a sensor network. Then we propose a routing protocol to improve network lifetime close to this upper-bound on some certain conditions. Our proposed routing protocol, called L-PEDAP, is based on constructing localized, self-organizing, robust and power-aware data aggregation trees. We also propose a node scheduling protocol that can work with our routing protocol together to improve network lifetime further. Our node scheduling protocol, called PENS, keeps an optimal number of nodes active to achieve minimum energy consumption in a round, and puts the remaining nodes into sleep mode for a while. Under some conditions, the optimum number can be greater than the minimum number of nodes required to cover an area. We also derive the conditions under which keeping more nodes alive can be more energy efficient. The extensive simulation experiments we performed to evaluate our PEDAP and PENS protocols show that they can be effective methods to improve wireless sensor network lifetime for data gathering applications where nodes have power-control capability and where perfect data aggregation can be used.Tan, Hüseyin ÖzgürPh.D

Behavioural equivalences and interference metrics for mobile ad-hoc networks

Abstract Connectivity and communication interference are two key aspects in mobile ad-hoc networks (MANETs). This paper proposes a process algebraic model targeted at the analysis of both such aspects. The framework includes a probabilistic process calculus and a suite of analytical techniques based on a probabilistic observational congruence and an interference-sensitive preorder. The former enables the verification of behavioural equivalences; the latter makes it possible to evaluate the interference level of behaviourally equivalent networks. The result is a comprehensive and effective framework for the behavioural analysis and a quantitative assessment of interference for wireless networks in the presence of node mobility. We show our techniques at work on two realistic case studies

Development of an integrated omics in silico workflow and its application for studying bacteria-phage interactions in a model microbial community

Microbial communities are ubiquitous and dynamic systems that inhabit a multitude of environments. They underpin natural as well as biotechnological processes, and are also implicated in human health. The elucidation and understanding of these structurally and functionally complex microbial systems using a broad spectrum of toolkits ranging from in situ sampling, high-throughput data generation ("omics"), bioinformatic analyses, computational modelling and laboratory experiments is the aim of the emerging discipline of Eco-Systems Biology. Integrated workflows which allow the systematic investigation of microbial consortia are being developed. However, in silico methods for analysing multi-omic data sets are so far typically lab-specific, applied ad hoc, limited in terms of their reproducibility by different research groups and suboptimal in the amount of data actually being exploited. To address these limitations, the present work initially focused on the development of the Integrated Meta-omic Pipeline (IMP), a large-scale reference-independent bioinformatic analyses pipeline for the integrated analysis of coupled metagenomic and metatranscriptomic data. IMP is an elaborate pipeline that incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning as well as genomic signature-based visualizations. The IMP-based data integration strategy greatly enhances overall data usage, output volume and quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python while relying on Docker for reproducibility. The IMP pipeline was then applied to a longitudinal multi-omic dataset derived from a model microbial community from an activated sludge biological wastewater treatment plant with the explicit aim of following bacteria-phage interaction dynamics using information from the CRISPR-Cas system. This work provides a multi-omic perspective of community-level CRISPR dynamics, namely changes in CRISPR repeat and spacer complements over time, demonstrating that these are heterogeneous, dynamic and transcribed genomic regions. Population-level analysis of two lipid accumulating bacterial species associated with 158 putative bacteriophage sequences enabled the observation of phage-host population dynamics. Several putatively identified bacteriophages were found to occur at much higher abundances compared to other phages and these specific peaks usually do not overlap with other putative phages. In addition, there were several RNA-based CRISPR targets that were found to occur in high abundances. In summary, the present work describes the development of a new bioinformatic pipeline for the analysis of coupled metagenomic and metatranscriptomic datasets derived from microbial communities and its application to a study focused on the dynamics of bacteria-virus interactions. Finally, this work demonstrates the power of integrated multi-omic investigation of microbial consortia towards the conversion of high-throughput next-generation sequencing data into new insights

Axmedis 2005

The AXMEDIS conference aims to promote discussions and interactions among researchers, practitioners, developers and users of tools, technology transfer experts, and project managers, to bring together a variety of participants. The conference focuses on the challenges in the cross-media domain (which include production, protection, management, representation, formats, aggregation, workflow, distribution, business and transaction models), and the integration of content management systems and distribution chains, with particular emphasis on cost reduction and effective solutions for complex cross-domain problems