Biology of Applied Digital Ecosystems

A primary motivation for our research in Digital Ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the biological processes that contribute to these properties have not been made explicit in Digital Ecosystems research. Here, we discuss how biological properties contribute to the self-organising features of biological ecosystems, including population dynamics, evolution, a complex dynamic environment, and spatial distributions for generating local interactions. The potential for exploiting these properties in artificial systems is then considered. We suggest that several key features of biological ecosystems have not been fully explored in existing digital ecosystems, and discuss how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, with measures originating from theoretical ecology, to confirm its likeness to a biological ecosystem. Including the responsiveness to requests for applications from the user base, as a measure of the 'ecological succession' (development).Comment: 9 pages, 4 figure, conferenc

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

Population genomic structure of the gelatinous zooplankton species Mnemiopsis leidyi in its nonindigenous range in the North Sea

Nonindigenous species pose a major threat for coastal and estuarine ecosystems. Risk management requires genetic information to establish appropriate management units and infer introduction and dispersal routes. We investigated one of the most successful marine invaders, the ctenophore Mnemiopsis leidyi, and used genotyping-by-sequencing (GBS) to explore the spatial population structure in its nonindigenous range in the North Sea. We analyzed 140 specimens collected in different environments, including coastal and estuarine areas, and ports along the coast. Single nucleotide polymorphisms (SNPs) were called in approximately 40 k GBS loci. Population structure based on the neutral SNP panel was significant (F-ST .02; p < .01), and a distinct genetic cluster was identified in a port along the Belgian coast (Ostend port; pairwise F-ST .02-.04; p < .01). Remarkably, no population structure was detected between geographically distant regions in the North Sea (the Southern part of the North Sea vs. the Kattegat/Skagerrak region), which indicates substantial gene flow at this geographical scale and recent population expansion of nonindigenous M. leidyi. Additionally, seven specimens collected at one location in the indigenous range (Chesapeake Bay, USA) were highly differentiated from the North Sea populations (pairwise F-ST .36-.39; p < .01). This study demonstrates the utility of GBS to investigate fine-scale population structure of gelatinous zooplankton species and shows high population connectivity among nonindigenous populations of this recently introduced species in the North Sea. OPEN RESEARCH BADGES This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at: The DNA sequences generated for this study are deposited in the NCBI sequence read archive under SRA accession numbers -, and will be made publically available upon publication of this manuscript

Islands of Sustainability in Time and Space

We review the economics perspective on sustainable resource use and sustainable development. Under standard conditions, dynamic efficiency leads to sustainability of renewable resources but not the other way around. For the economic-ecological system as a whole, dynamic efficiency and intergenerational equity similarly lead to sustainability, but ad hoc rules of sustainability may well lead to sacrifices in human welfare. We then address the challenges of extending economic sustainability to space as well as time and discuss the factors leading to optimal islands of preservation regarding renewable resources. Exogenous mandates based on moral imperatives such as self-sufficiency and strong sustainability may result in missed win-win opportunities that could improve both the economy and the environment, as well as increase social welfare across generations.Islands of sustainability, sustainable development, sustainability science, fisheries, forests

Information Producers, Information Consumers : Location Data Privacy in Institutional Settings

Peer reviewedPreprin

Towards Odor-Sensitive Mobile Robots

J. Monroy, J. Gonzalez-Jimenez, "Towards Odor-Sensitive Mobile Robots", Electronic Nose Technologies and Advances in Machine Olfaction, IGI Global, pp. 244--263, 2018, doi:10.4018/978-1-5225-3862-2.ch012 Versión preprint, con permiso del editorOut of all the components of a mobile robot, its sensorial system is undoubtedly among the most critical ones when operating in real environments. Until now, these sensorial systems mostly relied on range sensors (laser scanner, sonar, active triangulation) and cameras. While electronic noses have barely been employed, they can provide a complementary sensory information, vital for some applications, as with humans. This chapter analyzes the motivation of providing a robot with gas-sensing capabilities and also reviews some of the hurdles that are preventing smell from achieving the importance of other sensing modalities in robotics. The achievements made so far are reviewed to illustrate the current status on the three main fields within robotics olfaction: the classification of volatile substances, the spatial estimation of the gas dispersion from sparse measurements, and the localization of the gas source within a known environment

ScaFi: A Scala DSL and Toolkit for Aggregate Programming

Supported by current socio-scientific trends, programming the global behaviour of whole computational collectives makes for great opportunities, but also significant challenges. Recently, aggregate computing has emerged as a prominent paradigm for so-called collective adaptive systems programming. To shorten the gap between such research endeavours and mainstream software development and engineering, we present ScaFi, a Scala toolkit providing an internal domain-specific language, libraries, a simulation environment, and runtime support for practical aggregate computing systems development

Energy Efficient Communication Protocols for Wireless Sensor Networks

The popularity of Wireless Sensor Networks have increased tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. Since these devices rely on battery power and may be placed in hostile environments replacing them becomes a tedious task. Thus, improving the energy of these networks becomes important.The thesis provides methods for clustering and cluster head selection to WSN to improve energy efficiency. It presents a comparison between the different methods on the basis of the network lifetime . It proposes a modified approach for cluster head selection with good performance and reduced computational complexity .In addition it also proposes BFO as an algorithm for clustering of WSN which would result improved performance with faster convergence