Cloud Service Selection System Approach based on QoS Model: A Systematic Review

The Internet of Things (IoT) has received a lot of interest from researchers recently. IoT is seen as a component of the Internet of Things, which will include billions of intelligent, talkative "things" in the coming decades. IoT is a diverse, multi-layer, wide-area network composed of a number of network links. The detection of services and on-demand supply are difficult in such networks, which are comprised of a variety of resource-limited devices. The growth of service computing-related fields will be aided by the development of new IoT services. Therefore, Cloud service composition provides significant services by integrating the single services. Because of the fast spread of cloud services and their different Quality of Service (QoS), identifying necessary tasks and putting together a service model that includes specific performance assurances has become a major technological problem that has caused widespread concern. Various strategies are used in the composition of services i.e., Clustering, Fuzzy, Deep Learning, Particle Swarm Optimization, Cuckoo Search Algorithm and so on. Researchers have made significant efforts in this field, and computational intelligence approaches are thought to be useful in tackling such challenges. Even though, no systematic research on this topic has been done with specific attention to computational intelligence. Therefore, this publication provides a thorough overview of QoS-aware web service composition, with QoS models and approaches to finding future aspects

Efficient Learning Machines

Computer scienc

Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

GUT-BACTERIA SYMBIOSIS IN INSECT PESTS

Insects are one of the most fascinating taxa on Earth: their diversity, diffusion, colonization of different niches are unparalleled in the animal kingdom. Besides, they have a remarkable impact on human life: they are parasites for people, animals and crops, vectors of diseases, pollinators, and even breeding animals (e.g. honeybees, silkworms). This extraordinary evolutionary success and diversification is partially due to the symbiotic relationships that insects have with a wide range of bacteria. These symbionts can be divided into primary, secondary symbionts and gut bacteria. Primary symbionts are found in very specialized cells (the bacteriocytes), strictly maternally transmitted and not cultivable. They are essential for their host, and vice-versa: they can actually be considered part of a single organism called \u201cholobiont\u201d. Secondary symbionts are not necessary for the host survival, although often beneficial, and they can inhabit various organs and tissues. In this category fall also reproductive parasites, as Wolbachia, which spreads in the population by maternal transmission, manipulating the reproduction of the host to favour the birth of infected daughters. Finally, gut bacteria are a more vague category, comprising organisms that live in the insect intestine because they are ingested with the diet, but also symbionts that establish a close relationship with the host, being essential for its survival and development. The roles of all these microorganisms are, to different extents, important for the insect physiology. Primary symbionts are generally essential to complement unbalanced diets and secondary ones contribute to the host fitness, while reproduction parasites deeply affect the reproduction mode of their hosts. Even commensals have been demonstrated to influence the development, mating choice and immune responses in Drosophila flies. For these reasons, the understanding of the biology of an insect can not do without the characterisation of its microbiota. In the second chapter of my PhD thesis, a review on the microbial ecology techniques applied to the study of insect microbial communities gives an overview on the methods that can be applied to this purpose. On one hand, molecular analyses based on the 16S gene sequencing, such as 16S rRNA barcoding (pyrotag) and Denaturing Gradient Gel Electrophoresis (DGGE) are the most powerful methods to get a complete picture of the microbial community composition and structure. Microscopic localisation of symbionts can be also achieved by Fluorescent In Situ Hybridisation. On the other hand, the isolation of bacteria allows to deeply characterize the cultivable fraction, verifying through direct in vitro tests the activities of the strains. Taking advantage of a strain collection isolated from the target insect, the symbiotic relationship can be investigated through in vivo experiments. The more common ones involve i) the labeling of the strains with fluorescent proteins and the recolonization of the insects, to evaluate their localisation and colonisation ability, ii) the assessment of the detrimental effects of symbionts deprivation on the hosts, and iii) the comparison of insects monoassociated with different strains to check the effects on host fitness. To further analyse the interaction between bacteria and their hosts from a genetic point of view, advanced techniques, such as Signature Tagged Mutagenesis or In Vivo Expression Technology, can be performed. Many of these techniques have been applied in the case studies here presented, in which the microbial communities associated to three insect pests have been characterised. In the third chapter is presented a study on the spotted-wing fly Drosophila suzukii. Unlike its relative D. melanogaster, which feeds on rotten fruit, this fly feeds and lays eggs on healthy fruits. The most damaged crops are members of the Drupaceae family (e.g. cherries) and berries (strawberries, raspberries, blueberries). The bacterial community associated to this pest have been characterised with a focus on acetic acid bacteria (AAB), important symbionts of many sugar-feeding insects. According to our findings, D. suzukii harbours a diverse community of AAB, detected both in the isolate collection and in culture-independent screenings (pyrotag, DGGE). They are primarily localised in the gut, attached to the peritrophic matrix, as showed by FISH micrographs. The ability of three AAB species (Gluconobacter oxydans, Acetobacter tropicalis and Acetobacter indonesiensis) to colonise the gut has been proved by recolonization experiments of the insect using GFP-marked strains. In the fourth chapter, the bacterial community of the wood-feeding beetle Rhynchophorus ferrugineus has been analysed. Commonly named Red Palm Weevil (RPW), this insect is an important pest for palm trees. The plants are damaged mainly by the larvae, which dig tunnels in the trunks until pupation. Bacteria associated to the red palm weevil have been studied primarily by molecular means (pyrotag). Our results outline that the bacteria hosted by R. ferrugineus are mainly acquired from the environment while feeding. Indeed, a sharp difference has been registered between field-caught and bred specimens. While field caught RPW harbour more bacterial taxa which are in common with their feeding plants, the animals fed on apple in the laboratory show a higher prevalence of lactic acid and acetic acid bacteria, which presumably grow on the rotten fruit. The latter result is further confirmed by the bacterial isolations performed on apple-fed specimens. Besides, the DNA sequence of a primary symbiont, Candidatus Nardonella, has been detected. This bacterium has been shown to inhabit a wide range of insects of the same family of the RPW, Curculionidae. The fifth chapter is about the gut bacterial community of Psacothea hilaris hilaris. Native of Japan and east China, this longicorn beetle (family: Cerambicidae) arrived in Italy as a consequence of the wood trade, and settled as a stable population in a small area in Como province. Its larvae dig tunnels in the trunks of the trees of the Moraceae family, while the adults feed on leaves. The most damaged by its feeding habits are mulberry and fig trees. This beetle hosts a variegate gut microbiota, that, as shown by DGGE, greatly changes according to the diet and to the gut tract examined. The cultivable fraction of this microbiota has been tested for several activities that proved the capability of the community as a whole to exploit the food sources in the insect gut (primarily, sugars from plant cell walls) and to assist their host in carbon and nitrogen absorption. Thus, even if acquired from the environment, these bacteria seem to be adapted to a symbiotic lifestyle. From the comparison among these three studies, some conclusions can be drawn. All three case studies outline the importance of the diet in shaping the insect microbial community. In detail, wild insects always show higher diversity and individual variability in their associated microbiota. Reared insects appear, on the contrary, dominated by the species that can rapidly grow on laboratory diets, such as Lactobacillales and Enterobacteriales. Secondly, these studies depict a more accurate image of the commensal bacteria, which are not merely acquired by chance through feeding, but are capable to actively colonize insect guts, and to efficiently exploit this niche to multiply and spread in the environment. Finally, the research data point out that the origin and the function of many of the organisms detected in insects are yet poorly understood. For this reason, these studies can be considered a basis to for future research, aimed to a more in-depth understanding of the roles of these bacteria and their interactions with the hosts

Evolutionary genomics : statistical and computational methods

This open access book addresses the challenge of analyzing and understanding the evolutionary dynamics of complex biological systems at the genomic level, and elaborates on some promising strategies that would bring us closer to uncovering of the vital relationships between genotype and phenotype. After a few educational primers, the book continues with sections on sequence homology and alignment, phylogenetic methods to study genome evolution, methodologies for evaluating selective pressures on genomic sequences as well as genomic evolution in light of protein domain architecture and transposable elements, population genomics and other omics, and discussions of current bottlenecks in handling and analyzing genomic data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that lead to the best results. Authoritative and comprehensive, Evolutionary Genomics: Statistical and Computational Methods, Second Edition aims to serve both novices in biology with strong statistics and computational skills, and molecular biologists with a good grasp of standard mathematical concepts, in moving this important field of study forward

Evolutionary Genomics

This open access book addresses the challenge of analyzing and understanding the evolutionary dynamics of complex biological systems at the genomic level, and elaborates on some promising strategies that would bring us closer to uncovering of the vital relationships between genotype and phenotype. After a few educational primers, the book continues with sections on sequence homology and alignment, phylogenetic methods to study genome evolution, methodologies for evaluating selective pressures on genomic sequences as well as genomic evolution in light of protein domain architecture and transposable elements, population genomics and other omics, and discussions of current bottlenecks in handling and analyzing genomic data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that lead to the best results. Authoritative and comprehensive, Evolutionary Genomics: Statistical and Computational Methods, Second Edition aims to serve both novices in biology with strong statistics and computational skills, and molecular biologists with a good grasp of standard mathematical concepts, in moving this important field of study forward

Sustainable Agriculture and Advances of Remote Sensing (Volume 2)

Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publication of the results, among others