Self-adaptive architectures in IoT systems: a systematic literature review

Over the past few years, the relevance of the Internet of Things (IoT) has grown significantly and is now a key component of many industrial processes and even a transparent participant in various activities performed in our daily life. IoT systems are subjected to changes in the dynamic environments they operate in. These changes (e.g. variations in bandwidth consumption or new devices joining/leaving) may impact the Quality of Service (QoS) of the IoT system. A number of self-adaptation strategies for IoT architectures to better deal with these changes have been proposed in the literature. Nevertheless, they focus on isolated types of changes. We lack a comprehensive view of the trade-offs of each proposal and how they could be combined to cope with simultaneous events of different types.In this paper, we identify, analyze, and interpret relevant studies related to IoT adaptation and develop a comprehensive and holistic view of the interplay of different dynamic events, their consequences on QoS, and the alternatives for the adaptation. To do so, we have conducted a systematic literature review of existing scientific proposals and defined a research agenda for the near future based on the findings and weaknesses identified in the literature.

Evolution of phenotypic variance provides insights into the genetic basis of adaption

Most traits are polygenic and the contributing loci can be identified by GWAS. Their adaptive architecture is, however, poorly characterized. Here, we propose a new approach to study the adaptive architecture, which does not depend on genomic data. Relying on experimental evolution we measure the phenotypic variance in replicated populations during adaptation to a new environment. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting is a powerful approach to distinguish between oligogenic and polygenic adaptive architectures. We apply this new method to gene expression variance in male Drosophila simulans before and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We conclude that adaptive gene expression evolution is best explained by a highly polygenic adaptive architecture. We propose that the evolution of phenotypic variance provides a powerful approach to characterize the adaptive architecture, in particular when combined with genomic data.

Optimization of Quality of Experience for Video Traffic

<div>The rapid shift toward video on-demand and real time information systems has affected mobile as well as wired networks. The research community has placed a strong focus on optimizing the Quality of Experience (QoE) of video traffic, mainly because video is popular among Internet users. Techniques have been proposed in different directions towards improvement of the perception of video users. This paper investigates the performance of a novel cross-layer architecture for optimizing the QoE of video traffic. The proposed architecture is compared to two other architectures; non-adaptive and adaptive. For the former, video traffic is sent without adaptation, whereas for the later video sources adapt their transmission rate. Both are compared in terms of the mean opinion score of video sessions, number of sessions, delay, packet drop ratio, jitter and utilization. The results from extensive simulations show that the proposed architecture outperforms the non-adaptive and adaptive architectures for video traffic.</div>

Optimization of Quality of Experience for Video Traffic

<div>The rapid shift toward video on-demand and real time information systems has affected mobile as well as wired networks. The research community has placed a strong focus on optimizing the Quality of Experience (QoE) of video traffic, mainly because video is popular among Internet users. Techniques have been proposed in different directions towards improvement of the perception of video users. This paper investigates the performance of a novel cross-layer architecture for optimizing the QoE of video traffic. The proposed architecture is compared to two other architectures; non-adaptive and adaptive. For the former, video traffic is sent without adaptation, whereas for the later video sources adapt their transmission rate. Both are compared in terms of the mean opinion score of video sessions, number of sessions, delay, packet drop ratio, jitter and utilization. The results from extensive simulations show that the proposed architecture outperforms the non-adaptive and adaptive architectures for video traffic.</div>

Low concordance of short-term and long-term selection responses in experimental Drosophila populations

Experimental evolution is becoming a popular approach to study the genomic selection response of evolving populations. Computer simulation studies suggest that the accuracy of the signature increases with the duration of the experiment. Since some assumptions of the computer simulations may be violated, it is important to scrutinize the influence of the experimental duration with real data. Here, we use a highly replicated Evolve and Resequence study in Drosophila simulans to compare the selection targets inferred at different time points. At each time point, approximately the same number of SNPs deviates from neutral expectations, but only 10 % of the selected haplotype blocks identified from the full data set can be detected after 20 generations. Those haplotype blocks that emerge already after 20 generations differ from the others by being strongly selected at the beginning of the experiment and display a more parallel selection response. Consistent with previous computer simulations, our results demonstrate that only Evolve and Resequence experiments with a sufficient number of generations can characterize complex adaptive architectures.

Phenotypic and Genomic Local Adaptation across Latitude and Altitude in Populus trichocarpa

Local adaptation to climate allows plants to cope with temporally and spatially heterogeneous environments, and parallel phenotypic clines provide a natural experiment to uncover the genomic architecture of adaptation. Though extensive effort has been made to investigate the genomic basis of local adaptation to climate across the latitudinal range of tree species, less is known for altitudinal clines. We used exome capture to genotype 451 Populus trichocarpa genotypes across altitudinal and latitudinal gradients spanning the natural species range, and phenotyped these trees for a variety of adaptive traits in two common gardens. We observed clinal variation in phenotypic traits across the two transects, which indicates climate-driven selection, and coupled gene-based genotype–phenotype and genotype–environment association scans to identify imprints of climatic adaptation on the genome. Although many of the phenotype- and climate-associated genes were unique to one transect, we found evidence of parallelism between latitude and altitude, as well as significant convergence when we compared our outlier genes with those putatively involved in climatic adaptation in two gymnosperm species. These results suggest that not only genomic constraint during adaptation to similar environmental gradients in poplar but also different environmental contexts, spatial scale, and perhaps redundant function among potentially adaptive genes and polymorphisms lead to divergent adaptive architectures.

Distinct patterns of selective sweep and polygenic adaptation

The central paradigm of molecular population genetics is selective sweeps, where targets of selection have independent effects on the phenotype and quickly rise to fixation. In quantitative genetics, many loci contribute epistatically to adaptation and subtle frequency changes occur at many loci. Since both paradigms could result in a sweep-like genomic signature, additional criteria are needed to distinguish them. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles under both paradigms. We identify several distinct patterns of selective sweeps and polygenic adaptation in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two paradigms.Author’s summaryThe selective sweep model assumes an independent frequency increase of favorable alleles and has been the basis of many tests for selection. While, polygenic adaptation is typically modelled by small frequency shifts in many loci. Recently, some theoretical and empirical work demonstrated that polygenic adaptation, similar to sweep, could also results in pronounced allele frequency changes. These results suggest that other distinct features need to be identified. Using computer simulations, we identified distinctive features for each paradigm that can be used to differentiate the sweep model from polygenic adaptation. Features such as allele frequency trajectories, time-series fitness, distribution of selected alleles on haplotypes, and parallelism among replicates can be used for development of suitable tests to distinguish between different adaptive architectures. These features provide the basis for theoretical modeling, design of selection experiments and data analysis.