The utility of pollination for autonomic computing

From the biology’s point of view, pollination is an important step in the reproduction of seed plants. From our point of view, pollination is a promising and novel, biological paradigm for future dependable and self-managing computing systems. This estimation is based on the characteristics the pollination process between plants and insects implies inherently. To utilize pollination as a paradigm for self-managing and thus autonomic computing systems, this paper identifies the useful properties that emerge by the collaborative behavior of insects and plants during the pollination process. Based on this process the paper presents an artificial pollination system that implements these properties by adapting the natural architecture and behavior. Furthermore, the paper illustrates the practical value of this system by an application in aviation. Finally open issues and an outlook on future work are presented.1st IFIP International Conference on Biologically Inspired Cooperative Computing - Biological Inspiration 1Red de Universidades con Carreras en Informática (RedUNCI

A Survey on Natural Inspired Computing (NIC): Algorithms and Challenges

Nature employs interactive images to incorporate end users2019; awareness and implication aptitude form inspirations into statistical/algorithmic information investigation procedures. Nature-inspired Computing (NIC) is an energetic research exploration field that has appliances in various areas, like as optimization, computational intelligence, evolutionary computation, multi-objective optimization, data mining, resource management, robotics, transportation and vehicle routing. The promising playing field of NIC focal point on managing substantial, assorted and self-motivated dimensions of information all the way through the incorporation of individual opinion by means of inspiration as well as communication methods in the study practices. In addition, it is the permutation of correlated study parts together with Bio-inspired computing, Artificial Intelligence and Machine learning that revolves efficient diagnostics interested in a competent pasture of study. This article intend at given that a summary of Nature-inspired Computing, its capacity and concepts and particulars the most significant scientific study algorithms in the field

Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions

This overview gravitates on research achievements that have recently emerged from the confluence between Big Data technologies and bio-inspired computation. A manifold of reasons can be identified for the profitable synergy between these two paradigms, all rooted on the adaptability, intelligence and robustness that biologically inspired principles can provide to technologies aimed to manage, retrieve, fuse and process Big Data efficiently. We delve into this research field by first analyzing in depth the existing literature, with a focus on advances reported in the last few years. This prior literature analysis is complemented by an identification of the new trends and open challenges in Big Data that remain unsolved to date, and that can be effectively addressed by bio-inspired algorithms. As a second contribution, this work elaborates on how bio-inspired algorithms need to be adapted for their use in a Big Data context, in which data fusion becomes crucial as a previous step to allow processing and mining several and potentially heterogeneous data sources. This analysis allows exploring and comparing the scope and efficiency of existing approaches across different problems and domains, with the purpose of identifying new potential applications and research niches. Finally, this survey highlights open issues that remain unsolved to date in this research avenue, alongside a prescription of recommendations for future research.This work has received funding support from the Basque Government (Eusko Jaurlaritza) through the Consolidated Research Group MATHMODE (IT1294-19), EMAITEK and ELK ARTEK programs. D. Camacho also acknowledges support from the Spanish Ministry of Science and Education under PID2020-117263GB-100 grant (FightDIS), the Comunidad Autonoma de Madrid under S2018/TCS-4566 grant (CYNAMON), and the CHIST ERA 2017 BDSI PACMEL Project (PCI2019-103623, Spain)

A Survey on Natural Inspired Computing (NIC): Algorithms and Challenges

Nature employs interactive images to incorporate end users’ awareness and implication aptitude form inspirations into statistical/algorithmic information investigation procedures. Nature-inspired Computing (NIC) is an energetic research exploration field that has appliances in various areas, like as optimization, computational intelligence, evolutionary computation, multi-objective optimization, data mining, resource management, robotics, transportation and vehicle routing. The promising playing field of NIC focal point on managing substantial, assorted and self-motivated dimensions of information all the way through the incorporation of individual opinion by means of inspiration as well as communication methods in the study practices. In addition, it is the permutation of correlated study parts together with Bio-inspired computing, Artificial Intelligence and Machine learning that revolves efficient diagnostics interested in a competent pasture of study. This article intend at given that a summary of Nature-inspired Computing, its capacity and concepts and particulars the most significant scientific study algorithms in the field

Energy-efficient resource allocation scheme based on enhanced flower pollination algorithm for cloud computing data center

Cloud Computing (CC) has rapidly emerged as a successful paradigm for providing ICT infrastructure. Efficient and environmental-friendly resource allocation mechanisms, responsible for allocatinpg Cloud data center resources to execute user applications in the form of requests are undoubtedly required. One of the promising Nature-Inspired techniques for addressing virtualization, consolidation and energyaware problems is the Flower Pollination Algorithm (FPA). However, FPA suffers from entrapment and its static control parameters cannot maintain a balance between local and global search which could also lead to high energy consumption and inadequate resource utilization. This research developed an enhanced FPA-based energy efficient resource allocation scheme for Cloud data center which provides efficient resource utilization and energy efficiency with less probable Service Level Agreement (SLA) violations. Firstly, an Enhanced Flower Pollination Algorithm for Energy-Efficient Virtual Machine Placement (EFPA-EEVMP) was developed. In this algorithm, a Dynamic Switching Probability (DSP) strategy was adopted to balance the local and global search space in FPA used to minimize the energy consumption and maximize resource utilization. Secondly, Multi-Objective Hybrid Flower Pollination Resource Consolidation (MOH-FPRC) algorithm was developed. In this algorithm, Local Neighborhood Search (LNS) and Pareto optimisation strategies were combined with Clustering algorithm to avoid local trapping and address Cloud service providers conflicting objectives such as energy consumption and SLA violation. Lastly, Energy-Aware Multi-Cloud Flower Pollination Optimization (EAM-FPO) scheme was developed for distributed Multi-Cloud data center environment. In this scheme, Power Usage Effectiveness (PUE) and migration controller were utilised to obtain the optimal solution in a larger search space of the CC environment. The scheme was tested on MultiRecCloudSim simulator. Results of the simulation were compared with OEMACS, ACS-VMC, and EA-DP. The scheme produced outstanding performance improvement rate on the data center energy consumption by 20.5%, resource utilization by 23.9%, and SLA violation by 13.5%. The combined algorithms have reduced entrapment and maintaned balance between local and global search. Therefore, based on the findings the developed scheme has proven to be efficient in minimizing energy consumption while at the same time improving the data center resource allocation with minimum SLA violation

The Sciences of Data – Moving Towards a Comprehensive Systems Perspective

Data science’s rapid development in a dynamically growing data environment endows it with unique characteristics among scientific disciplines, juxtaposing challenges typically encountered in theoretical as well as empirical sciences. This raises questions as to the identification of the most pressing problems for data science, as well as to what constitutes its theoretical foundations. In this contribution, we first describe data science from the perspective of philosophy of science. We argue that the current mode of development of data science is adequately described by what we term the differentiational-expansionist mode. This leads us to conclude that data science concerns the acquisition of scientific theories relating to the application of methods, workflows and algorithms that generate value for users – which we term the integrative view. This definition emphasizes the interdependent nature of human and algorithmic elements in complex data workflows. We then offer four challenges for the future of the field. We conclude that since full control of entire data workflows is unfeasible, attention should be redirected towards the creation of an infrastructure by which data workflows will self-organize in a useful manner

The ecomics of ecosystems and biodiversity: scoping the scale

The G8 decided in March 2007 to initiate a “Review on the economics of biodiversity loss”, in the so called Potsdam Initiative: 'In a global study we will initiate the process of analysing the global economic benefit of biological diversity, the costs of the loss of biodiversity and the failure to take protective measures versus the costs of effective conservation. The study is being supported by the European Commission (together with the European Environmental Agency and in cooperation with the German Government. “The objective of the current study is to provide a coherent overview of existing scientific knowledge upon which to base the economics of the Review, and to propose a coherent global programme of scientific work, both for Phase 2 (consolidation) and to enable more robust future iterations of the Review beyond 2010.

Modern computing: Vision and challenges

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

Biologically-inspired double skin facades for hot climates: a parametric approach for performative design

La Biomimicry è una scienza applicata che studia le forme, i materiali, i sistemi e i processi naturali per individuare soluzioni applicabili anche a problemi umani. Tale scienza trova applicazione in molti campi, quali l’agricoltura, la medicina, l’ingegneria e l’architettura. Grazie ai progressi compiuti nella modellazione parametrica, ad oggi sono disponibili potenti strumenti che, oltre alla simulazione energetica, consentono di esplorare le potenzialità delle soluzioni tratte dal mondo naturale nella progettazione architettonica, superando i limiti della semplice imitazione della forma. Una delle maggiori sfide per gli architetti negli ultimi anni è la riduzione della domanda energetica del costruito. Per i climi caldi, le esigenze di ventilazione e raffrescamento sono pertanto fattori cruciali per migliorarne la prestazione energetica. La tesi di ricerca affronta il problema della progettazione e dell’efficienza energetica dell’involucro edilizio in contesti climatici caldi, quale l’Egitto. A tal fine, è stato definito e applicato un approccio progettuale biomimetico-computazionale, per studiare e analizzare i comportamenti adattivi di termoregolazione di vari organismi naturali. In particolare, il lavoro di ricerca esplora possibili soluzioni architettoniche, ispirate a caratteristiche biologiche, per l’involucro di un edificio per uffici, con l’obiettivo di ridurre la domanda energetica per il raffrescamento. L’involucro dell’edificio è stato modellato parametricamente utilizzando Grasshopper Visual Programming Language per Rhino 3D Modeller, applicando inoltre alcuni algoritmi evolutivi multi-obiettivo per ottimizzare la soluzione architettonica rispetto al duplice obiettivo di diminuire i carichi di raffrescamento e mantenere un buon livello di illuminazione naturale. In tal modo, la riduzione dei carichi di raffreddamento non comporta un incremento dei consumi elettrici per l'illuminazione artificiale. Le prestazioni termiche dell’edificio sono state valutate con il software EnergyPlus. La soluzione architettonica esplorata è una facciata a doppia pelle ispirata a vari principi della natura. Le prestazioni della soluzione proposta sono state confrontate con quelle di un edificio per uffici esistente a Il Cairo. Il modello dell’edificio è stato ricostruito sulla base di planimetrie e specifiche sui materiali presenti; inoltre la disponibilità di dati sui consumi energetici per il raffrescamento dell’edificio ha permesso di valutare l’accuratezza della prestazione energetica calcolata con il software di modellazione. La soluzione progettuale è stata comparate anche rispetto alle prestazioni di una tipica facciata a doppia pelle. Inoltre le prestazioni termiche calcolate con EnergyPlus sono state confrontate con quelle ottenute con software di simulazione fluidodinamica computazionale (CFD), più accurati nel calcolo delle facciate a doppia pelle. Tale comparazione ha permesso di identificare il grado di errore e l’appropriatezza dell’uso di EnergyPlus nelle fasi iniziali della progettazione. La facciata a doppia pelle proposta consente una diminuzione della domanda di raffrescamento fino al 13,4%, migliorando al tempo stesso il livello di illuminazione naturale, che spesso costituisce uno dei maggiori limiti per l’applicazione di tale sistema. La ricerca termina con una sintesi dei risultati ottenuti e una valutazione complessiva del processo di progettazione presentato, degli strumenti di progettazione/simulazione utilizzati e delle prestazioni dell’involucro proposto, discutendone vantaggi e limiti. Sulla base delle sperimentazioni e dei risultati conseguiti, sono state individuate linee guida e raccomandazioni per la progettazione delle facciate a doppia pelle nei climi caldi. Inoltre viene fornita una matrice che raccoglie tutte le idee biomimetiche esplorate e analizzate, che rappresenta una mini-banca dati per architetti o designer interessati a questo approccio progettuale nell’affrontare i problemi di termoregolazione del costruito. Infine, la differenza di accuratezza tra i risultati di EnergyPlus e quelli dello strumento CFD è risultata trascurabile.Biomimicry is an applied science that derives inspiration for solutions to human problems through the study of natural designs, materials, structures and processes. Many fields of study benefit from biomimetic inspirations, such as agriculture, medicine, engineering, and architecture. Technological advances in parametric and computational design software in addition to environmental simulation means offer very useful tools in order to explore the potential of nature’s inspirations in architectural designs that does not just mimic shapes and forms. Energy efficiency is one of the major and growing concerns facing architects. Cooling and ventilation needs are critical factors that affect energy efficiency especially in hot climates. This thesis addresses the problem of designing building skins that are energy efficient in the context of hot climates such as that in Egypt. The research attempts to define and apply a biomimetic-computational design approach to study and analyse natural organisms in terms of their behaviour regarding thermoregulation. Aiming to decrease cooling loads, the research explores possible architectural solutions for a biologically inspired skin system for office buildings. The building’s skin is parametrically designed using Grasshopper Visual Programming Language for Rhino 3D Modeller, and it is optimised using multi-objective evolutionary algorithms which are particularly important in the attempt of finding a range of solutions that reduce cooling loads while maintaining daylight needs. Consequently, the reduction in cooling loads should not be at the expense of increased energy consumption in artificial lighting. Simulations regarding the thermal performance were performed using EnergyPlus. A Double-Skin Façade (DSF) is proposed based on inspirations from nature. In order to evaluate the performance of the proposal, it is compared to the performance of the skin of an existing office building in Cairo acting as a reference case. Data regarding the reference case such as the building drawings, material specifications and annual cooling consumption were obtained in order to build its digital model and assess its accuracy. The proposed design is also evaluated by comparing it to a typical flat DSF. The obtained results regarding the thermal performance of the proposed building skin are verified by comparing them to results of more accurate simulations performed using Computational Fluid Dynamics (CFD). The aim is to know the degree of error as well as the appropriateness of using EnergyPlus for geometrically-complex DSFs in early design phases when CFD is not practical. The proposed DSF was able to decrease cooling loads by up to 13.4% while improving daylight performance at the same time which is often one of the main challenges of using DSFs. The research criticises the presented design approach as a whole, the design/simulation tools used and the performance of the proposed skin discussing their benefits and limitations. Based on the design experimentation and results, general guidelines and recommendations for DSF design in hot climates are presented. Additionally, the research presents a compiled matrix of the biomimetic ideas explored and analysed in order to serve as a mini-data bank for architects or designers interested in this design approach in addressing thermoregulation problems. Finally, the comparison between EnergyPlus and CFD software results showed minor differences