Software-Defined Cloud Computing: Architectural Elements and Open Challenges

The variety of existing cloud services creates a challenge for service providers to enforce reasonable Software Level Agreements (SLA) stating the Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid such penalties at the same time that the infrastructure operates with minimum energy and resource wastage, constant monitoring and adaptation of the infrastructure is needed. We refer to Software-Defined Cloud Computing, or simply Software-Defined Clouds (SDC), as an approach for automating the process of optimal cloud configuration by extending virtualization concept to all resources in a data center. An SDC enables easy reconfiguration and adaptation of physical resources in a cloud infrastructure, to better accommodate the demand on QoS through a software that can describe and manage various aspects comprising the cloud environment. In this paper, we present an architecture for SDCs on data centers with emphasis on mobile cloud applications. We present an evaluation, showcasing the potential of SDC in two use cases-QoS-aware bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi, Indi

Efficient Resource Management for Cloud Computing Environments

Cloud computing has recently gained popularity as a cost-effective model for hosting and delivering services over the Internet. In a cloud computing environment, a cloud provider packages its physical resources in data centers into virtual resources and offers them to service providers using a pay-as-you-go pricing model. Meanwhile, a service provider uses the rented virtual resources to host its services. This large-scale multi-tenant architecture of cloud computing systems raises key challenges regarding how data centers resources should be controlled and managed by both service and cloud providers. This thesis addresses several key challenges pertaining to resource management in cloud environments. From the perspective of service providers, we address the problem of selecting appropriate data centers for service hosting with consideration of resource price, service quality as well as dynamic reconfiguration costs. From the perspective of cloud providers, as it has been reported that workload in real data centers can be typically divided into server-based applications and MapReduce applications with different performance and scheduling criteria, we provide separate resource management solutions for each type of workloads. For server-based applications, we provide a dynamic capacity provisioning scheme that dynamically adjusts the number of active servers to achieve the best trade-off between energy savings and scheduling delay, while considering heterogeneous resource characteristics of both workload and physical machines. For MapReduce applications, we first analyzed task run-time resource consumption of a large variety of MapReduce jobs and discovered it can vary significantly over-time, depending on the phase the task is currently executing. We then present a novel scheduling algorithm that controls task execution at the level of phases with the aim of improving both job running time and resource utilization. Through detailed simulations and experiments using real cloud clusters, we have found our proposed solutions achieve substantial gain compared to current state-of-art resource management solutions, and therefore have strong implications in the design of real cloud resource management systems in practice

Efficient Resource Management for Cloud Computing Environments

Cloud computing has recently gained popularity as a cost-effective model for hosting and delivering services over the Internet. In a cloud computing environment, a cloud provider packages its physical resources in data centers into virtual resources and offers them to service providers using a pay-as-you-go pricing model. Meanwhile, a service provider uses the rented virtual resources to host its services. This large-scale multi-tenant architecture of cloud computing systems raises key challenges regarding how data centers resources should be controlled and managed by both service and cloud providers. This thesis addresses several key challenges pertaining to resource management in cloud environments. From the perspective of service providers, we address the problem of selecting appropriate data centers for service hosting with consideration of resource price, service quality as well as dynamic reconfiguration costs. From the perspective of cloud providers, as it has been reported that workload in real data centers can be typically divided into server-based applications and MapReduce applications with different performance and scheduling criteria, we provide separate resource management solutions for each type of workloads. For server-based applications, we provide a dynamic capacity provisioning scheme that dynamically adjusts the number of active servers to achieve the best trade-off between energy savings and scheduling delay, while considering heterogeneous resource characteristics of both workload and physical machines. For MapReduce applications, we first analyzed task run-time resource consumption of a large variety of MapReduce jobs and discovered it can vary significantly over-time, depending on the phase the task is currently executing. We then present a novel scheduling algorithm that controls task execution at the level of phases with the aim of improving both job running time and resource utilization. Through detailed simulations and experiments using real cloud clusters, we have found our proposed solutions achieve substantial gain compared to current state-of-art resource management solutions, and therefore have strong implications in the design of real cloud resource management systems in practice

Cost-Effective Resource Provisioning for MapReduce in a Cloud

This paper presents a new MapReduce cloud service model, Cura, for provisioning cost-effective MapReduce services in a cloud. In contrast to existing MapReduce cloud services such as a generic compute cloud or a dedicated MapReduce cloud, Cura has a number of unique benefits. First, Cura is designed to provide a cost-effective solution to efficiently handle MapReduce production workloads that have a significant amount of interactive jobs. Second, unlike existing services that require customers to decide the resources to be used for the jobs, Cura leverages MapReduce profiling to automatically create the best cluster configuration for the jobs. While the existing models allow only a per-job resource optimization for the jobs, Cura implements a globally efficient resource allocation scheme that significantly reduces the resource usage cost in the cloud. Third, Cura leverages unique optimization opportunities when dealing with workloads that can withstand some slack. By effectively multiplexing the available cloud resources among the jobs based on the job requirements, Cura achieves significantly lower resource usage costs for the jobs. Cura's core resource management schemes include cost-aware resource provisioning, VM-aware scheduling and online virtual machine reconfiguration. Our experimental results using Facebook-like workload traces show that our techniques lead to more than 80 percent reduction in the cloud compute infrastructure cost with upto 65 percent reduction in job response times

Processamento de eventos complexos como serviço em ambientes multi-nuvem

Orientadores: Luiz Fernando Bittencourt, Miriam Akemi Manabe CapretzTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O surgimento das tecnologias de dispositivos móveis e da Internet das Coisas, combinada com avanços das tecnologias Web, criou um novo mundo de Big Data em que o volume e a velocidade da geração de dados atingiu uma escala sem precedentes. Por ser uma tecnologia criada para processar fluxos contínuos de dados, o Processamento de Eventos Complexos (CEP, do inglês Complex Event Processing) tem sido frequentemente associado a Big Data e aplicado como uma ferramenta para obter informações em tempo real. Todavia, apesar desta onda de interesse, o mercado de CEP ainda é dominado por soluções proprietárias que requerem grandes investimentos para sua aquisição e não proveem a flexibilidade que os usuários necessitam. Como alternativa, algumas empresas adotam soluções de baixo nível que demandam intenso treinamento técnico e possuem alto custo operacional. A fim de solucionar esses problemas, esta pesquisa propõe a criação de um sistema de CEP que pode ser oferecido como serviço e usado através da Internet. Um sistema de CEP como Serviço (CEPaaS, do inglês CEP as a Service) oferece aos usuários as funcionalidades de CEP aliadas às vantagens do modelo de serviços, tais como redução do investimento inicial e baixo custo de manutenção. No entanto, a criação de tal serviço envolve inúmeros desafios que não são abordados no atual estado da arte de CEP. Em especial, esta pesquisa propõe soluções para três problemas em aberto que existem neste contexto. Em primeiro lugar, para o problema de entender e reusar a enorme variedade de procedimentos para gerência de sistemas CEP, esta pesquisa propõe o formalismo Reescrita de Grafos com Atributos para Gerência de Processamento de Eventos Complexos (AGeCEP, do inglês Attributed Graph Rewriting for Complex Event Processing Management). Este formalismo inclui modelos para consultas CEP e transformações de consultas que são independentes de tecnologia e linguagem. Em segundo lugar, para o problema de avaliar estratégias de gerência e processamento de consultas CEP, esta pesquisa apresenta CEPSim, um simulador de sistemas CEP baseado em nuvem. Por fim, esta pesquisa também descreve um sistema CEPaaS fundamentado em ambientes multi-nuvem, sistemas de gerência de contêineres e um design multiusuário baseado em AGeCEP. Para demonstrar sua viabilidade, o formalismo AGeCEP foi usado para projetar um gerente autônomo e um conjunto de políticas de auto-gerenciamento para sistemas CEP. Além disso, o simulador CEPSim foi minuciosamente avaliado através de experimentos que demonstram sua capacidade de simular sistemas CEP com acurácia e baixo custo adicional de processamento. Por fim, experimentos adicionais validaram o sistema CEPaaS e demonstraram que o objetivo de oferecer funcionalidades CEP como um serviço escalável e tolerante a falhas foi atingido. Em conjunto, esses resultados confirmam que esta pesquisa avança significantemente o estado da arte e também oferece novas ferramentas e metodologias que podem ser aplicadas à pesquisa em CEPAbstract: The rise of mobile technologies and the Internet of Things, combined with advances in Web technologies, have created a new Big Data world in which the volume and velocity of data generation have achieved an unprecedented scale. As a technology created to process continuous streams of data, Complex Event Processing (CEP) has been often related to Big Data and used as a tool to obtain real-time insights. However, despite this recent surge of interest, the CEP market is still dominated by solutions that are costly and inflexible or too low-level and hard to operate. To address these problems, this research proposes the creation of a CEP system that can be offered as a service and used over the Internet. Such a CEP as a Service (CEPaaS) system would give its users CEP functionalities associated with the advantages of the services model, such as no up-front investment and low maintenance cost. Nevertheless, creating such a service involves challenges that are not addressed by current CEP systems. This research proposes solutions for three open problems that exist in this context. First, to address the problem of understanding and reusing existing CEP management procedures, this research introduces the Attributed Graph Rewriting for Complex Event Processing Management (AGeCEP) formalism as a technology- and language-agnostic representation of queries and their reconfigurations. Second, to address the problem of evaluating CEP query management and processing strategies, this research introduces CEPSim, a simulator of cloud-based CEP systems. Finally, this research also introduces a CEPaaS system based on a multi-cloud architecture, container management systems, and an AGeCEP-based multi-tenant design. To demonstrate its feasibility, AGeCEP was used to design an autonomic manager and a selected set of self-management policies. Moreover, CEPSim was thoroughly evaluated by experiments that showed it can simulate existing systems with accuracy and low execution overhead. Finally, additional experiments validated the CEPaaS system and demonstrated it achieves the goal of offering CEP functionalities as a scalable and fault-tolerant service. In tandem, these results confirm this research significantly advances the CEP state of the art and provides novel tools and methodologies that can be applied to CEP researchDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação140920/2012-9CNP

Cost Function based Event Triggered Model Predictive Controllers - Application to Big Data Cloud Services

International audienceHigh rate cluster reconfigurations is a costly issue in Big Data Cloud services. Current control solutions manage to scale the cluster according to the workload, however they do not try to minimize the number of system reconfigurations. Event-based control is known to reduce the number of control updates typically by waiting for the system states to degrade below a given threshold before reacting. However, computer science systems often have exogenous inputs (such as clients connections) with delayed impacts that can enable to anticipate states degradation. In this paper, a novel event-triggered approach is proposed. This triggering mechanism relies on a Model Predictive Controller and is defined upon the value of the optimal cost function instead of the state or output error. This controller reduces the number of control changes, in the normal operation mode, through constraints in the MPC formulation but also assures a very reactive behavior to changes of exogenous inputs. This novel control approach is evaluated using a model validated on a real Big Data system. The controller efficiently scales the cluster according to specifications, meanwhile reducing its reconfigurations

Cross-Layer Rapid Prototyping and Synthesis of Application-Specific and Reconfigurable Many-accelerator Platforms

Technological advances of recent years laid the foundation consolidation of informatisationof society, impacting on economic, political, cultural and socialdimensions. At the peak of this realization, today, more and more everydaydevices are connected to the web, giving the term ”Internet of Things”. The futureholds the full connection and interaction of IT and communications systemsto the natural world, delimiting the transition to natural cyber systems and offeringmeta-services in the physical world, such as personalized medical care, autonomoustransportation, smart energy cities etc. . Outlining the necessities of this dynamicallyevolving market, computer engineers are required to implement computingplatforms that incorporate both increased systemic complexity and also cover awide range of meta-characteristics, such as the cost and design time, reliabilityand reuse, which are prescribed by a conflicting set of functional, technical andconstruction constraints. This thesis aims to address these design challenges bydeveloping methodologies and hardware/software co-design tools that enable therapid implementation and efficient synthesis of architectural solutions, which specifyoperating meta-features required by the modern market. Specifically, this thesispresents a) methodologies to accelerate the design flow for both reconfigurableand application-specific architectures, b) coarse-grain heterogeneous architecturaltemplates for processing and communication acceleration and c) efficient multiobjectivesynthesis techniques both at high abstraction level of programming andphysical silicon level.Regarding to the acceleration of the design flow, the proposed methodologyemploys virtual platforms in order to hide architectural details and drastically reducesimulation time. An extension of this framework introduces the systemicco-simulation using reconfigurable acceleration platforms as co-emulation intermediateplatforms. Thus, the development cycle of a hardware/software productis accelerated by moving from a vertical serial flow to a circular interactive loop.Moreover the simulation capabilities are enriched with efficient detection and correctiontechniques of design errors, as well as control methods of performancemetrics of the system according to the desired specifications, during all phasesof the system development. In orthogonal correlation with the aforementionedmethodological framework, a new architectural template is proposed, aiming atbridging the gap between design complexity and technological productivity usingspecialized hardware accelerators in heterogeneous systems-on-chip and networkon-chip platforms. It is presented a novel co-design methodology for the hardwareaccelerators and their respective programming software, including the tasks allocationto the available resources of the system/network. The introduced frameworkprovides implementation techniques for the accelerators, using either conventionalprogramming flows with hardware description language or abstract programmingmodel flows, using techniques from high-level synthesis. In any case, it is providedthe option of systemic measures optimization, such as the processing speed,the throughput, the reliability, the power consumption and the design silicon area.Finally, on addressing the increased complexity in design tools of reconfigurablesystems, there are proposed novel multi-objective optimization evolutionary algo-rithms which exploit the modern multicore processors and the coarse-grain natureof multithreaded programming environments (e.g. OpenMP) in order to reduce theplacement time, while by simultaneously grouping the applications based on theirintrinsic characteristics, the effectively explore the design space effectively.The efficiency of the proposed architectural templates, design tools and methodologyflows is evaluated in relation to the existing edge solutions with applicationsfrom typical computing domains, such as digital signal processing, multimedia andarithmetic complexity, as well as from systemic heterogeneous environments, suchas a computer vision system for autonomous robotic space navigation and manyacceleratorsystems for HPC and workstations/datacenters. The results strengthenthe belief of the author, that this thesis provides competitive expertise to addresscomplex modern - and projected future - design challenges.Οι τεχνολογικές εξελίξεις των τελευταίων ετών έθεσαν τα θεμέλια εδραίωσης της πληροφοριοποίησης της κοινωνίας, επιδρώντας σε οικονομικές,πολιτικές, πολιτιστικές και κοινωνικές διαστάσεις. Στο απόγειο αυτής τη ςπραγμάτωσης, σήμερα, ολοένα και περισσότερες καθημερινές συσκευές συνδέονται στο παγκόσμιο ιστό, αποδίδοντας τον όρο «Ίντερνετ των πραγμάτων».Το μέλλον επιφυλάσσει την πλήρη σύνδεση και αλληλεπίδραση των συστημάτων πληροφορικής και επικοινωνιών με τον φυσικό κόσμο, οριοθετώντας τη μετάβαση στα συστήματα φυσικού κυβερνοχώρου και προσφέροντας μεταυπηρεσίες στον φυσικό κόσμο όπως προσωποποιημένη ιατρική περίθαλψη, αυτόνομες μετακινήσεις, έξυπνες ενεργειακά πόλεις κ.α. . Σκιαγραφώντας τις ανάγκες αυτής της δυναμικά εξελισσόμενης αγοράς, οι μηχανικοί υπολογιστών καλούνται να υλοποιήσουν υπολογιστικές πλατφόρμες που αφενός ενσωματώνουν αυξημένη συστημική πολυπλοκότητα και αφετέρου καλύπτουν ένα ευρύ φάσμα μεταχαρακτηριστικών, όπως λ.χ. το κόστος σχεδιασμού, ο χρόνος σχεδιασμού, η αξιοπιστία και η επαναχρησιμοποίηση, τα οποία προδιαγράφονται από ένα αντικρουόμενο σύνολο λειτουργικών, τεχνολογικών και κατασκευαστικών περιορισμών. Η παρούσα διατριβή στοχεύει στην αντιμετώπιση των παραπάνω σχεδιαστικών προκλήσεων, μέσω της ανάπτυξης μεθοδολογιών και εργαλείων συνσχεδίασης υλικού/λογισμικού που επιτρέπουν την ταχεία υλοποίηση καθώς και την αποδοτική σύνθεση αρχιτεκτονικών λύσεων, οι οποίες προδιαγράφουν τα μετα-χαρακτηριστικά λειτουργίας που απαιτεί η σύγχρονη αγορά. Συγκεκριμένα, στα πλαίσια αυτής της διατριβής, παρουσιάζονται α) μεθοδολογίες επιτάχυνσης της ροής σχεδιασμού τόσο για επαναδιαμορφούμενες όσο και για εξειδικευμένες αρχιτεκτονικές, β) ετερογενή αδρομερή αρχιτεκτονικά πρότυπα επιτάχυνσης επεξεργασίας και επικοινωνίας και γ) αποδοτικές τεχνικές πολυκριτηριακής σύνθεσης τόσο σε υψηλό αφαιρετικό επίπεδο προγραμματισμού,όσο και σε φυσικό επίπεδο πυριτίου.Αναφορικά προς την επιτάχυνση της ροής σχεδιασμού, προτείνεται μια μεθοδολογία που χρησιμοποιεί εικονικές πλατφόρμες, οι οποίες αφαιρώντας τις αρχιτεκτονικές λεπτομέρειες καταφέρνουν να μειώσουν σημαντικά το χρόνο εξομοίωσης. Παράλληλα, εισηγείται η συστημική συν-εξομοίωση με τη χρήση επαναδιαμορφούμενων πλατφορμών, ως μέσων επιτάχυνσης. Με αυτόν τον τρόπο, ο κύκλος ανάπτυξης ενός προϊόντος υλικού, μετατεθειμένος από την κάθετη σειριακή ροή σε έναν κυκλικό αλληλεπιδραστικό βρόγχο, καθίσταται ταχύτερος, ενώ οι δυνατότητες προσομοίωσης εμπλουτίζονται με αποδοτικότερες μεθόδους εντοπισμού και διόρθωσης σχεδιαστικών σφαλμάτων, καθώς και μεθόδους ελέγχου των μετρικών απόδοσης του συστήματος σε σχέση με τις επιθυμητές προδιαγραφές, σε όλες τις φάσεις ανάπτυξης του συστήματος. Σε ορθογώνια συνάφεια με το προαναφερθέν μεθοδολογικό πλαίσιο, προτείνονται νέα αρχιτεκτονικά πρότυπα που στοχεύουν στη γεφύρωση του χάσματος μεταξύ της σχεδιαστικής πολυπλοκότητας και της τεχνολογικής παραγωγικότητας, με τη χρήση συστημάτων εξειδικευμένων επιταχυντών υλικού σε ετερογενή συστήματα-σε-ψηφίδα καθώς και δίκτυα-σε-ψηφίδα. Παρουσιάζεται κατάλληλη μεθοδολογία συν-σχεδίασης των επιταχυντών υλικού και του λογισμικού προκειμένου να αποφασισθεί η κατανομή των εργασιών στους διαθέσιμους πόρους του συστήματος/δικτύου. Το μεθοδολογικό πλαίσιο προβλέπει την υλοποίηση των επιταχυντών είτε με συμβατικές μεθόδους προγραμματισμού σε γλώσσα περιγραφής υλικού είτε με αφαιρετικό προγραμματιστικό μοντέλο με τη χρήση τεχνικών υψηλού επιπέδου σύνθεσης. Σε κάθε περίπτωση, δίδεται η δυνατότητα στο σχεδιαστή για βελτιστοποίηση συστημικών μετρικών, όπως η ταχύτητα επεξεργασίας, η ρυθμαπόδοση, η αξιοπιστία, η κατανάλωση ενέργειας και η επιφάνεια πυριτίου του σχεδιασμού. Τέλος, προκειμένου να αντιμετωπισθεί η αυξημένη πολυπλοκότητα στα σχεδιαστικά εργαλεία επαναδιαμορφούμενων συστημάτων, προτείνονται νέοι εξελικτικοί αλγόριθμοι πολυκριτηριακής βελτιστοποίησης, οι οποίοι εκμεταλλευόμενοι τους σύγχρονους πολυπύρηνους επεξεργαστές και την αδρομερή φύση των πολυνηματικών περιβαλλόντων προγραμματισμού (π.χ. OpenMP), μειώνουν το χρόνο επίλυσης του προβλήματος της τοποθέτησης των λογικών πόρων σε φυσικούς,ενώ ταυτόχρονα, ομαδοποιώντας τις εφαρμογές βάση των εγγενών χαρακτηριστικών τους, διερευνούν αποτελεσματικότερα το χώρο σχεδίασης.Η αποδοτικότητά των προτεινόμενων αρχιτεκτονικών προτύπων και μεθοδολογιών επαληθεύτηκε σε σχέση με τις υφιστάμενες λύσεις αιχμής τόσο σε αυτοτελής εφαρμογές, όπως η ψηφιακή επεξεργασία σήματος, τα πολυμέσα και τα προβλήματα αριθμητικής πολυπλοκότητας, καθώς και σε συστημικά ετερογενή περιβάλλοντα, όπως ένα σύστημα όρασης υπολογιστών για αυτόνομα διαστημικά ρομποτικά οχήματα και ένα σύστημα πολλαπλών επιταχυντών υλικού για σταθμούς εργασίας και κέντρα δεδομένων, στοχεύοντας εφαρμογές υψηλής υπολογιστικής απόδοσης (HPC). Τα αποτελέσματα ενισχύουν την πεποίθηση του γράφοντα, ότι η παρούσα διατριβή παρέχει ανταγωνιστική τεχνογνωσία για την αντιμετώπιση των πολύπλοκων σύγχρονων και προβλεπόμενα μελλοντικών σχεδιαστικών προκλήσεων