Cloud Orchestration Research Articles

Orchestrated Platform for Cyber‐Physical Systems

One of the main driving forces in the era of cyber‐physical systems (CPSs) is the introduction of massive sensor networks (or nowadays various Internet of things solutions as well) into manufacturing processes, connected cars, precision agriculture, and so on. Therefore, large amounts of sensor data have to be ingested at the server side in order to generate and make the “twin digital model” or virtual factory of the existing physical processes for (among others) predictive simulation and scheduling purposes usable. In this paper, we focus on our ultimate goal, a novel software container‐based approach with cloud agnostic orchestration facilities that enable the system operators in the industry to create and manage scalable, virtual IT platforms on‐demand for these two typical major pillars of CPS: (1) server‐side (i.e., back‐end) framework for sensor networks and (2) configurable simulation tool for predicting the behavior of manufacturing systems. The paper discusses the scalability of the applied discrete‐event simulation tool and the layered back‐end framework starting from simple virtual machine‐level to sophisticated multilevel autoscaling use case scenario. The presented achievements and evaluations leverage on (among others) the synergy of the existing EasySim simulator, our new CQueue software container manager, the continuously developed Occopus cloud orchestrator tool, and the latest version of the evolving MiCADO framework for integrating such tools into a unified platform.

Time Complexity of an Distributed Algorithm for Load Balancing of Microservice-oriented Applications in the Cloud

Microservice architecture is a relatively new cloud application design pattern. Each microservice has a single responsibility in terms of functional requirement, and that can be managed independently from other microservices. This is done using automated cloud orchestration systems. In this paper we analyze the time complexity of an simple swarm-like decentralized load balancing algorithm for microservices running inside OpenVZ virtualization containers. We show that it can offer performance improvements with respect to the existing centralized container orchestration systems.

Occopus: a Multi-Cloud Orchestrator to Deploy and Manage Complex Scientific Infrastructures

This paper presents Occopus, an open-source cloud orchestration and management framework for heterogeneous multi-cloud platforms. Occopus provides a language to specify infrastructure descriptions and node definitions based on which Occopus can automatically deploy and maintain the specified virtual infrastructures in the target clouds. The paper introduces the required structure of the infrastructure descriptions and node definitions in an informal way and shows two use cases (Hadoop cluster and MICADO framework) how Occopus can be used to deploy complex virtual infrastructures. The paper also explains the architecture and implementation aspects of Occopus and describes its main distinguishing features compared to other cloud orchestrator frameworks.

Fault-tolerance analyzer: A middle layer for pre-provision testing in OpenStack

OpenStack is arguably the most popular open-source cloud orchestration software available today. Its user-base spans from large corporations and large scale service providers to SMEs. OpenStack manages infrastructure resources e.g. compute, storage and networking. While customers get a fully functional cloud, an incumbent fault-tolerance analysis and suggestion system is absent from this otherwise robust cloud management system. In this work, we demonstrate a system for automated fault-tolerance (FT) analysis of network applications hosted on OpenStack. Faults are modeled by random server and/or service shutdowns. Aim of the FT Analyzer is to equip cloud tenants with information to determine optimum configuration for their applications before firing up the service. FT Analyzer helps tenants maintain maximum up-time for services and data and preemptively tests the virtual network based applications for any issues that can have a negative impact on performance in post deployment scenario.

MiCADO—Microservice-based Cloud Application-level Dynamic Orchestrator

Various scientific and commercial applications require automated scalability and orchestration on cloud computing resources. However, extending applications with such automated scalability on an individual basis is not feasible. This paper investigates how such automated orchestration can be added to cloud applications without major reengineering of the application code. We suggest a generic architecture for an application level cloud orchestration framework, called MiCADO that supports various application scenarios on multiple heterogeneous federated clouds. Besides the generic architecture description, the paper also presents the first MiCADO reference implementation, and explains how the scalability of the Data Avenue service that is applied for data transfer in WS-PGRADE/gUSE based science gateways, can be improved. Performance evaluation of the implemented scalability based on up and downscaling experiments is presented.

Angleško-slovenski glosar virtualizacijske terminologije: usklajevanje tehničnega, terminološkega in organizacijskega dela

With the growing adoption of using virtual machines over physical hosts as a form of resource consolidation, The English-Slovene Glossary of Virtualization-related Terms encompassing management of virtual machines, cloud orchestration and data storage seemed like the next logical step.The Glossary of Virtualization-related Terms has been translated into Slovene and reviewed by experts in the fields of cloud computing, virtualization technologies and linguists. Close to 6000 terms had been localized for the Slovene market, using the advanced version of Poedit application – the editor for translating apps and websites. PoEdit automatically displays translation equivalents either from its own base (built-in translation memory) or from the base of previously translated words and phrases, which had been created and offered as opensource by other users. Based on these, it makes suggestions and, over time, learns enough to fill in frequently used strings. The translated text was then imported into its original page location – the Graphic User Interface (visible on buttons on the dashboard) of the customized ManageIQ Enterprise Virtualization Manager (EVM) software used by administrators of public and private clouds. Hence the main criterion was brevity and precision in transfering meaning across languages. This is where we encountered most problems – neologisms and existing words that acquire new meaning as a result of rapid development of virtualization technology. To avoid merely adding a suffix while the core of the word remains the same in Slovene (e.g. tenant, tenant-ov) and also to encourage further additions, comments or suggested changes the glossary has been made available on Wikipedia, the online encyclopedia.

Enabling End-to-End Orchestration of Multi-Cloud Applications

The orchestration of application components across heterogeneous cloud providers is a problem that has been tackled using various approaches, some of which led to the creation of cloud orchestration and management standards, such as TOSCA and CAMP. Standardization is a definitive method of providing an end-to-end solution capable of defining, deploying, and managing applications and their components across heterogeneous cloud providers. TOSCA and CAMP, however, perform different functions with regard to cloud applications. TOSCA is focused primarily on topology modeling and orchestration, whereas CAMP is focused on deployment and management of applications. This paper presents a novel solution that not only involves the combination of the emerging standards TOSCA and CAMP, but also introduces extensions to CAMP to allow for multi-cloud application orchestration through the use of declarative policies. Extensions to the CAMP platform are also made, which brings the standards closer together to enable a seamless integration. Our proposal provides an end-to-end cloud orchestration solution that supports a cloud application modeling and deployment process, allowing a cloud application to span and be deployed over multiple clouds. The feasibility and the benefit of our approach are demonstrated in our validation study.

Profiling Energy Efficiency and Data Communications for Mobile Internet of Things

This paper proposes a novel power management solution for resource-constrained devices in the context of Internet of Things (IoT). We focus on smartphones in the IoT, as they are getting increasingly popular and equipped with strong sensing capabilities. Smartphones have complex and asynchronous power consumption incurred by heterogeneous components including their on-board sensors. Their interaction with the cloud allows them to offload computation tasks and access remote data storage. In this work, we aim at monitoring the power consumption behaviours of the smartphones, profiling both individual applications and the system as a whole, to make better decisions in power management. We design a cloud orchestration architecture as an epic predictor of behaviours of smart devices by extracting their application characteristics and resource utilization. We design and implement this architecture to perform energy profiling and data analysis on massive data logs. This cloud orchestration architecture coordinates a number of cloud-based services and supports dynamic workflows between service components, which can reduce energy consumption in the energy profiling process itself. Experimental results showed that small portion of applications dominate the energy consumption of smartphones. Heuristic profiling can effectively reduce energy consumption in data logging and communications without scarifying the accuracy of power monitoring.

Managing Workflows on top of a Cloud Computing Orchestrator for using heterogeneous environments on e-Science

Scientific workflows (SWFs) are widely used to model processes in e-Science. SWFs are executed by means of workflow management systems (WMSs), which orchestrate the workload on top of computing infrastructures. The advent of cloud computing infrastructures has opened the door of using on-demand infrastructures to complement or even replace local infrastructures. However, new issues have arisen, such as the integration of hybrid resources or the compromise between infrastructure reutilisation and elasticity. In this article, we present an ad hoc solution for managing workflows exploiting the capabilities of cloud orchestrators to deploy resources on demand according to the workload and to combine heterogeneous cloud providers (such as on-premise clouds and public clouds) and traditional infrastructures (clusters) to minimise costs and response time. The work does not propose yet another WMS but demonstrates the benefits of the integration of cloud orchestration when running complex workflows. The article shows several configuration experiments from a realistic comparative genomics workflow called Orthosearch, to migrate memory-intensive workload to public infrastructures while keeping other blocks of the experiment running locally. The article computes running time and cost suggesting best practices.

E-eco: Performance-aware energy-efficient cloud data center orchestration

The high energy consumption of data centers has been a recurring issue in recent research. In cloud environments, several techniques are being used that aim for energy efficiency, ranging from scaling the processors frequency, to the use of sleep states during idle periods and the consolidation of virtual machines. Although these techniques enable a reduction in power consumption, they usually impact application performance. In this paper, we present an orchestration of different energy-savings techniques in order to improve the trade-off between energy consumption and application performance. To this end, we implemented the Energy-Efficient Cloud Orchestrator - e-eco - a management system that acts along with the cloud load balancer deciding which technique to apply during execution. To evaluate e-eco, tests were carried out in a real environment using scale-out applications on a dynamic cloud infrastructure, taking into account transactions per second as a performance metric. In addition to the empirical experiments, we also analyzed the scalability of our approach with an enhanced version of the CloudSim simulator. Results of our evaluations demonstrated that e-eco is able to reduce energy consumption up to 25% compared to power-agnostic approaches at a cost of only 6% of extra SLA violations. When compared to existing power-aware approaches, e-eco achieved the best trade-off between performance and energy-savings. These results showed that our orchestration approach showed a better balance in regard to a more energy-efficient data center with smaller impact on application performance when compared with other works presented in the literature.

Managing cloud via Smart Cloud Engine and Knowledge Base

Complexity of cloud infrastructures needs models and tools for process management, configuration, scaling, elastic computing and cloud resource health control. This paper presents a Smart Cloud Engine and solution based on a Knowledge Base, KB, with the aim of modeling cloud resources, Service Level Agreements and their evolutions, and enabling the reasoning on structures by implementing strategies of efficient smart cloud management and intelligence. The solution proposed provides formal verification and intelligence tools for cloud control. It can be easily integrated with a large range of cloud configuration manager, cloud orchestrator, and monitoring tools, since the connections with these tools are performed by using REST calls and XML files. The proposed solution has been validated in the context of large ICARO Cloud project and in the cloud facility of a national cloud service provider. Some data resulting from the validation phases have been reported and are referring to the dynamic management of real ECLAP social network http://www.eclap.eu.

MADONA: a method for automated provisioning of cloud-based component-oriented business applications

Service-oriented computing and cloud computing offer many opportunities for developing and deploying applications. In this paper, we propose and describe a component-oriented method for automated provisioning of cloud business applications. The method covers the whole application's lifecycle and is based on cloud orchestration tools that manage the deployment and dependencies of supplied components. We aim to reduce the necessary technical knowledge for provisioning component-oriented cloud applications. To this end, we extend Linked Unified Service Description Language to describe services for matching user's requirements. We adopt a real case study to show the feasibility of the method.

Smart Cloud Engine and Solution Based on Knowledge Base

Abstract Complexity of cloud infrastructures needs models and tools for process management, configuration, scaling, elastic computing and healthiness control. This paper presents a Smart Cloud solution based on a Knowledge Base, KB, with the aim of modeling cloud resources, Service Level Agreements and their evolution, and enabling the reasoning on structures by implementing strategies of efficient smart cloud management and intelligence. The solution proposed provides formal verification tools and intelligence for cloud control. It can be easily integrated with any cloud configuration manager, cloud orchestrator, and monitoring tool, since the connections with these tools are performed by using REST calls and XML files. It has been validated in the large ICARO Cloud project with a national cloud service provider.

Beyond Mere Application Structure Thoughts on the Future of Cloud Orchestration Tools

Abstract Managing cloud applications running on IaaS is complicated and error prone. This is why DevOps tools and application description languages have been emerging. While these tools and languages enable the user to define the application and communication structure based on application components, they lack the possibility to define sophisticated communication patterns including the wiring on instance level. This paper details these shortcomings and presents approaches to overcome them. In particular, they we propose (i) adding boundaries to wiring specifications and (ii) introducing a higher-level abstraction—called facet —on top of the application. The combination of both concepts allows specifying wiring on basis of logical units and their relations. Hence, the concepts overcome general wiring problems that currently exist in cloud orchestration tools. In addition to that, the introduction of facets improves the re-use of components across di ff erent applications.

Orchestrating Hybrid Cloud Deployment: An Overview

Balancing enterprise control over cloud data with hybrid cloud benefits will increasingly require cloud orchestration. Reaping full hybrid cloud benefits requires increased organizational focus on security and control. But as more clouds come into play, each with specific offerings and rules, implementing these controls and coordinating management over different environments can become burdensome. The cloud orchestration framework we propose can both facilitate the hybrid cloud adoption process and help enterprises establish centralized control over multiple clouds.

The Virtual Computing Lab (VCL)

In this paper, we describe the Virtual Computing Lab (VCL) with its main features and services. Also, we introduce the recent advances of the VCL system and its usage in research and education. The VCL is a cloud computing system that has been optimized for the educational services and research needs of the academic community. VCL is an open source cloud orchestration stack with a self-service portal that currently supports a large number of customers and commercial cloud, or cloud-related services and solutions. It was developed by NCSU with support from IBM Corporation. VCLs promise to support researchers and students in all academic levels to fulfill all their computing needs. In addition to supporting students and faculty members at NC State University and other UNC System universities, the NC VCL now also supports students at several NC community colleges. Also, we introduced cloud computing and service science related activities and achievements at Jordan University of Science and Technology.

Cloud Scheduling Optimization: A Reactive Model to Enable Dynamic Deployment of Virtual Machines Instantiations

This study proposes a model for supporting the decision making process of the cloud policy for the deployment of virtual machines in cloud environments. We explore two configurations, the static case in which virtual machines are generated according to the cloud orchestration, and the dynamic case in which virtual machines are reactively adapted according to the job submissions, using migration, for optimizing performance time metrics. We integrate both solutions in the same simulator for measuring the performance of various combinations of virtual machines, jobs and hosts in terms of the average execution and total simulation time. We conclude that the dynamic configuration is prosperus as it offers optimized job execution performance.