Community Research and Development Information Service - CORDIS

H2020

ENTICE Report Summary

Project ID: 644179
Funded under: H2020-EU.2.1.1.3.

Periodic Reporting for period 1 - ENTICE (dEcentralized repositories for traNsparent and efficienT vIrtual maChine opErations)

Reporting period: 2015-02-01 to 2016-07-31

Summary of the context and overall objectives of the project

What is the problem/issue being addressed?
Virtualization is a key technology in Cloud computing that allows users to run multiple virtual machines (VM) with their own application environment on top of physical hardware. Essentially VMs are virtual slices of large, physical servers. Virtualization enables scaling up and down of applications by elastic on-demand provisioning of VMs in response to their variable load to achieve increased utilisation efficiency at a lower operational cost, while guaranteeing the desired level of Quality of Service (QoS, such as response time) to the end-users. Typically, VMs are created using provider-specific templates (so-called VM images) that are stored in proprietary repositories, leading to provider lock-in and hampering portability or simultaneous usage of multiple federated Clouds.

In this context, optimisation at the level of the VM images is needed both by the applications and by the underlying Cloud providers for improved resource usage, operational costs, elasticity, storage use, and other desired QoS- related features. We identify in this project five critical barriers that prevent many users from industry, business and academia to effectively use Cloud resources and virtualized environments for their computing and data processing needs: (i) manual, error-prone and time consuming VM image creation, (ii) monolithic VM images with large deployment and migration overheads, (iii) proprietary unoptimised VM repositories, (iv) inelastic resource provisioning, and (v) lack of information to support effective VM image optimisation.

Why is it important for society?
In European society, there exists a large variety of industrial applications and users that can strongly benefit from the ENTICE environment, such as: Cloud providers, application developers and most importantly Cloud users.

Societal benefits of ENTICE will be the streamlined, automated and intuitive deployment process with simple, optimised, and predictable performance that helps to save time and effort to get customers cloud
ready. Hence, the ENTICE environment will provide substantial advantages to many potential costumers in the SaaS domain such as lower capital expenditures, no need to manage upgrades and patches, and enterprise scalability.

This will result in societal impact through ENTICE changing user behaviour and utilise highly optimisedVM operations and image repositories based on innovative multi-objective VM synthesis, analysis, and placement optimisation techniques to improve Cloud resource utilisation, which in turn will have a societal impact on energy consumption and the CO2 footprint. As such, ENTICE will contribute to the action plan of the European code of conduct for energy efficiency in data centres.

Furthermore, with the help of the lightweight ENTICE distributed VM repository, SaaS and IaaS-based applications and infrastructures will gain increased availability and elasticity. Thus, ENTICE and its technology bring unique Cloud advancements which go far beyond any other existing service or environment available in Europe and word-wide. At least one use case (DEIMOS EOD) will be deployed across the world with the help of ENTICE. For this to happen, ENTICE will be integrated with other non-European IaaS providers like FutureGrid and Amazon EC2. Based on demonstrations of this and other use cases around the world, we expect over 100 SaaS providers from outside Europe to adopt ENTICE for their own applications within three years after the project end.

What are the overall objectives?
In this project, we will research and create an initial prototype of a novel VM repository and operational environment named ENTICE for federated Cloud infrastructures aiming to:
(i) simplify the creation of lightweight and highly optimised VM images tuned for high level descriptions of applications;
(ii) automatically decompose and distribute VM images based on multi-objective optimisation (performance, economic costs, storage size, and QoS needs) and a knowledge base and reasoning infrastructure to meet application runtime requirements; and
(iii) elastic auto-scale applications on Cloud resources based on their fluctuating load with optimised VM interoperability across Cloud infrastructures and without provider lock-in, in order to finally fulfil the promises that virtualization technology has failed to deliver so far.

ENTICE will ultimately be capable of receiving unmodified and functionally complete VM images from users, and transparently tailor and optimise them for specific Cloud infrastructures with respect to their size, configuration, and geographical distribution, such that they are loaded, delivered, and executed faster and with improved QoS compared to their current behaviour.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In this project, a multidisciplinary team of computer scientists and application providers has actively worked on researching a ubiquitous repository-based technology, which has resulted in a development of an initial integrated prototype of the ENTICE environment. The ENTICE environment is completely decoupled from the applications and their specific runtime environments, but continuously supports them through optimised VM image creation, redistribution and storage.

The ENTICE architecture has a modular structure. The communication between the separate modules is established by using Service-oriented architecture, which guaranties transparent distribution of the computational modules.
In accordance with the scheduled research and development activities, for the project period of M1-M18, the following separate modules have been developed and integrated in a first ENTICE prototype:

1. Interoperable and decentralized VM image synthesis – the module provides automatic synthesising of highly-optimised virtual appliances that allow the efficient deployment and execution of the incorporated services and/or applications. Furthermore, it has been designed to identify unused libraries in the VM images, which results in reduced storage requirements.
2. Multi-objective middleware for distributed VM image repositories in federated Cloud infrastructures - the multi-objective optimization framework is designed as a unified core module, which can be utilized for multiple different optimization purposes. Internally, the optimization module is sub-divided in four distinctive sub-modules. Each of the sub-modules has been tailored specifically for a given task, as described in the project proposal.
3. Knowledge base and reasoning – the knowledge base stores all information, which is essential for normal functioning of the ENTICE environment. Within the knowledge base an initial ontology was firstly deployed and then it was expanded and adapted to fit the selected Jena Fuseki technology. Some parts of the ontology were tested through an initial implementation of the Knowledge Base, which was populated with instances data. The Knowledge Base itself was developed to run as a software service. Additionally, this module incorporates reasoning algorithms, capable of providing implementation of the novel concept of Pareto - SLA
4. Image portal and Graphical User Interface – the image portal, as the main entry point for the ENTICE environment is composed of two elements: frontend and backend. The frontend covers the representation of all ENTICE functions in a form understandable by the users. The backend integrates all above mentioned ENTICE services with the Image portal and the graphical user interface.

During the first half of the project time-line we have started with the required tests and procedures for validation and demonstration of the ENTICE environment on the basis of a carefully-chosen set of use cases provided by the ENTICE company partners: (i) DEIMOS as a SaaS provider with different services to demonstrate the efficiency and usability of the results of the project, (ii) FLEX as an IaaS provider aiming at a better portability and efficiency of the resources of their Cloud offerings that aid service providers to reach better customer support with versatile and client means to upload, utilise and transfer VM images, and (iii) WT, which is both a SaaS and IaaS provider, who plans to demonstrate portability, efficiency, and elasticity of the ENTICE environment. So far, initial preparations have been conducted to fully deploy the ENTICE environment in the private infrastructure of DEIMOS. Additionally, the pilot use cases for the WT and FLEX have been tested on the initial ENTICE prototype.

The goals of ENTICE for the period of M1 – M18 have been successfully achieved. The ideas and currently available results of ENTICE have been presented at various workshops, expositions and networking events. We also started various collaborations with various EU projects and software engineering clusters to exchange ideas and to reuse software components.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

For the period of M1-M18 the ENTICE project has progressed beyond the state-of-the art and provided the following innovation:

1. Multi-objective Middleware for Distributed VM image repositories in Federated Cloud Environment, which has been designed to provide an easy to use interface capable of receiving unmodified and functionally complete VM images from its users, and transparently distribute them to a specific Cloud infrastructure in a federation with respect to their size, configuration, and geographical distribution, such that they are loaded and delivered faster and with improved reduced financial cost compared to existing solutions.

2. Knowledge Base for Automated Decision Making in Virtual Machine Images Distribution, Analysis and Synthesis, which encompasses a knowledge base built on top of Open Source technologies, such as Jena Fuseki, and reasoners, such as Pellet, and standards, such as OWL/RDF. The ENTICE Knowledge Base can be used along with the ENTICE environment or as a standalone service to assist software engineers to automate decision making in complex situations, for example where there is the need for multi-criteria optimisation. The Knowledge Base provides easy to use REST-like API’s for integration with third party services.

3. Middleware for Virtual Machine Image Synthesis and Size Optimization, which encompasses a middleware for automated synthesis of highly-optimised VM images for efficient deployment and execution of user applications and/or services. The middleware provides two approaches: (i) start with an already existing VM image and eliminate parts not necessary for the user indicated functionality, and (ii) synthesise VM images from scratch by optimising recipe descriptions. The proposed middleware focuses on services that are widely hosted in virtualised environments, but delivered as a monolithic block of multitude of sometimes vaguely related functionalities. The middleware also provides easy to use REST-like API’s for integration with third party services.

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