Formal Design of Dynamic Reconfiguration Protocol for Cloud Applications

International audienceCloud applications are complex applications composed of a set of interconnected software components running on different virtual machines, hosted on remote physical servers. Deploying and reconfiguring this kind of applications are very complicated tasks especially when one or multiple virtual machines fail when achieving these tasks. Hence, there is a need for protocols that can dynamically reconfigure and manage running distributed applications. In this article, we present a novel protocol, which aims at reconfiguring cloud applications. This protocol is able to ensure communication between virtual machines and resolve dependencies by exchanging messages, (dis)connecting, and starting/stopping components in a specific order. The interaction between machines is assured via a publish-subscribe messaging system. Each machine reconfigures itself in a decentralized way. The protocol supports virtual machine failures, and the reconfiguration always terminates successfully even in the presence of a finite number of failures. Due to the high degree of parallelism inherent to these applications, the protocol was specified using the LNT value-passing process algebra and verified using the model checking tools available in the CADP toolbox. The use of formal specification languages and tools helped to detect several bugs and to improve the protocol

CIRUS: an elastic cloud-based framework for Ubilytics

International audienceThe Internet of Things (IoT) has become a reality with the availability of chatty embedded devices. The huge amount of data generated by things must be analysed with models and technologies of the " Big Data An-alytics " , deployed on Cloud platforms. The CIRUS project aims to deliver a generic and elastic cloud-based framework for Ubilytics (ubiquitous big data analytics). The CIRUS framework collects and analyses IoT data for Machine to Machine services using Component-off-the-Shelves (COTS) such as IoT gateways, Message brokers or Message-as-a-Service providers and Big Data analytics platforms deployed and reconfigured dynamically with Roboconf. In this paper, we demonstrate and evaluate the genericity and elasticity of CIRUS with the deployment of an Ubilytics use case using a real dataset based on records originating from a practical source

An Adaptable Framework to Deploy Complex Applications onto Multi-cloud Platforms

International audienceCloud computing is nowadays a popular technology for hosting IT services. However, deploying and reconfiguring complex applications involving multiple software components, which are distributed on many virtual machines running on single or multi-cloud platforms, is error-prone and time-consuming for human administrators. Existing deployment frameworks are most of the time either dedicated to a unique type of application (e.g. JEE applications) or address a single cloud platform (e.g. Amazon EC2). This paper presents a novel distributed application management framework for multi-cloud platforms. It provides a Domain Specific Language (DSL) which allows to describe applications and their execution environments (cloud platforms) in a hierarchical way in order to provide a fine-grained management. This framework implements an asynchronous and parallel deployment protocol which accelerates and make resilient the deployment process. A prototype has been developed to serve conducting intensive experiments with different type of applications (e.g. OSGi application and ubiquitous big data analytics for IoT) over disparate cloud models (e.g. private, hybrid, and multi-cloud), which validate the genericity of the framework. These experiments also demonstrate its efficiency comparing to existing frameworks such as Cloudify

Roboconf: a Hybrid Cloud Orchestrator to Deploy Complex Applications

International audienceThis paper presents Roboconf, an open-source distributed application orchestration framework for multi-cloud platforms, designed to solve challenges of current Autonomic Computing Systems in the era of Cloud computing. It provides a Domain Specific Language (DSL) which allows to describe applications and their execution environments (cloud platforms) in a hierarchical way in order to provide a fine-grained management. Roboconf implements an asynchronous and parallel deployment protocol which accelerates and makes resilient the deployment process. Intensive experiments with different type of applications over different cloud models (e.g. private, hybrid, and multi-cloud) validate the genericity of Roboconf. These experiments also demonstrate its efficiency comparing to existing frameworks such as RightScale, Scalr, and Cloudify

Aspects Can Be Efficient: Experience with Replication and Protection

Separation of concerns, which aims at separating different aspects involved in complex applications, is a general trend in software programming. It allows a given aspect to be programmed in a more or less isolated manner from the functional code of an application. This trend has been studied by the AOP (Aspect Oriented Programming) community, through the provision of language supports for programming and composing aspects. It has also been experi-mented in the context of component-based middleware, which usually address system-related aspects (e.g., transactions, security, persistence, etc). In both domains, most implementations of separation of concerns involve indirection objects and extra method calls that incur a non-negligible performance over-head. While performance was initially not the main motivation of «separation of concern environments», we believe that it is possible to efficiently integrate as-pects in such environments. In this paper, we report on an experiment which aims at optimizing aspects through code injection techniques. We consider two aspects, replication and access control, and present a preliminary performance evaluation which confirms that the overhead can be significantly reduced

Experiences Implementing Efficient Java Thread Serialization, Mobility and Persistence

Today, mobility and persistence are important aspects of distributed computing- . They have many fields of use such as load balancing, fault tolerance and dynamic reconfiguration of applications. In this context, Java provides many useful mechanisms for the mobility of code via dynamic class loading, and the mobility or persistence of data via object serialization. However, Java does not provide any mechanism for the mobility/persistence of computation (i.e., threads). We designed and implemented a new mechanism, called , that is used to build thread mobility or thread persistence. Therefore, a running Java thread can, at an arbitrary state of its execution, migrate to a remote machine where it resumes its execution, or be checkpointed on disk for possible subsequent recovery. With our services, migrating a thread is simply performed by the call of our primitive, and checkpointing/recovering a thread is performed by the call of our and primitives. Several projects have recently addressed the issue of Java thread serialization, e.g., Sumatra, Wasp, JavaGo, Brakes, JavaGoX, Merpati. Some of them have attempted to minimize the overhead incurred by the thread serialization mechanism on thread performance, but none of them has been able to completely avoid this overhead. We propose a generic Java thread serialization mechanism that does not impose any performance overhead on serialized threads. This is achieved thanks to the use of type inference and dynamic de-optimization techniques. In this paper, we describe the design and implementation details of our thread serialization prototype in Sun Microsystems' JDK. We report on experiments conducted with our prototype, present a comparative performance evaluation of the main thread serialization techniques, and confirm the elimination of the performance overhead with our thread serialization mechanism

Cooperative Resource Management in a IaaS

Virtualized IaaS generally rely on a server consolidation system to pack virtual machines (VMs) on as few servers as possible, for energy saving. However, two situations are not taken into account, and could enhance consolidation. First, since the managed VMs can be of various sizes (small, medium, large, etc.), VMs packing can be obstructed when sizes don't fit available spaces on servers. Therefore, we would need to "split" such VMs. Second, two VMs which host replicas of the same application server (for scalability) could be "fusion Ned" when they are located on the same physical server, in order to reduce virtualization overhead and VMs memory footprint. Split and fusion operations lead to the management of elastic VMs and requires cooperation between the application level and the provider level, as they impact management at both levels. In this paper, we propose a IaaS resource management system which implements elastic VMs based on split/fusion operations and cooperative management. We show its benefit with a set of experiments

Asynchronous Coordination of Stateful Autonomic Managers in the Cloud

International audienceCloud computing is now an omnipresent paradigm in modern programming. Cloud applications usually consist of several software components deployed on remote virtual machines. Managing such applications is a challenging problem because manual administration is no longer realistic for these complex distributed systems. Thus, auto-nomic computing is a promising solution for monitoring and updating these applications automatically. This is achieved through the automation of administration functions and the use of control loops called au-tonomic managers. An autonomic manager observes the environment, detects changes, and reconfigures dynamically the application. Multiple autonomic managers can be deployed in the same system and must make consistent decisions. Using them without coordination may lead to inconsistencies and error-prone situations. In this paper, we present our approach for coordinating stateful autonomic managers, which relies on a simple coordination language, new techniques for asynchronous controller synthesis and Java code generation. We used our approach for coordinating real-world cloud applications

Self-scalable Benchmarking as a Service with Automatic Saturation Detection

Part 4: ServicesInternational audienceSoftware applications providers have always been required to perform load testing prior to launching new applications. This crucial test phase is expensive in human and hardware terms, and the solutions generally used would benefit from further development. In particular, designing an appropriate load profile to stress an application is difficult and must be done carefully to avoid skewed testing. In addition, static testing platforms are exceedingly complex to set up. New opportunities to ease load testing solutions are becoming available thanks to cloud computing. This paper describes a Benchmark-as-a-Service platform based on: (i) intelligent generation of traffic to the benched application without inducing thrashing (avoiding predefined load profiles), (ii) a virtualized and self-scalable load injection system. This platform was found to reduce the cost of testing by 50% compared to more commonly used solutions. It was experimented on the reference JEE benchmark RUBiS. This involved detecting bottleneck tiers