Patrizio Dazzi

Cloud federations in contrail

Cloud computing infrastructures support dynamical and flexible access to computational, network and storage resources. To date, several disjoint industrial and academic technologies provide infrastructure level access to Clouds. Especially for industrial platforms, the evolution of de-facto standards goes together with worries about user lock-in to a platform. The Contrail project [6] proposes a federated and integrated approach to Clouds. In this work we present and motivate the architecture of Contrail federations. Contrails goal is to minimize the burden on the user and increase the efficiency in using Cloud platforms by performing both a vertical and a horizontal integration. To this end, Contrail federations play a key role, allowing users to exploit resources belonging to different cloud providers, regardless of the kind of technology of the providers and with a homogeneous, secure interface. Vertical integration is achieved by developing both the Infrastructure- and the Platform-as-a-Service levels within the project. A third key point is the adoption of a fully open-source approach toward technology and standards. Beside supporting user authentication and applications deployment, Contrail federations aim at providing extended SLA management functionalities, by integrating the SLA management approach of SLA@SOI project in the federation architecture.

Behavioural skeletons for component autonomic management on grids

We present behavioural skeletons for the CoreGRID Component Model, which are an abstraction aimed at simplifying the development of GCM-based selfmanagement applications. Behavioural skeletons abstract component self-managent in component-based design as design patterns abstract class design in classic OO development. As here we just wish to introduce the behavioural skeleton framework, emphasis is placed on general skeleton structure rather than on their autonomic management policies.

A peer-to-peer recommender system for self-emerging user communities based on gossip overlays

Gossip-based peer-to-peer protocols proved to be very efficient for supporting dynamic and complex information exchange among distributed peers. They are useful for building and maintaining the network topology itself as well as to support a pervasive diffusion of the information injected into the network. This is very useful in a world where there is a growing need to access and be aware of many types of distributed resources like Internet pages, shared files, online products, news and information. Finding flexible, scalable and efficient mechanisms addressing this topic is a key issue, even with relevant social and economic aspects. In this paper, we propose the general architecture of a system whose aim is to exploit the collaborative exchange of information between peers in order to build a system able to gather similar users and spread useful suggestions among them.

QBROKAGE: A Genetic Approach for QoS Cloud Brokering

The broad diffusion of Cloud Computing has fostered the proliferation of a large number of cloud computing providers. The need of Cloud Brokers arises for helping consumers in discovering, considering and comparing services with different capabilities and offered by different providers. Also, consuming services exposed by different providers, when possible, may alleviate the vendor lock-in. While it can be straightforward to choose the best provider when deploying small and homogeneous applications, things get harder if the size and complexity of applications grow up. In this paper we propose a genetic approach for Cloud Brokering, focusing on finding Infrastructure-as-a-Service (IaaS) resources for satisfying Quality of Service (QoS) requirements of applications. We performed a set of experiments with an implementation of such broker. Results show that our broker can find near-optimal solutions even when dealing with hundreds of providers, trying at the same time to mitigate the vendor lock-in.

Joint structured/unstructured parallelism exploitation in muskel

Structured parallel programming promises to raise the level of abstraction perceived by programmers when implementing parallel applications. In the meanwhile, however, it restricts the freedom of programmers to implement arbitrary parallelism exploitation patterns. In this work we discuss a data flow implementation methodology for skeleton based structured parallel programming environments that easily integrates arbitrary, user-defined parallelism exploitation patterns while preserving most of the benefits typical of structured parallel programming models.

A P2P REcommender System based on Gossip Overlays (PREGO)

Gossip-based Peer-to-Peer protocols proved to be very efficient for supporting dynamic and complex information exchange among distributed peers. They are useful for building and maintaining the network topology itself as well as to support a pervasive diffusion of the information injected into the network. This is very useful in a world where there is a growing need to access and be aware of many types of distributed resources like Internet pages, shared files, online products, news and information, finding ???exible, scalable and efficient mechanisms addressing this topic is a key issue, even with relevant social and economic aspects. In this paper, we propose the general architecture of a system that tries to exploit the collaborative exchange of information between peers in order to build a system able to gather similar users and spread useful suggestions among them.

PAL: Exploiting Java Annotations for Parallelism

We discuss how Java annotations can be used to provide the meta information needed to automatically transform plain Java programs into suitable parallel code that can be run on workstation clusters, networks and grids. Programmers are only required to decorate the methods that will eventually be executed in parallel with standard Java 1.5 annotations. Then these annotations are automatically processed and parallel byte code is derived. When the annotated program is started, it automatically retrieves the information about the executing platform and evaluates the information specified inside the annotations to transform the byte-code into a semantically equivalent multithreaded or multitask version, depending on the target architecture features. The results returned by the annotated methods, when invoked, are futures with a wait-by-necessity semantics. A PAL (Parallel Abstraction Layer) prototype exploiting the annotation based parallelizing approach has been implemented in Java. PAL targets JJPF, an existing, skeleton based, JAVA/JINI programming environment, as Parallel Framework. The experiments made with the prototype are encouraging: the design of parallel applications has been greatly simplified and the performances obtained are the same of an application directly written in JJPF.

Service and Resource Discovery supports over P2P overlays

We describe the main architecture and the design principles of the Service/Resource Discovery System (SRDS), a component of the XtreemOS Operating System. XtreemOS is a Linux extension that enables management and exploitation as single platform of computational resources provided by federated Virtual Organizations. The SRDS provides scalable and fault-tolerant directory services supporting many of the platform functionalities, ranging from dynamic resource location and job control to system and application-oriented directory services. The key challenge of the SRDS design is to provide the common metaphor of the directory service, meeting the scalability requirements of a Grid-aware Operating system, and at the same time enjoy extendability and configurability, especially with respect to the quality of service provided. The SRDS design combines different peer to peer structured overlay networks, exploiting their peculiar strengths. We describe the implementation and our design of the namespace abstraction as implemented on top of multiple overlay networks. Finally, we show test results of the SRDS on top of a subset of the Grid5000 platform.

Cracker: Crumbling large graphs into connected components

The problem of finding connected components in a graph is common to several applications dealing with graph analytics, such as social network analysis, web graph mining and image processing. The exponentially growing size of graphs requires the definition of appropriated computational models and algorithms for their processing on high throughput distributed architectures. In this paper we present cracker, an efficient iterative algorithm to detect connected components in large graphs. The strategy of cracker is to iteratively grow a spanning tree for each connected component of the graph. Nodes added to such trees are discarded from the computation in the subsequent iterations. We provide an extensive experimental evaluation considering a wide variety of synthetic and real-world graphs. The experimental evaluation shows that cracker consistently outperforms state-of-the-art approaches both in terms of total computation time and volume of messages exchanged.

Balanced Graph Partitioning with Apache Spark

A significant part of the data produced every day by online services is structured as a graph. Therefore, there is the need for efficient processing and analysis solutions for large scale graphs. Among the others, the balanced graph partitioning is a well known NP-complete problem with a wide range of applications. Several solutions have been proposed so far, however most of the existing state-of-the-art algorithms are not directly applicable in very large-scale distributed scenarios. A recently proposed promising alternative exploits a vertex-center heuristics to solve the balance graph partitioning problem. Their algorithm is massively parallel: there is no central coordination, and each node is processed independently. Unfortunately, we found such algorithm to be not directly exploitable in current BSP-like distributed programming frameworks. In this paper we present the adaptations we applied to the original algorithm while implementing it on Spark, a state-of-the-art distributed framework for data processing.