Giovanni Morana

A P2P strategy for QoS discovery and SLA negotiation in Grid environment

In recent years, Grid systems and Peer to Peer networks are the most commonly-used solutions to achieve the same goal: the sharing of resources and services in heterogeneous, dynamic, distributed environments. Many studies have proposed hybrid approaches that try to conjugate the advantages of the two models. This paper proposes an architecture that integrates the P2P interaction model in Grid environments, so as to build an open cooperative model wherein Grid entities are composed in a decentralized way. In particular, this paper focuses on a QoS aware discovery algorithm for P2P Grid systems, analyzing protocol and explaining techniques used to improve its performance.

Scaling and Self-repair of Linux Based Services Using a Novel Distributed Computing Model Exploiting Parallelism

This paper describes a prototype implementing a high degree of fault tolerance, reliability and resilience in distributed software systems. The prototype incorporates fault, configuration, accounting, performance and security (FCAPS) management using a signaling network overlay and allows the dynamic control of a set of nodes called Distributed Intelligent Managed Elements (DIMEs) in a network. Each DIME is a computing entity (implemented in Linux and in the future will be ported to Windows) endowed with self-management and signaling capabilities to collaborate with other DIMEs in a network. The prototype incorporates a new computing model proposed by Mikkilineni in 2010, with signaling network overlay over the computing network and allows parallelism in resource monitoring, analysis and reconfiguration. A workflow is implemented as a set of tasks, arranged or organized in a directed acyclic graph (DAG) and executed by a managed network of DIMEs. Distributed DIME networks provide a network computing model to create distributed computing clouds and execute distributed managed workflows with high degree of agility, availability, reliability, performance and security.

Service Virtualization Using a Non-von Neumann Parallel, Distributed, and Scalable Computing Model

This paper describes a prototype implementing a high degree of transaction resilience in distributed software systems using a non-von Neumann computing model exploiting parallelism in computing nodes. The prototype incorporates fault, configuration, accounting, performance, and security (FCAPS) management using a signaling network overlay and allows the dynamic control of a set of distributed computing elements in a network. Each node is a computing entity endowed with self-management and signaling capabilities to collaborate with similar nodes in a network. The separation of parallel computing and management channels allows the end-to-end transaction management of computing tasks (provided by the autonomous distributed computing elements) to be implemented as network-level FCAPS management. While the new computing model is operating system agnostic, a Linux, Apache, MySQL, PHP/Perl/Python (LAMP) based services architecture is implemented in a prototype to demonstrate end-to-end transaction management with auto-scaling, self-repair, dynamic performance management and distributed transaction security assurance. The implementation is made possible by a non-von Neumann middleware library providing Linux process management through multi-threaded parallel execution of self-management and signaling abstractions. We did not use Hypervisors, Virtual machines, or layers of complex virtualization management systems in implementing this prototype.

Computing Models for Distributed Autonomic Clouds and Grids in the Context of the DIME Network Architecture

This paper presents an overview of computing models for a very important class of distributed systems: autonomic grids and clouds. We present the DIME network architecture as a representative of this still relatively new class of computing. We attempt to capture its potentials by formal modeling and emerging properties.

An ACO Inspired Strategy to Improve Jobs Scheduling in a Grid Environment

Scheduling is one of the most crucial issue in a grid environment because it strongly affects the performance of the whole system. In literature there are several algorithms that try to obtain the best performance possible for the specified requirements; taking into account that the issue of allocating jobs on resources is a combinatorial optimization problem, NP-hard in most cases, several heuristics have been proposed to provide good performance. In this work an algorithm inspired to Ant Colony Optimization theory is proposed: this algorithm, named Aliened Ant Algorithm, is based on a different interpretation of pheromone trails. The goodness of the proposed algorithm, in term of load balancing and average queue waiting time, has been evaluated by mean of a vast campaign of simulations carried out on some real scenarios of a grid infrastructure.

A bio-inspired distributed algorithm to improve scheduling performance of multi-broker grids

The scheduling in grids is known to be a NP-hard problem. The distributed deployment of nodes, their heterogeneity and their fluctuations in terms of workload and availability make the design of an effective scheduling algorithm a very complex issue. The scientific literature has proposed several heuristics able to tackle this kind of optimization problem using techniques and strategies inspired by nature. The algorithms belonging to ant colony optimization (ACO) paradigm represent an example of these techniques: each one of these algorithms uses strategies inspired by the self-organization ability of real ants for building effective grid schedulers. In this paper, the authors propose an on line, non-clairvoyant, distributed scheduling solution for multi-broker grid based on the alienated ant algorithm (AAA), a new ACO inspired technique exploiting a “non natural” behavior of ants and an inverse interpretation of pheromone trails. The paper introduces the proposed algorithm, explains the differences with other classical ACO approaches, and compares AAA with two different algorithms. The results of simulations show that the AAA guarantees good performance in terms of makespan, average queue waiting time and load balancing capability.

Infusing Cognition into Distributed Computing: A New Approach to Distributed Datacenters with Self-Managing Services on Commodity Hardware (Virtualized or Not)

The advent of virtualization technologies and cloud computing has improved application provisioning speed, resource utilization, fault-management, availability using auto-failover and performance optimization using auto-scaling in distributed computing environments. However, heterogeneous virtualization technologies offered by different service providers with disparate infrastructure and their orchestration and management systems have also increased the complexity of managing distributed applications and vendor lock-in. In this paper we utilize new computing, management and programming models introduced using the DIME network architecture to provide end to end service visibility and control across distributed physical or virtual infrastructure. Resulting decoupling of application and service transaction management from myriad distributed infrastructure management systems at run-time enables policy based, secure, service mobility across physical servers or virtual machines deployed in data enters or public clouds. Using the new architecture we have implemented service self-repair, auto-scaling, live-migration and end-to-end service transaction security independent of server and network security mechanisms.

Intelligent organisation of semantic networks, DIME network architecture and grid automata

A network architecture, based on increasing intelligence of computing nodes, is suggested for building the semantic grid. In its essence, distributed intelligent managed element (DIME) network architecture extends the conventional computational model of information processing networks, allowing improvement of the efficiency and resiliency of computational processes. This approach is based on organising the process dynamics under the supervision of intelligent agents. The DIME network architecture utilises the DIME computing model with non-von Neumann parallel implementation of a managed Turing machine cluster with a signalling network overlay and adds cognitive elements to evolve super-recursive information processing, for which it is proved that they improve efficiency and power of computational processes. In this paper, we model the DIME network architecture using grid automata. A grid automaton provides a universal model for computer, sensor, and many other networks. We introduce different types of grid automata and study constructive operations with grid automata, which are oriented at the network construction, generation and development.

Cognitive Application Area Networks: A New Paradigm for Distributed Computing and Intelligent Service Orchestration

Distributed systems are dynamic systems where software and hardware together deliver information processing services to allow modelling, interaction, reasoning, analysis and control of the external environment. The intent of the distributed computation is to execute computational workflows using computing resources. The software contains the algorithms that specify the tasks while the hardware provides the required resources to execute the algorithms. The initial structure is defined by the association of software with hardware and the dynamic structure is defined by their temporal evolution. The meta-knowledge of the intent of the algorithm, the association of specific algorithm to a specific device, their temporal evolution and exception handling when the computation deviates from the intent is outside the software and hardware design and is expressed in non-functional requirements. In this paper, we describe an architecture to capture the meta-knowledge in meta-containers and enforce the intent of the computation while the computation is in progress.

Scalable and Configurable Monitoring System for Cloud Environments

The scale of the current cloud infrastructures and the heterogeneity of applications running on them pose significant challenges about resources management on clouds. This paper proposes a monitoring system that allows user to collect and aggregate data in a form flexible and adequate to the integration with the management policy that he adopt. This monitoring system is supplied by a a configurable and highly scalable version of publisher-subscriber pattern. It gives user the capability of selecting data he should obtain from the provider with the desired grain of triggering and is suitable to support distributed and cooperative management systems.