Rossano Gaeta

GreatSPN 1.7: graphical editor and analyzer for timed and stochastic Petri nets

This paper describes the GreatSPN 1.7 package for the modeling, validation, and performance evaluation of distributed systems using Generalized Stochastic Petri Nets and their colored extension. The tool provides a friendly framework to experiment with timed Petri net based modeling techniques. It implements efficient analysis algorithms to allow its use on “real” applications, not only toy examples. Developed in a university for non-profit purposes, it is distributed free of charge to other universities for educational and research purposes. An overview of the complete architecture of the package is given together with examples of its application. Then the various analysis and simulation modules are described.

On the fly gaussian elimination for LT codes

We propose an improved algorithm for decoding LT codes using Gaussian elimination. Our algorithm performs useful processing at each coded packet arrival thus distributing the decoding work during all packets reception, obtaining a shorter actual decoding time. Furthermore, using a swap heuristic the decoding matrix is kept sparse, decreasing the cost of both triangularization and back-substitution steps.

Parametric fault tree for the dependability analysis of redundant systems and its high-level Petri net semantics

In order to cope efficiently with the dependability analysis of redundant systems with replicated units, a new, more compact fault-tree formalism, called Parametric Fault Tree (PFT), is defined. In a PFT formalism, replicated units are folded and indexed so that only one representative of the similar replicas is included in the model. From the PFT, a list of parametric cut sets can be derived, where only the relevant patterns leading to the system failure are evidenced regardless of the actual identity of the component in the cut set. The paper provides an algorithm to convert a PFT into a class of High-Level Petri Nets, called SWN. The purpose of this conversion is twofold: to exploit the modeling power and flexibility of the SWN formalism, allowing the analyst to include statistical dependencies that could not have been accommodated into the corresponding PFT and to exploit the capability of the SWN formalism to generate a lumped Markov chain, thus alleviating the state explosion problem. The search for the minimal cut sets (qualitative analysis) can be often performed by a structural T-invariant analysis on the generated SWN. The advantages that can be obtained from the translation of a PFT into a SWN are investigated considering a fault-tolerant multiprocessor system example.

Generalized Probabilistic Flooding in Unstructured Peer-to-Peer Networks

In this paper, we propose a generalization of the basic flooding search strategy for decentralized unstructured peer-to-peer (P2P) networks. In our algorithm a peer forwards a query to one of its neighbors using a probability that is a function of the number of connections in the overlay network of both. Moreover, this probability may also depend on the distance from the query originator. To analyze the performance of the proposed search strategy in heterogeneous decentralized unstructured P2P networks, we develop a generalized random graph (GRG)-based model that takes into account the high variability in the number of application level connections that each peer establishes, and the nonuniform distribution of resources among peers. Furthermore, the model includes an analysis of peer availability, i.e., the capability of relaying queries of other peers, as a function of the query generation rate of each peer. Validation of the proposed model is carried out comparing the model predictions with simulations conducted on real overlay topologies obtained from crawling the popular file sharing application Gnutella.

Analysis of PPLive through active and passive measurements

The P2P-IPTV is an emerging class of Internet applications that is becoming very popular. The growing popularity of these rather bandwidth demanding multimedia streaming applications has the potential to flood the Internet with a huge amount of traffic.

Efficient discrete-event simulation of colored Petri nets

Colored Petri nets are a powerful formalism for the description of complex, asynchronous distributed systems. They can express in a very concise way the behavior of very large systems, especially in case these systems are composed of many replications of a few basic components that individually behave in a similar way. The simulation of such models is, however, difficult to perform in a computationally efficient way. For the specific class of stochastic well-formed nets (SWNs), we present a set of optimizations that allow a very efficient implementation of the event-driven simulation technique. Three approaches are followed to improve simulation efficiency: first, an efficient algorithm for the computation of the occurrences of a transition in a given marking; second, reduction of the amount of work needed to schedule or preempt the occurrence of a transition as a consequence of a marking change, taking into account the restrictions on color functions for the SWN formalism; third, reduction of the average length of the event list in the case of symmetric models where the so-called symbolic simulation technique applies. The approach is validated by performance measurements on several large SWN models taken from the literature.

Fluid models for large-scale wireless sensor networks

We develop an analytical framework for the study of large-scale, wireless sensor networks. We use a fluid approach, i.e., we represent the sensor network by a continuous fluid entity distributed on the network area. We assume that sensors employ a CSMA/CA mechanism to access the channel and a minimum energy consumption criterion to select traffic routes, and accurately model these aspects. Furthermore, the framework accounts for energy consumption and is able to model the active/sleep dynamics of the nodes. We validate our approach through simulation and show that the proposed framework is well suited for describing the properties of large sensor networks and understanding their complex behavior. To the best of our knowledge, our framework is one of few analytical models developed for large-scale sensor networks which can accurately capture the main aspects of these systems.

A simple analytical framework to analyze search strategies in large-scale peer-to-peer networks

This paper presents an analytical framework to study search strategies in large-scale decentralized unstructured peer-to-peer (P2P) networks. The peers comprising the P2P network and their application-level connections are modeled as generalized random graphs (GRGs) whose simple and efficient analysis is accomplished using the generating function of the graphs degree distribution. The framework we defined allows the computation of several interesting performance indexes to be used to compare different search strategies: in particular, the average number of messages sent throughout the P2P network and the probability that a query is successful are used as examples. Furthermore, assuming that the cumulative distribution function (CDF) of the time required by a peer to positively reply to a query is known, we show how to derive the CDF of the time it takes for a randomly chosen peer to obtain at least one positive reply from other peers. The approach is validated through simulation showing that the accuracy of the proposed model improves as the size of the P2P network increases making it a suitable tool for the analysis of search strategies in large-scale systems.

Rateless codes network coding for simple and efficient P2P video streaming

The goal of this paper is the development of network coding solutions able to improve the performance of video streaming applications over peer-to-peer overlays. Recent advances in P2P protocols have shown that rateless codes can be profitably applied to P2P video streaming with several advantages in terms of protocol efficiency and simplification, e.g. push based video delivery, no need of packet reconciliation at the decoder. In this paper existing and novel network coding techniques based on rateless codes are presented and compared, showing that rateless codes, besides simplifying the protocol design, can significantly reduce the startup and playback delays. The proposed protocol is evaluated on real topologies, obtained by crawling the widespread PPLive video streaming application. The reported experimental results show that the proposed protocol significantly reduces the startup and playback delay and allows one to increase the bitrate devoted to the video stream.

TURINstream: A Totally pUsh, Robust, and effIcieNt P2P Video Streaming Architecture

This paper presents TURINstream, a novel P2P video streaming architecture designed to jointly achieve low delay, robustness to peer churning, limited protocol overhead, and quality-of-service differentiation based on peers cooperation. Separate control and video overlays are maintained by peers organized in clusters that represent sets of collaborating peers. Clusters are created by means of a distributed algorithm and permit the exploitation of the participant nodes upload capacity. The video is conveyed with a push mechanism by exploiting the advantages of multiple description coding. TURINstream design has been optimized through an event driven overlay simulator able to scale up to tens of thousands of peers. A complete prototype of TURINstream has been developed, deployed, and tested on PlanetLab. We tested our prototype under varying degree of peer churn, flash crowd arrivals, sudden massive departures, and limited upload bandwidth resources. TURINstream fulfills our initial design goals, showing low average connection, startup, and playback delays, high continuity index, low control overhead, and effective quality-of-service differentiation in all tested scenarios.