Abstract The huge and ever-increasing amount of publicly available data is shaping the data-driven society that citizens are encouraged to tame. It requires future generations, i.e., current learners, to acquire data literacy skills to make informed decisions. Towards this direction, we present a data literacy workshop involving more than $$\varvec{150}$$ 150 high school learners focused on co-creating Open Data via a digital environment and authoring data stories while evaluating their engagement and learning. Results show that participants are, on average, engaged during the in-person stages of the workshops, independently by gender, and they are mainly interested in collaborative activities, hands-on, and public presentations. This experiment confirm that learning is positively correlated with engagement, which aligns with the literature. However, further efforts should be invested in letting learners master data literacy skills while increasing their interest.

In this Work-in-Progress paper we present a preliminary study and the design of a taxonomy of Tools, Languages and Environments (TLE) employed in K-12 Computing Education, in schools and outreach programs. The research provides an analytical classification model based on a survey of TLEs and on previous related works. It also outlines the collaborative protocol that will allow researchers to share the results of the taxonomy on a public repository. An analysis of the most common platforms where contributors can work collaboratively is presented to show the qualitative process of identification and choice of GitHub as the most reliable one.

Traditional forms of cyber security education mainly focus on knowledge transmission, which means that knowledge is perceived as a tangible object being transferred from an expert (i.e., the teacher) to a beginner. When practiced well, the learner may acquire such knowledge, but not the resilience to apply it in various contexts [1], [2]. This is especially troubling for the cyber security domain, given the dynamic and constantly changing nature of the field and the environments in which it is required. We therefore need forms of education that aim at understanding the interdisciplinary nature of the field of cyber security as well as at the development of joint action in context: being able to quickly analyse and understand evolving and possibly previously unseen situations and take collaborative action to prevent, detect and recover from incidents.

Summary The cloud computing paradigm has emerged as the backbone of modern price‐aware scalable computing systems. Many cloud service models are competing to become the leading doorway to access the computational power of cloud providers. Recently, a novel service model, called function‐as‐a‐service (FaaS), has been proposed, which enables users to exploit the cloud computational scalability, left out the configuration and management of huge computing infrastructures. This article discloses Fly, a domain‐specific language, which aims at reconciling cloud and high‐performance computing paradigms adopting a multicloud strategy by providing a powerful, effective, and pricing‐efficient tool for developing scalable workflow‐based scientific applications by exploiting different and at the same time FaaS cloud providers as computational backends in a transparent fashion. We present several improvements of the Fly language, as well as a new enhanced version of a source‐to‐source compiler, which currently supports Symmetric Multiprocessing, Amazon AWS, and Microsoft Azure backends and translation of functions in Java, JavaScript, and Python programming languages. Furthermore, we discuss a performance evaluation of Fly on a popular benchmark for distributed computing frameworks, along with a collection of case studies with an analysis of their performance results and costs.

Storytelling is an effective way of communicating information and knowledge, and it is widely adopted in heterogeneous contexts, from education by improving critical thinking and enhancing learning practice, to journalism by encouraging coherent stories of news supported by graphical representations. However, storytelling platforms seem to be targeted to a specific audience without showing how they can be adapted to heterogeneous needs, from class support in education to mechanisms to overcome the syndrome of the white page. In this article, we propose Novelette, a digital storytelling environment, and we show how it can be applied in heterogeneous contexts and by the different target audience. We present Novelette operating mechanisms, its architecture, and we overview different use cases, from tales creation Rodari style to data- and media-stories. By use-cases, we desire to make evident that the same platform can generate stories engaging for any target audience.

Querying Linked (Open) Data (LOD) by directly using SPARQL could be a painful task for most potential users of semantic data. Several approaches have been proposed to help users in query formulation. They succeed in hiding the underlying complexity but exploit only the monological - individual - approach. Information seeking and retrieval is not merely an individual effort, but it inherently involves various collaborative activities. For this reason, our proposal is to facilitate the exploitation of LODs by wrapping the querying and visualization tool in a social platform environment. In this way, we enable the dialogical approach. Moreover, since the users can collaboratively create datasets and visualizations, and reuse them also out of the social platform, we reach the trialogical learning. In this paper, we present our design approach, our tool, and related tests.

The exponential growth in the use of digital devices and the ubiquitous online access produce a huge amount of structured and unstructured data that can be mined and analyzed to gather insights into several domains. In particular, since the advent of Web 2.0, Online Social Networks (OSNs) represent a rich opportunity for researchers to collect real user data and to explore OSNs users behavior. This study represents a first attempt to characterize and classify OSNs users according to their level of activity through the use of user profile attributes. We analyzed four case studies from the Twitter platform for a final total of around 721 thousand users, divided into four sub-datasets and examined over a period of at least six months in 2017. Following a data-driven methodology, we found that static, profile-based information - based on the entire lifetime of the users - can help to recognize users influence in Twitter online communities. On the other hand, these profile attributes are not enough to characterize user activity on the microblogging platform.

This paper introduces a minimum viable software product to filter large datasets of engine data recorded during laboratory experiments of combustion engines. The aim is to support analysts in the identification and analysis of specific physical phenomenon within hours of recorded engine experimental data. Specifically, the tool has been designed considering the use case of identifying Low Speed Pre-Ignition events. This work describes the tool's graphical user interface and its scalable architecture based on mainstream web and big-data technologies as well as the practical application to pre-ignition events identification. The paper provides details on the architecture's performance, providing evidence of its scalability by increasing the number of available computing workers.

This paper contributes in the field of Open Data and their visualisations, trying to reduce the gap between the public institutions (who publish Open Data) and citizens, providing awareness of data quality and supporting them during the process of chart creation. Proposed solution syntactically analyses the dataset's values to infer its data types and continually shows a list of chart visualisations compatible with the selected dataset and its fields. Instead to start with a catalogue containing all available charts, the system reduces the space of charts proposing any time only those that are compatible. In addition, a well-known barrier in the use of Open Data is the poor quality of the available datasets, thus, this paper proposes two quality indexes to provide at glance awareness of the dataset quality. This provides a quantitative measurement to dataset publishers (e.g., public institutions), who can evaluate the data quality, and also the citizens, who can ask for better open datasets providing a reason for such request.

Simulation models are becoming an increasingly popular tool for the analysis and optimization of complex real systems in different fields. Finding an optimal system design requires performing a large parameter sweep. In this paper, we present the design of SOF (Simulation Optimization and exploration Framework on the cloud), a framework which exploits the computing power of a cloud computational environment in order to realize effective and efficient simulation optimization strategies. SOF offers several attractive features: SOF requires "zero configuration" as it does not require any additional software installed on the remote node, SOF is transparent to the user, since the user is totally unaware that system operates on a distributed environment, SOF is highly customizable and programmable, since it enables the running of different simulation optimization scenarios on different simulation toolkits. The tool has been fully developed and is available on a public repository under the Apache public licence.

This paper describes ExploraTool, a new interactive tool to visually explore data from multiple repositories. The tool has been applied in a real setting to explore computational fluid dynamics (CFD) simulation data and obtain new insights into the space of simulations. The inclusion of free exploration, filtering operations, and chart generation provides a quick method for performance comparisons. The paper proposes an algorithmic means of processing input in the form of tabular data sets, generating a plausible hierarchical structure over metadata categories, which is used to initialize the visualization together with interactions' methods to explore, select, and compare sets of simulation data. This paper also reports on the evaluation study performed involving 24 engineers over two distinct locations from a large automotive manufacturer to evaluate the usability and the overall user satisfaction with the tool. Participants rated the tool as intuitive, useful, and effective.

This paper describes a tool called ExploraTool to visualise, explore and graphically query large repositories of simulations. Instead of starting with the empty list, ExploraTool provides an initial overview of the repository content, progressively grouping the simulations by their main attributes, such as brand, vehicle model, power source, engine type and so on. Users can interactively navigate the repository view through drill-down, roll-up and rearrangement operations. In this way, using the ExploraTool, simulation analysts can visualise, explore and filter large repository of simulations as well as select groups of simulations to compare their performances.

ExploraTool is a tool to visually and textually explore, filter and select data within simulation repositories. The tool groups items together by their main attribute values. Groups are represented as nested ellipses. Drill-down and rollup operations are provided. In this paper, we extend by adding a textual based search facility that updates the visualisation, allowing at same time textual and visual queries. ExploraTool's features, challenges to face and future work have been discussed.

SUMMARY: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein-protein and protein-nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps. AVAILABILITY AND IMPLEMENTATION: CONSRANK is accessible as a public web tool at https://www.molnac.unisa.it/BioTools/consrank/. CONTACT: [email protected].

This paper describes Floasys, a web-based platform to foster the collaboration among Computational Fluid Dynamics analysts and to promote model reuse by centrally managing simulation data and providing metadata annotations and search functionality over them. In this way, CFD analysts access to simulation data and results performed by different engineers and are able to leverage on them to make the right design decisions.

Software that is meant to support collaboration is mostly developed “ad hoc”, placing some additional overhead to users, that are required to integrate the common work practices, realized with the traditional software applications, with the new collaborative features offered by the new application.

Nowadays, to design product impacted by fluid flow, industries use Computational Fluid Dynamics (CFD) to get a better insight into product behaviour. In this paper, we present a system architecture design for CFD Workflow management.

Agent-Based Models (ABMs) are a class of models which, by simulating the behavior of multiple agents (i.e., ndependent actions, interactions and adaptation), aim to emulate and/or predict complex phenomena. One of the general features of ABM simulations is their experimental capacity, that requires a viable and reliable infrastructure to interact with a running simulation, monitoring its behaviour, as it proceeds, and applying changes to the configurations at run time, (the computational steering) in order to study "what if" scenarios.

In this paper we present the analysis of a laboratory experiment designed to understand the effect of two communication environments, that is, face-to-face or computed-mediated, on group achievements when participants are involved in programming tasks, within an academic computer science course. Results show better students' performances in the computer-mediated setting, as stated by a statistically significant difference between the two approaches when considering the quality of the produced projects, in terms of the teacher's evaluation to pass the final exam. Our analysis shows that the integration of a collaborative instrument in a development environment helps students to achieve better results.

In this work, we present an interactive visual clustering approach for the exploration and analysis of vast volumes of data. Our proposed approach is a bio-inspired collective behavioral model to be used in a 3D graphics environment. Our paper illustrates an extension of the behavioral model for clustering and a parallel implementation, using Compute Unified Device Architecture to exploit the computational power of Graphics Processor Units (GPUs). The advantage of our approach is that, as data enters the environment, the user is directly involved in the data mining process. Our experiments illustrate the effectiveness and efficiency provided by our approach when applied to a number of real and synthetic data sets.

In this work, we present an interactive visual clustering approach for the exploration and analysis of datasets using the computational power of Graphics Processor Units (GPUs). The visualization is based on a collective behavioral model that enables cognitive amplification of information visualization. In this way, the workload of understanding the representation of information moves from the cognitive to the perceptual system. The results enable a more intuitive, interactive approach to the discovery of knowledge. The paper illustrates this behavioral model for clustering data, and applies it to the visualization of a number of real and synthetic datasets.

We focus on agent-based simulations where a large number of agents move in the space, obeying to some simple rules. Since such kind of simulations are computational intensive, it is challenging, for such a contest, to let the number of agents to grow and to increase the quality of the simulation. A fascinating way to answer to this need is by exploiting parallel architectures. In this paper, we present a novel distributed load balancing schema for a parallel implementation of such simulations. The purpose of such schema is to achieve an high scalability. Our approach to load balancing is designed to be lightweight and totally distributed: the calculations for the balancing take place at each computational step, and influences the successive step. To the best of our knowledge, our approach is the first distributed load balancing schema in this context. We present both the design and the implementation that allowed us to perform a number of experiments, with up-to 1,000,000 agents. Tests show that, in spite of the fact that the load balancing algorithm is local, the workload distribution is balanced while the communication overhead is negligible.

SUMMARY: Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein-protein and protein-nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermolecular contact maps. AVAILABILITY: COCOMAPS is accessible as a public web tool at http://www.molnac.unisa.it/BioTools/cocomaps CONTACT: [email protected]; [email protected].

In this paper we describe a novel Model-View-Controller based architecture, Centralized Control, that introduces collaboration in single-users applications. The architecture is able to add collaboration with no need to modify the source code of the original single-user application, and providing als

Several proposals have been presented to supplement the traditional measure of routing efficiency in P2P networks, i.e. the (average) number of hops for lookup operations, with measures of the latency incurred in the underlying network. So far, no solution has been presented to this “latency” problem without incurring in extra and heavy management costs. We propose Relaxed-2-Chord, a new design of the traditional Chord protocol, that is able to fit the routing tables with low latency nodes, doing a parasitic measurement of nodes' latency without adding any overhead. The solution that we present is a Distributed Hash Table system whose aim is to combine the routing efficiency and flexibility of the Chord protocol - i.e. a good degree/diameter tradeoff - and a provable optimal hop by hop latency. Our work is inspired by the recent Lookup-parasitic random sampling (LPRS) strategies which allow to improve the network stretch, that is, the ratio between the latency of two nodes on the overlay network and the unicast latency between those nodes. Relaxed-2-Chord reaches the same results as LPRS without introducing any overhead

We present a load-balancing technique that exploits the temporal coherence, among successive computation phases, in mesh-like computations to be mapped on a cluster of processors. Our method partitions the computation in balanced tasks and distributes them to independent processors through the prediction binary tree (PBT). At each new phase, current PBT is updated by using previous phase computing time (for each task) as (next phase) cost estimate. The PBT is designed so that it balances the load across the tasks as well as reduce {\em dependency} among processors for higher performances. Reducing dependency is obtained by using rectangular tiles of the mesh, of almost-square shape (i.e. one dimension is at most twice the other). By reducing dependency, one can reduce inter-processors communication or exploit local dependencies among tasks (such as data locality).Our strategy has been assessed on a significant problem, parallel ray tracing. Our implementation shows a good scalability, and improves over coherence-oblivious implementations. We report different measurements showing that granularity of tasks is a key point for the performances of our decomposition/mapping strategy.

Abstract The Chord protocol is the best known example of implementation of logarithmic complexity routing for structured peer‐to‐peer networks. Its routing algorithm, however, does not provide an optimal trade‐off between resources exploited (the size of the ‘finger table’) and performance (the average or worst‐case number of hops to reach destination). Cordasco et al. showed that a finger table based on Fibonacci distances provides lower number of hops with fewer table entries. In this paper we generalize this result, showing how to construct an improved finger table when the objective is to reduce the number of hops, possibly at the expense of an increased size of the finger table. Our results can also be exploited to guarantee low routing time in case a fraction of nodes fails. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract We propose a family of novel Chord‐based P2P schemes retaining all positive aspects that made Chord a popular topology for routing in P2P networks. The schemes, based on the Fibonacci number system, allow to simultaneously improve on the maximum/average number of hops for lookups and the routing table size per node. © 2008 Wiley Periodicals, Inc. NETWORKS, 2008

Co-located collaboration in classroom is the topic we tackle in this paper. We present COFFEE a tailorable collaborative environment that is designed for interactive, co-located (i.e. Face2Face) collaboration in classroom. We present the requirements for tailorability that have driven our design, CoFFEE architecture, some tools that have been deployed and discuss the latecomer management issue that is offered by the core of our architecture to all the tools that can be developed within the framework.

In this paper we present SynCoBook, a distributed system that offers the functionalities of a face-to-face cooperative bookmarking system and of a recommendation system. Our overall objective was to design and realize a practical tool that can be used in project-based learning, in the classroom, to participate in the WebQuests [12] or to cooperatively build an annotated Webliography, i.e., a set of URLs, organized and scaffolded with group annotations. Moreover, our system also offers advanced awareness tools as well as recommendations based on the items in the Webliography and their Google-related pages.

We define a proximity overlay network (PON) which allow to realize DHT systems whose aim is to combine routing efficiency - i.e. an optimal degree/diameter tradeoff - and proximity awareness. The proposed systems is parameterized with a positive integer s which measures the amount of flexibility offered by the network. Varying the value of s the system goes from a quite rigid network (s=2) which offer an optimal degree/diameter tradeoff. Increasing s to relatively low values allows to increase the flexibility of the network and consequently improves the stretch, that is, the ratio between the latency of two nodes on the overlay network and the unicast latency between those nodes. We are able to reconcile the conflict between the load balancing and proximity relationship by proving the efficiency of the main performance metrics. In particular we analytically prove that our system can result in lookup latencies proportional to the maximum latency of the underlying physical network, provided that the physical network has a power law latency expansion.

In this paper we present a prototyped system to enable the virtual exploration of a complex virtual environment. Our approach exploits Quest3D as main rendering engine, its output is conveyed toward users PDAs to allow them to explore using the PDA as a (mobile) interface to the virtual environment. An important aspect of the system is that it relies on an off-the-shelf PC and low end wireless network. Some early results showed that the prototype is able to easily manage 5 PDAs. Suggested fields of use of our system are virtual cultural heritage, educational virtual environments, videogames.

Techniques are developed for mapping structured data to an ensemble of parallel memory modules in a way that limits the number of conflicts, i.e., simultaneous accesses by distinct processors to the same memory module. The techniques determine, for any given conflict tolerance c, the smallest ensemble that allows one to store any n-node data structure "of type X" in such a way that no more than c nodes of a structure are stored on the same module. This goal is achieved by determining the smallest c-perfect universal graphs for data structures "of type X." Such a graph is the smallest graph that contains a homomorphic image of each n-node structure "of type X" with each node of the image holding < c nodes of the structure. In the current paper, "type X" refers to rooted binary trees and three array-like structures: chaotic arrays, ragged arrays, and rectangular arrays. For each of these families of data structures, the number of memory modules needed to achieve conflict tolerance c is determined to within constant factors.

The chord protocol is the best known example of implementation of logarithmic complexity routing for structured peer-to-peer networks. Its routing algorithm, however, does not provide an optimal trade-off between resources exploited (the size of the "finger table") and performance (the average or worst-case number of hops to reach destination). Cordasco et al. showed that a finger table based on Fibonacci distances provides lower number of hops with fewer table entries. In this paper, we generalize this result, showing how to construct an improved finger table when the objective is to reduce the number of hops, possibly at the expense of an increased size of the finger table. Our results can also be exploited to guarantee low routing time in case a fraction of nodes is assumed to fail.

The paper presents some experiences in developing a virtual environment using a videogame engine. It provides the details and the caveats met during development, with particular attentions to the architectural reconstruction problem, the textures resolution and the programmability. Some considerations are also reported from an historical point of view, emphasizing the importance of virtual reconstructions, and from a psychological point of view stressing how a narrative context enhances the learning process.

No abstract available.

We propose routing schemes that optimize the average number of hops for lookup requests in peer-to-peer (P2P) systems without adding any overhead to the system. Our work is inspired by the recently introduced variation of greedy routing, called neighbor-of-neighbor (NoN), which allows to get optimal average path length with respect to the degree. Our proposal has the advantage of first "limiting" and then "eliminating" the use of randomization. As a consequence, the NoN technique can be implemented with our schemes without adding any overhead. Analyzed networks include several popular topologies: chord, hypercube based networks, symphony, skip-graphs. Theoretical results and extensive simulations show that the proposed simplifications (while maintaining the original node degree) do not increase the average path length of the networks, which is often improved in practice. The improvement is obtained with no harm to the operational efficiency (e.g. stability, ease of programming, scalability, fault-tolerance) of the considered systems.

In this paper we study state-of-the-art technologies to design interactive and cooperative 3D environments that are based on videogame 3D engines. We provide, first, a categorization of videogame 3D engines from the point of view of their usage in creating interactive 3D worlds and show a comparison of the most important characteristics. Then, we show an example of how we used a commercial videogame engine to create an interactive an enjoyable visit to an archaeological site.

In this paper we present our experience in building a visual flle manager, VENNFS2, that offers to users an adaptive interface toward access to files. Our file manager was originally designed to overcome some of limitations of hierarchical file systems, since it allows users to categorize files in such a way that files may belong multiple categories at once. Based on the past history of the files that were opened and modified by the user, VENNFS2 graphically presents the user a small number of choices of the next file the user will modify. Some preliminary testing with interesting hints are also reported.

We describe a framework in Java to create sonification applications with minimum effort from the programmer and musician. Our tool, AMIFAST, offers a set of modules that can be easily assembled to produce sonification of off-line as well as on-line (i.e. real-time) applications. Moreover, the programmer can easily add new functionalities In AMIFaST, we included a sonification technique that we introduce here, Markov Chain Perturbation.

Greedy routing has been used in most of the proposed P2P networks because of several reasons. One of the main advantages is that greedy routing is very simple to implement and has some “implicit” fault-tolerance capabilities. It was however noticed that greedy routing usually produces paths of length larger than what would be required in a network of the given node degree. As an example some popular topologies like Chord have degree O(log n) and the greedy routing produces an average path length O(log n) whereas the lower bound is Ω(log n/log log n). The use of randomization allowed to show networks with optimal average path length. Recently a novel approach for routing in DHTs which improves on greedy routing has been proposed [4]. This approach, called NoN (Neighbors–of–Neighbors), substantially consists in making the greedy choice by looking not only at the neighbors of a node but at all the nodes at distance at most 2 from the node itself. The NoN approach together with the use of randomization in establishing the neighbors of the nodes which are present in the network, can optimally reduce the latency in several well known topologies. Hence the use of randomization, inspired by the Small-world idea introduced by Kleinberg [2], together with the NoN routing allows to maintain, to some extent, the advantages of greedy routing while optimizing the latency. Our goal is to retain the improvements given by the NoN routing over randomized networks, while eliminating the drawback in system overhead implied by this technique. In fact, randomization and NoN routing require the transmission to a node of its neighbors’s neighbors. While the authors in [4] argue that this can be done without extra cost by using keep-alive TCP messages, we eliminate the extracommunication at all and, similarly, eliminate the need of storing in each node its neighbors’s neighbors. To this aim we need to eliminate the random factor in establishing each neighbor of a node. In fact, determinism allows each node to calculate locally the neighbors of its neighbors. ∗ Work partially supported by EU RTN project ARACNE and by Italian FIRB WEBMINDS project

We present a prototypal file manager, VENNFS, that is designed to overcome some of the limitations of the current desktop interfaces, that are strongly based on hierarchical file systems. VENNFS allows users to place documents and categories on a plane so that files may belong to multiple categories at once, where proximity on the plane can represent similarity and time filtering is allowed.

We present an adaptive system for training and teaching. Our system integrates an adaptive training environment and a cooperative environment for exams both accessible via Internet by standard Java-enabled browsers. In this paper we present details on the architecture, describe the project with regard to the adaptive self-training part, and report on an experiment that demonstrates the effectiveness of the strategy: to draw attention of students to the topics they need to study. We experimented the system in a real case study with students attending a first year course, "Laboratorio di Informatica" of the Laurea degree in computer science in our University.

In this paper, we study efficient strategies for mapping onto parallel memory systems complete trees that are accessed by fixed templates (like complete subtrees, paths, or any combinations their of). These mappings are evaluated with respect to the following criteria: (1) the largest number of data items that can be accessed in parallel without memory conflicts; (2) the number of memory conflicts that can occur when accessing templates of size equal to the number of available memory modules, thereby exploiting the full parallelism of the system; (3) the complexity of the memory addressing scheme, i.e., the cost of retrieving the module where a given data item is mapped. We show that there exist trade-offs between these three criteria and the performance of different mapping strategies depends on the emphasis given on each of these criteria. More specifically, we describe an algorithm for mapping complete binary trees of height H onto M memory modules and prove that it achieves the following performance results: (1) conflict-free access to complete subtrees of size K and paths of size N such that N + K - [log K] /spl les/ M; (2) at most 1 conflict in accessing complete subtrees and paths of size M; (3) O(K/M + c) conflicts when accessing a composite template of K nodes consisting of c disjoint subsets, each subset being a complete subtree, or a path or a set of consecutive nodes in a level of the tree.

In this paper we study strategies for mapping complete tree data structures, that are accessed by fixed templates, onto parallel memory systems. These mappings are evaluated with respect to the following three different criteria: (i) the number of memory conflicts that can occur in a parallel access to the data structure; (ii) the largest number of elements that can be accessed in parallel without memory conflicts; (iii) the complexity of the memory addressing scheme. We show that there exist trade-offs between these criteria. We describe an algorithm COLOR for mapping complete trees onto EA memory modules and prove that it achieves the following performance: (i) conflict-free access to complete subtrees of size K and paths of size N, for M/spl ges/N+K-[log K]; (ii) at most 1 conflict when accessing complete subtrees and paths of size M; (iii) O((K/M)+c) conflicts when accessing a composite template of K nodes consisting of c disjoint subsets, each being a complete subtree, a path or a set of consecutive nodes in a level of the tree.

We present a report on JSEB (Java Scalable Service Builder) whose goal is to offer programmers a tool that can be used to efficiently add scalability and fault-tolerance to a replicated service in cluster(s) of workstations.

We describe several Web-based visualizations of processes obtained using 3WPS, a distributed framework to build systems that monitor and interact with a process by a 3D interface accessible via WWW.

Hypercube is a popular interconnection network whose size must be a power of 2. Several interconnection networks have been proposed that do not suffer this limitation. Among them the extended Fibonacci cubes are based on the same sequence of the Fibonacci cubes and share many appealing structural properties. In this paper, we show how Extended Fibonacci Cubes can be seen as (Cartesian) product graphs whose components are hypercubes and Fibonacci Cubes. By exposing this property, we prove a conjecture that there are no distinct Extended Fibonacci Cubes (except the trivial ones) with the same number of nodes. Our result further validates the motivations behind the proposal of this interconnection network as a flexible alternative to hypercubes.

Electronic Commerce (EC) is currently one of the fastest growing and most practically relevant application areas of distributed systems technologies. It is based on the economic aspects of commercial trading patterns combined with distributed computing systems technology. It is a market environment that is characterized by low transaction costs, a large number of market participants, and easy online access to services and goods offered. It also implies a set of rules and policies for the successful organization of business transactions. EC involves more than simple online transactions, it encompasses diverse activities as conducting market research, identifying opportunities and partners, cultivating relationships with customers and suppliers, document exchange and customer modeling. Our paper deals with the latter aspect of EC. We introduce here a model for developing a symmetric adaptive system for EC on the World Wide Web. Our main contribution is that the model is, by all means, symmetric: we model both customers and goods and make both their profiles change as a consequence of a customer buying a certain product. The symmetry in our model greatly simplifies the approach and the queries, giving some insights on the formalization of the allowed queries that were, in way, unexpected. Furthermore, the model itself can provide an easy-to-evaluate measure for the confidence in adapting its response to any given customer and is able to provide useful feedback to the manager, then allowing, so to speak, "manual adjustment" that can help the behaviour of the system in the future.

We study fine-grain computation on the Reconfigurable Ring of Processors (RRP), a parallel architecture whose processing elements (PEs) are interconnected via a multiline reconfigurable bus, each of whose lines has one-packet width and can be configured, independently of other lines, to establish an arbitrary PE-to-PE connection. We present a "cooperative" message passing protocol that will, in the presence of suitable implementation technology, endow an RRP with message latency that is logarithmic in the number of PEs a message passes over in transit. Our study focuses on the computational consequences of such latency in such an architecture. Our main results prove that: (1) an N-PE RRP can execute a sweep up or down an N-leaf complete binary tree in time proportional to log N log log N;(2) a broad range of N-PE architectures, including N-PE RRPs, require time proportional to log N log log N to perform such a sweep.

In this paper we consider the Supercube, a new interconnection network derived from the hypercube. The Supercube, introduced by A. Sen (1989), has the same diameter and connectivity as a Hypercube but can be realized for any number of nodes, not only powers of 2. We study the Supercube's ability to execute parallel programs, using graph-embedding techniques. We show that complete binary trees and bidimensional meshes (with a side length power of 2) are spanning subgraphs of the Supercube. We then prove that the Supercube is Hamiltonian and, when the number of nodes is not a power of 2, it contains all cycles of length greater than 3 as subgraphs.>