Francesc Giné

Guidelines for the final year project assessment in engineering

This paper presents an efficient and objective procedure for the outcome-based assessment of engineering final year projects (FYP). The procedure, consisting of 6 steps, can easily be customized for different engineering curricula. A User Guide has been developed to help institutions create their own FYP assessment system. The guide includes the assessment procedure and aids for its implementation. Particularly, a set of FYP-oriented observable descriptors for Tuning outcomes was defined. The end-products of the proposed assessment procedure are a set of assessment reports that the evaluator agent/s must fulfil per milestone, marking the level reached by the student at every descriptor (0: unacceptable, 1: minimum acceptable, 2: good, 3: excellent). These marks are then gathered together in an overall assessment sheet showing, for every learning outcome, the evolution along the assessment milestones of the level reached by the student at any descriptor. This sheet is a very powerful tool for setting the final mark. All assessment agents use the same list of descriptors and the same levels of acquisition, thus improving the consistency, traceability and global quality of the assessment process.

A secure elliptic curve-based RFID protocol

Nowadays, the use of Radio Frequency Identification (RFID) systems in industry and stores has increased. Nevertheless, some of these systems present privacy problems that may discourage potential users. Hence, high confidence and effient privacy protocols are urgently needed. Previous studies in the literature proposed schemes that are proven to be secure, but they have scalability problems. A feasible and scalable protocol to guarantee privacy is presented in this paper. The proposed protocol uses elliptic curve cryptography combined with a zero knowledge-based authentication scheme. An analysis to prove the system secure, and even forward secure is also provided.

CISNE: a new integral approach for scheduling parallel applications on non-dedicated clusters

Our main interest is oriented towards keeping both local and parallel jobs together in a non-dedicated cluster. In order to obtain some profits from the parallel applications, it is important to consider time and space sharing as a mean to enhance the scheduling decisions. In this work, we introduce an integral scheduling system for non-dedicated clusters, termed CISNE. It includes both a previously developed dynamic coscheduling system and a space-sharing job scheduler to make better scheduling decisions than can be made separately. CISNE allows multiple parallel applications to be executed concurrently in a non dedicated Linux cluster with a good performance, as much from the point of view of the local user as that of the parallel application user. This is possible without disturbing the local user and obtaining profits for the parallel user. The good performance of CISNE has been evaluated in a Linux cluster.

CoDiP2P: A Peer-to-Peer Architecture for Sharing Computing Resources

Peer-to-Peer (P2P) computing, the harnessing of idle compute cycles through the Internet, offers new research challenges in the domain of distributed computing. This paper presents CoDiP2P, a Computing Distributed architecture using the P2P paradigm. CoDiP2P allows computing resources from ordinary users to be shared in an open access by means of creating dynamic areas of computing resources in a completely distributed, scalable and fault tolerant way. This paper discusses its system architecture and evaluates its functionality by means of simulation.

Coscheduling and Multiprogramming Level in a Non-dedicated Cluster

Our interest is oriented towards keeping both local and parallel jobs together in a time-sharing non-dedicated cluster. In such systems, dynamic coscheduling techniques, without memory restriction, that consider the MultiProgramming Level for parallel applications (MPL), is a main goal in current cluster research. In this paper, a new technique called Cooperating Coscheduling (CCS), that combines a dynamic coscheduling system and a resource balancing schema, is applied.

Analyzing locality over a P2P computing architecture

A characteristic of Peer-to-Peer (P2P) computing networks is their huge number of different computational resources scattered across the Internet. Gathering peers into markets according to their multi-attribute computational resources makes it easier to manage these environments. This solution is known as market overlay. In this context, the closeness of the markets with similar resources, known as locality, is a key feature for ensuring good P2P resource management. Thus, the locality feature over a market overlay allows a lack of resources in a given market to be compensated quickly by any other market with similar resources, whenever these are close to each other. Consequently, locality becomes an essential challenge. This paper addresses the analysis of the locality of P2P market over-lays. According to this, a new procedure for measuring locality is applied together with an extensive analysis of some well-known structured P2P overlays. Based on this analysis, a new P2P computing architecture, named DisCoP, oriented towards optimizing locality is proposed. Our proposal gathers the peers into markets according to their computational resources. A Hilbert function is used to arrange multi-attribute markets in an ordered and mono-dimensional space and the markets are linked by means of a Bruijn graph. In order to maintain the DisCoP locality whenever the overlay is not completed, a solution based on the virtualization of markets is also proposed. Finally, the DisCoP locality is tested together with the proposed virtualization method for approximate searches over uncompleted overlays. The simulation results show that approximate searches exploit the DisCoP locality efficiently.

Implementing Explicit and Implicit Coscheduling in a PVM Environment

Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system when a parallel job is executed with local workloads, balancing parallel efficiency against the local interactive response. Explicit and implicit coscheduling techniques in a PVM-Linux NOW (or cluster) has been implemented. Their performance and overheads executing local tasks and representative distributed benchmarks have been analyzed and compared.

Predictive Coscheduling Implementation in a Non-dedicated Linux Cluster

Our research is focussed on keeping both local and parallel jobs together in a non-dedicated cluster or NOW (Network Of Workstations) and efficiently scheduling them by means of coscheduling mechanisms. A real implementation of a predictive coscheduling technique in a Linux cluster is presented in this article and its performance analyzed and compared with other coscheduling algorithms in the literature.

A Scalable Hybrid P2P System for MMOFPS

Nowadays, MMOGs are extensively used as they provide the ability for centralized gaming with many players. MMOGs can be classified into three different categories: MMRPOG that are role games, MMORTS based on real-time strategy games and MMOFPS named as first person shooter games. The computational requirements of these categories are different. In this paper we focus on MMOFPS, whose main gaming requirements are low latency values and scalability. We propose a new system called OnDeGaS (On Demand Game Service), that combines the functionalities of a centralized server infrastructure with a distributed P2P topology, in such a way that the system can grow at any moment according to the existing demand, by maintaining QoS. We evaluate the effectiveness of the OnDeGaS through simulation. The results show that the system is able to scale, while the average latency of the whole system is always maintained under an acceptable threshold. We also probe the benefits provided by the fault tolerance mechanism included in the system.

Coscheduling under Memory Constraints in a NOW Environment

Networks of Workstations (NOW) have become important and cost-effective parallel platforms for scientific computations. In practice, a NOW system is heterogeneous and non-dedicated. These two unique factors make scheduling policies on multiprocessor/multicomputer systems unsuitable for NOWs. However, the coscheduling principle is still an important basis for parallel process scheduling in these environments. We propose a new coscheduling algorithm for reducing the number of page faults across a non-dedicated cluster by increasing the execution priority of parallel tasks with lower page fault rate. Our method is based on knowledge of events obtained during execution, as communication activity and memory size of every task. The performance of our proposal has been analyzed and compared with other coscheduling implementations by means of simulation.