Abstract. Desktop grids use the free resources in Intranet and Internet environments for large-scale computation and storage. While desktop grids offer a high return on investment, one critical issue is the validation of results returned by participating hosts. Several mechanisms for result validation have been previously proposed. However, the characterization of errors is poorly understood. To study error rates, we implemented and deployed a desktop grid application across several thousand hosts distributed over the Internet. We then analyzed the results to give quantitative and empirical characterization of errors stemming from input or output (I/O) failures. We find that in practice, error rates are widespread across hosts but occur relatively infrequently. Moreover, we find that error rates tend to not be stationary over time nor correlated between hosts. In light of these characterization results, we evaluated state-ofthe-art error detection mechanisms and describe the trade-offs for using each mechanism.

The success of grid computing in open environments like the Internet is highly dependent on the adoption of mechanisms to detect failures and malicious sabotage attempts. It is also required to maintain a trust management system that permits one to distinguish the trustable from the non-trustable participants in a global computation. Without these mechanisms, users with data-critical applications will never rely on desktop grids, and will rather prefer to support higher costs to run their computations in closed and secure computing systems.This paper discusses the topics of sabotage-tolerance and trust management. After reviewing the state-of-the-art, we present two novel techniques: a mechanism for sabotage detection and a protocol for distributed trust management. The proposed techniques are targeted at the paradigm of volunteer-based computing commonly used on desktop grids.

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Current infrastructures for Volunteer Computing follow a centralized architecture for data distribution, creating a potential bottleneck when tasks require large input files or the central server has limited bandwidth. In this paper we propose two new data models for Berkeley Open Infrastructure for Network Computing (BOINC): an approach based on the popular BitTorrent protocol; and a Content Delivery Network approach. While the latter remains on a theoretical level, we developed a prototype that adds BitTorrent functionality for task distribution and conducted medium-scale tests of the environment. Our preliminary results indicate that the BitTorrent client had a negligible influence on the BOINC client's computation time. The BOINC server showed an unexpectedly low bandwidth output when seeding the file, as well as spikes on CPU usage. This paper discusses the tests that were performed, how they were evaluated, as well as some improvements that could be made in future research on both approaches.

Abstract. This paper presents an overview of JAMES, a J a va-based platform of mobile agents that is mainly oriented for the management o f d a t a and telecommunication networks. This platform has been developed on behalf of a Eureka Project !1921 and the project partners are Siemens SA, University of Coimbra and Siemens AG. We describe the main architecture of the platform giving more emphasis to the most important features. To s h o w the e ectiveness of some of the techniques that have been implemented we will present some performance results that compare the JAMES platform with the Aglets Workbench. The main target of our platform is network management and telecommunication applications. In this line, we h a ve done a Java-based implementation of SNMP that has been integrated within the platform. The industrial partners of our project i.e. Siemens S.A. have d e v eloped a prototype application for TMN performance management. Although it is still a prototype it is being used to validate the technological advantages of using mobile agents in the management of telecommunication networks.

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