Distributed Computing is a new form of online collaboration; such projects divide a large computational problem into small tasks that are sent out over the Internet to be completed on personal computers. Millions of people all over the world participate voluntarily in such projects, providing computing resources that would otherwise cost millions of dollars. However, Distributed Computing only works if many people participate. The technical challenge is to slice a problem into thousands of tiny pieces that can be solved independently, and then to reassemble the solutions. The social problem is how to find all those widely dispersed computers and persuade their owners to participate. This article examines what makes a collaborative Distributed Computing project successful. We report on data from a quantitative survey and a qualitative study of participants on several online forums, and discuss and analyze Distributed Computing using Arquilla and Ronfeldt's (2001) five‐level network organization framework.
Abstract. In this paper, we present a feedback-based system for managing trust and detecting malicious behavior in autonomically behaving networks. Like other distributed trust management systems, nodes rate the interactions they have with other nodes and this information is stored in a distributed fashion.Two crucial insights motivate our work. We recognize as separate entities the trust placed in a node, reputation, and the trust placed in the recommendations made by a node, credibility. We also introduce the concept of quality of a trust rating. Together, these two factors enhance the ability of each node to decide how much confidence it can place in a rating provided to it by a third party.We implement our scheme on a structured P2P network, Pastry, though our results can be extended to generic autonomic communication systems. Experimental results considering different models for malicious behavior indicate the contexts in which the RQC scheme performs better than existing schemes.
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