P eer-to-peer (P2P) file sharing networks are an important medium for the distribution of information goods.However, there is little empirical research into the optimal design of these networks under real-world conditions. Early speculation about the behavior of P2P networks has focused on the role that positive network externalities play in improving performance as the network grows. However, negative network externalities also arise in P2P networks because of the consumption of scarce network resources or an increased propensity of users to free ride in larger networks, and the impact of these negative network externalities-while potentially important-has received far less attention.Our research addresses this gap in understanding by measuring the impact of both positive and negative network externalities on the optimal size of P2P networks. Our research uses a unique dataset collected from the six most popular OpenNap P2P networks between December 19, 2000, and April 22, 2001. We find that users contribute additional value to the network at a decreasing rate and impose costs on the network at an increasing rate, while the network increases in size. Our results also suggest that users are less likely to contribute resources to the network as the network size increases. Together, these results suggest that the optimal size of these centralized P2P networks is bounded-At some point the costs that a marginal user imposes on the network will exceed the value they provide to the network. This finding is in contrast to early predictions that larger P2P networks would always provide more value to users than smaller networks. Finally, these results also highlight the importance of considering user incentives-an important determinant of resource sharing in P2P networks-in network design.
P eer-to-peer (P2P) file sharing networks are an important medium for the distribution of information goods. However, there is little empirical research into the optimal design of these networks under real-world conditions. Early speculation about the behavior of P2P networks has focused on the role that positive network externalities play in improving performance as the network grows. However, negative network externalities also arise in P2P networks because of the consumption of scarce network resources or an increased propensity of users to free ride in larger networks, and the impact of these negative network externalities-while potentially important-has received far less attention.Our research addresses this gap in understanding by measuring the impact of both positive and negative network externalities on the optimal size of P2P networks. Our research uses a unique dataset collected from the six most popular OpenNap P2P networks between December 19, 2000, and April 22, 2001. We find that users contribute additional value to the network at a decreasing rate and impose costs on the network at an increasing rate, while the network increases in size. Our results also suggest that users are less likely to contribute resources to the network as the network size increases. Together, these results suggest that the optimal size of these centralized P2P networks is bounded-At some point the costs that a marginal user imposes on the network will exceed the value they provide to the network. This finding is in contrast to early predictions that larger P2P networks would always provide more value to users than smaller networks. Finally, these results also highlight the importance of considering user incentives-an important determinant of resource sharing in P2P networks-in network design.
Improving the information retrieval (IR) performance of peer-to-peer networks is an important and challenging problem. Recently, the computer science literature has attempted to address this problem by improving IR search algorithms. However, in peer-to-peer networks, IR performance is determined by both technology and user behavior, and very little attention has been paid in the literature to improving IR performance through incentives to change user behavior.We address this gap by combining the club goods economics literature and the IR literature to propose a next generation file sharing architecture. Using the popular Gnutella 0.6 architecture as context, we conceptualize a Gnutella ultrapeer and its local network of leaf nodes as a "club" (in economic terms). We specify an information retrieval-based utility model for a peer to determine which clubs to join, for a club to manage its membership, and for a club to determine to which other clubs they should connect.We simulate the performance of our model using a unique real-world dataset collected from the Gnutella 0.6 network. These simulations show that our club model accomplishes both performance goals. First, peers are self-organized into communities of interest -in our club model peers are 85% more likely to be able to obtain content from their local club than they are in the current Gnutella 0.6 architecture. Second, peers have increased incentives to share content -our model shows that peers who share can increase their recall performance by nearly five times over the performance offered to free-riders. We also show that the benefits provided by our club model outweigh the added protocol overhead imposed on the network for the most valuable peers.
Improving the information retrieval (IR) performance of peer-to-peer networks is an important and challenging problem. Recently, the computer science literature has attempted to address this problem by improving IR search algorithms. However, in peer-to-peer networks, IR performance is determined by both technology and user behavior, and very little attention has been paid in the literature to improving IR performance through incentives to change user behavior.We address this gap by combining the club goods economics literature and the IR literature to propose a next generation file sharing architecture. Using the popular Gnutella 0.6 architecture as context, we conceptualize a Gnutella ultrapeer and its local network of leaf nodes as a "club" (in economic terms). We specify an information retrieval-based utility model for a peer to determine which clubs to join, for a club to manage its membership, and for a club to determine to which other clubs they should connect.We simulate the performance of our model using a unique real-world dataset collected from the Gnutella 0.6 network. These simulations show that our club model accomplishes both performance goals. First, peers are self-organized into communities of interest -in our club model peers are 85% more likely to be able to obtain content from their local club than they are in the current Gnutella 0.6 architecture. Second, peers have increased incentives to share content -our model shows that peers who share can increase their recall performance by nearly five times over the performance offered to free-riders. We also show that the benefits provided by our club model outweigh the added protocol overhead imposed on the network for the most valuable peers.
Private sector's role in community development is often seen as a supporting organization with its own interests. Generally, a company chooses to support a particular community according to the company's strategic topic. This top-down approach benefits the company in many ways including effective operations and communications. However, the effectiveness on sustainable development of communities is still questionable. As each strategic topic is heavily influenced by the company's reasoning, this approach often lacks in dimensions, has narrow focus, and therefore disconnects with the community real needs. This results in little contributions to the sustainability of the communities. This proposal proposes a different approach through a case study with two artisanal fishery communities. With this new approach, the company acted as a bridging organization working closely with the communities together with other stakeholders to truly understand their needs. The company, then, facilitated them in designing and implementing their own sustainable solutions. This requires changes in the company operations as well as acquiring new knowledge for its outreach team. The findings demonstrated a successful case of community development towards selfsustainable resource management. The analysis of these findings helps the company to strike a balance between "company-centric" and "community-centric" approach in the future.
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