Abstract. Application layer networks are software architectures that allow the provisioning of services requiring a huge amount of resources by connecting large numbers of individual computers, like in Grid or Peer-to-Peer computing. Controlling the resource allocation in those networks is nearly impossible using a centralized arbitrator. The network simulation project CATNET will evaluate a decentralized mechanism for resource allocation, which is based on the economic paradigm of the Catallaxy, against a centralized mechanism using an arbitrator object. In both versions, software agents buy and sell network services and resources to and from each other. The economic model is based on self-interested maximization of utility and self-interested cooperation between agents. This article describes the setup of money and message ows both for centralized and decentralized coordination in comparison.

Abstract. Scalability is a key design challenge that routing protocols for ad hoc networks must properly address to maintain the network performance when the number of nodes increases. We focus on this issue by reducing the amount of control information messages that a link state proactive routing algorithm introduces to the network. Our proposal is based on the observation that a high percentage of those messages is always the same. Therefore, we introduce a new mechanism that can predict the control messages that nodes need for building an accurate map of the network topology so they can avoid resending the same messages. This prediction mechanism, applied to OLSR protocol, could be used to reduce the number of messages transmitted through the network and to save computational processing and energy consumption. Our proposal is independent of the OLSR configuration parameters and it can dynamically self-adapt to network changes.

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Abstract-We propose an approach for predicting group formations, to address the problem of automating the incorporation of group awareness into CSCL applications. Contextual information can enable the construction of applications that effectively assist the group members to automatically communicate in synchronous and collocated collaborative learning activities. We used data traces collected from the study of students' behavior to train and test an intelligent system. Results have shown that context-information can be effectively used as a basis for a middleware for a dynamic group management. Inferring group membership is technically viable and can be used in real world settings.