Selecting communication media for distributed communities

Within the 'Virtual Mobility and Distributed Laboratories' project three naturalistic case studies of distributed research communities were conducted with a focus on the communication media used. The findings provide insight into relationships between the different media that the communities selected, and the different activities to which these media contributed. It is suggested that these findings are also relevant for distributed groups in which collaborative learning is the primary aim. A framework is presented for understanding and recommending selections of media for particular kinds of tasks, which is derived by integrating Media‐richness Theory and Activity Theory. This framework indicates how task/media fit may be achieved while taking into account the evolving character of activities in a distributed community. Some implications of the framework for collaborative distance learning are highlighted.\ud \u

Asynchronous Distributed Averaging on Communication Networks

Distributed algorithms for averaging have attracted interest in the control and sensing literature. However, previous works have not addressed some practical concerns that will arise in actual implementations on packet-switched communication networks such as the Internet. In this paper, we present several implementable algorithms that are robust to asynchronism and dynamic topology changes. The algorithms are completely distributed and do not require any global coordination. In addition, they can be proven to converge under very general asynchronous timing assumptions. Our results are verified by both simulation and experiments on Planetlab, a real-world TCP/IP network. We also present some extensions that are likely to be useful in applications