Recent Projects


Distributed Uplink Scheduling in CDMA Networks. This is a project in collaboration with Ashwin Sridharan and partially funded by Sprint Labs, which explores issues that arise in CDMA networks when devices (mobiles) are afforded some level of independence in making transmission decisions, instead of being under the tight control of a base station. Giving mobile devices some flexibility in deciding when to transmit and at what rate is increasingly desirable because of the diversity of applications they are now capable of running and that exhibit a broad range of communication requirements. However, allowing devices to make individually controlled transmission decisions may affect global system performance, and one of the goals of this project is to explore this trade-off in a number of different settings.

Related Publications


Towards Large-Scale Flat Networks. This is a project sponsored by and in collaboration with Siemens. Flat networks like Ethernet have many advantages in terms of simplicity and flexibility, e.g., plug-&-play and little or no configuration requirements. However, they suffer from a number of potential scalability limitations, which have limited the scope of their deployments and promoted the use of (hierarchical) routed solutions to build large networks, the Internet being a case in point. This work is not aimed at replacing the Internet with one big flat network, but it explores various issues aimed at improving the scalability of flat networks. In particular, it targets two important factors that affect scalability: (i) reliance on broadcast for address discovery; and (ii) loop prevention during path changes.

Related Publications


Data plane aggregation. This work was supported through NSF grant ITR-0085930 and aimed at developing a better understanding of the relations that exist between QoS provided as some aggregate level, e.g., a service class as in the Differentiated Services model, and the actual QoS that individual users experience. Of particular interest are models that allow explicit evaluation of individual QoS measures, and their use in identifying characteristics of user traffic that can result in significant differences between individual and aggregate QoS measures. This led to the development of models that allow the evaluation of the loss probability experienced by individual connections and when and why it differs from the aggregate loss probability. The environment that is assumed consists of a single FIFO queue where all the individual users belonging to the same service class are multiplexed. A separate but related perspective is that of security, namely, understanding the extent to which a single (or a few) user can affect the performance of many other users. In that context, we investigated the extent to which more sophisticated attack schemes can defeat existing mechanisms, and used that understanding towards developing better defenses.

Related Publications