Lixia Zhang

Named Data Networking (NDN) is one of five projects funded by the U.S. National Science Foundation under its Future Internet Architecture Program. NDN has its roots in an earlier project, Content-Centric Networking (CCN), which Van Jacobson first publicly presented in 2006. The NDN project investigates Jacobson's proposed evolution from today's host-centric network architecture (IP) to a data-centric network architecture (NDN). This conceptually simple shift has far-reaching implications for how we design, develop, deploy, and use networks and applications. We describe the motivation and vision of this new architecture, and its basic components and operations. We also provide a snapshot of its current design, development status, and research challenges. More information about the project, including prototype implementations, publications, and annual reports, is available on named-data.net.

In recent years, a wide variety of mobile computing devices has emerged, including portables, palmtops, and personal digital assistants. Providing adequate network connectivity for these devices will require a new generation of wireless LAN technology. In this paper we study media access protocols for a single channel wireless LAN being developed at Xerox Corporation's Palo Alto Research Center. We start with the MACA media access protocol first proposed by Karn [9] and later refined by Biba [3] which uses an RTS-CTS-DATA packet exchange and binary exponential back-off. Using packet-level simulations, we examine various performance and design issues in such protocols. Our analysis leads to a new protocol, MACAW, which uses an RTS-CTS-DS-DATA-ACK message exchange and includes a significantly different backoff algorithm.

In recent years, a wide variety of mobile computing devices has emerged, including portables, palmtops, and personal digital assistants. Providing adequate network connectivity for these devices will require a new generation of wireless LAN technology. In this paper we study media access protocols for a single channel wireless LAN being developed at Xerox Corporation's Palo Alto Research Center. We start with the MACA media access protocol first proposed by Karn [9] and later refined by Biba [3] which uses an RTS-CTS-DATA packet exchange and binary exponential back-off. Using packet-level simulations, we examine various performance and design issues in such protocols. Our analysis leads to a new protocol, MACAW, which uses an RTS-CTS-DS-DATA-ACK message exchange and includes a significantly different backoff algorithm.

Sink mobility brings new challenges to large-scale sensor networking. It suggests that information about each mobile sink's location be continuously propagated through the sensor field to keep all sensor nodes updated with the direction of forwarding future data reports. Unfortunately frequent location updates from multiple sinks can lead to both excessive drain of sensors' limited battery power supply and increased collisions in wireless transmissions. In this paper we describe TTDD, a Two-Tier Data Dissemination approach that provides scalable and efficient data delivery to multiple mobile sinks. Each data source in TTDD proactively builds a grid structure which enables mobile sinks to continuously receive data on the move by flooding queries within a local cell only. TTDD's design exploits the fact that sensor nodes are stationary and location-aware to construct and maintain the grid structures with low overhead. We have evaluated TTDD performance through both analysis and extensive simulation experiments. Our results show that TTDD handles multiple mobile sinks efficiently with performance comparable with that of stationary sinks.

In this paper we present PEAS, a robust energy-conserving protocol that can build long-lived, resilient sensor networks using a very large number of small sensors with short battery lifetime. PEAS extends the network lifetime by maintaining a necessary set of working nodes and turning off redundant ones. PEAS operations are based on individual node's observation of the local environment and do not require any node to maintain per neighbor node state. PEAS performance possesses a high degree of robustness in the presence of both node power depletions and unexpected failures. Our simulations and analysis show that PEAS can maintain an adequate working node density in the face of up to 38% node failures, and it can maintain roughly a constant overhead level under various deployment conditions ranging from sparse to very dense node deployment by using less than 1% of total energy consumption. As a result, PEAS can extend a sensor network's functioning time in linear proportion to the deployed sensor population.