If a source sends packets to a destination that is moving and changing IP addresses, the contents of the packet may refer to a destination address that is stale, and the packet may be discarded, or redirected by some special-purpose entity in the network known as an agent. The source may be informed of the change in the IP address of the destination as well, so that future packets can be sent directly to its new location. As users move inside a subnetwork, changes need to take place at one or more switches tracking that user, in an attempt to maintain connectivity to the user at all times.

Tracking updates may take a long time to arrive at the agents, end-hosts and switches, which can result in a temporary loss of connectivity to the user. This becomes particularly noticeable when users are engaged in streaming multimedia applications, and may even result in the abortion of TCP sessions. Furthermore, current technologies significantly limit the number of individual addresses that can be tracked by a device built at a reasonable cost. Therefore, any solution to support mobility must deal with inherent delays caused by distances between the moving user and entities in the network that track and assist the user, as well as limitations of the current technology in terms of cost and performance.

In this paper we assess, design and optimize schemes to support mobility in the Internet. These schemes exploit techniques called address-lookahead, packet n-casting, transparent learning and light-weight explicit registration. Via numerical simulation, we demonstrate considerable improvements in the user-perceived quality of applications, at no significant increase in cost. For example, 40% more voice calls can experience a high level of quality, at the cost of only a 3% increase in the bandwidth consumption in the Internet.