The quest to build scalable data center networks has driven much of the innovation in the networking community in recent decades. But the one-size-fits-all service model offered by these networks does not meet the needs of every application. In response, cloud providers have started to design custom clusters to support the specialized workloads used in finance, AI, high-performance computing, and other areas.

The current Web caching infrastructure, though it has a number of performance benefits for clients and network providers, does not meet publishers' requirements. We argue that to satisfy these requirements, caches should be enhanced in both the data and control planes. In the data plane, caches will dynamically generate content for clients by running code provided by publishers. In the control plane, caches will return logs of client accesses to publishers. In this paper, we introduce Gemini, a system which has both of these capabilities, and discuss two of its key components: security and incremental deployment. Since Gemini caches are deeply involved in content preparation and logging, ensuring that they perform correctly is vital. Traditional end-to-end security mechanisms are not sufficient to protect clients and publishers, so we introduce a new security model which consists of two pieces: an authorization mechanism and a verification mechanism. The former allows a publisher to authorize a set of caches to run its code and serve its content, while the latter allows clients and publishers to probabilistically verify that authorized caches are operating correctly. Because it is unrealistic to assume that Gemini caches will be deployed everywhere simultaneously, we have designed the system to be incrementally deployable and to coexist with legacy clients, caches, and servers. Finally, we describe our implementation of Gemini and present preliminary performance results.

As a growing number of Web sites introduce mirrors to increase throughput, the challenge for clients is determining which mirror will offer the best performance when a document is to be retrieved. We present findings from measuring 9 clients scattered throughout the United States retrieving over 490,000 documents from 47 production Web servers which mirror three different Web sites. We have several interesting findings that may aid in the design of protocols for choosing among mirror servers. Though server performance varies widely, we have observed that a server's performance relative to other servers is more stable and is independent of time scale. In addition, a change in an individual server's transfer time is not a strong indicator that its performance relative to other servers has changed. Finally, we have found that clients wishing to achieve near-optimal performance may only need to consider a small number of servers rather than all mirrors of a particular site.

We propose a third-party value-added services framework for enhancing the performance of reliable multicast protocols.In this framework, a value-added service provider will place servers called waypoints throughout ISPs' networks.Waypoints run a fully distributed, dynamic algorithm to determine which multicast groups to join.Having joined a group, a waypoint participates in the error recovery protocol, supplying repairs to receivers.From the application's perspective, waypoints appear to be additional application endpoints in the network.Waypoints seamlessly interoperate with current reliable multicast algorithms with only a minor change to receivers and no changes to routers.In our implementation, receivers and waypoints use STORM, a structure-based error recovery protocol.The waypoint recovery service is not limited to one error recovery protocol, and can be extended to enhance other reliable multicast protocols.Results from simulation experiments are presented to evaluate the potential benefits of theproposed scheme.We find that when multicast group members are isolated from each other, a waypoint recovery service can significantly enhance receivers' performance.