Cloud and AI/ML workloads are posing unprecedented new requirements on the wide-area network: it must combine strict availability, massive growth, and feature agility. It became increasingly clear that traditional WAN designs were ill-equipped to adapt to these requirements.

In this paper, we consider migration of virtual machines in a data center to minimize network power consumption. Network power is consumed when switches are turned on, and conserved when they are turned off; the optimization problem then is to site virtual machines within the data center to achieve connectivity and desired bandwidth while turning on as few switches as possible. Depending upon specifics of the permissible optimization, and topology considerations within the data center, this optimization problem can be easy, or hard. We fully taxonomize the suite of optimization problems in this general space, showing that the most complex problem (placement and routing of virtual machines in a topologically-rich data center network) is NP- hard. We offer a placement technique based on a classic VLSI placement algorithm, and demonstrate efficacy on a trace set derived from a production data center.

Researchers involved in designing network services and protocols rely on results from simulation and emulation environments to understand their application performance and scalability. To better understand the behavior of these applications and predict their performance when deployed on the actual Internet, the generated topologies must closely match real network characteristics, not just in terms of graph structure (node interconnectivity) but also with respect to various node and link annotations. Relevant annotations include link latencies, AS membership and whether a router is a peering or internal router. Finally, it should be possible to rescale a given topology to a variety of sizes while still maintaining its essential characteristics.

Researchers have proposed a variety of metrics to measure important graph properties, for instance, in social, biological, and computer networks. Values for a particular graph metric may capture a graph's resilience to failure or its routing efficiency. Knowledge of appropriate metric values may influence the engineering of future topologies, repair strategies in the face of failure, and understanding of fundamental properties of existing networks. Unfortunately, there are typically no algorithms to generate graphs matching one or more proposed metrics and there is little understanding of the relationships among individual metrics or their applicability to different settings. We present a new, systematic approach for analyzing network topologies. We first introduce the dK-series of probability distributions specifying all degree correlations within d-sized subgraphs of a given graph G. Increasing values of d capture progressively more properties of G at the cost of more complex representation of the probability distribution. Using this series, we can quantitatively measure the distance between two graphs and construct random graphs that accurately reproduce virtually all metrics proposed in the literature. The nature of the dK-series implies that it will also capture any future metrics that may be proposed. Using our approach, we construct graphs for d=0, 1, 2, 3 and demonstrate that these graphs reproduce, with increasing accuracy, important properties of measured and modeled Internet topologies. We find that the d=2 case is sufficient for most practical purposes, while d=3 essentially reconstructs the Internet AS-and router-level topologies exactly. We hope that a systematic method to analyze and synthesize topologies offers a significant improvement to the set of tools available to network topology and protocol researchers.

Session initiation protocol (SIP) is being widely adopted for VoIP, IM and other collaborative applications due to its simple yet rich functional design. However, one of the main drawbacks has been its per-application deployment (each application using its own SIP stack), leading to narrowly focused development of SIP based services. In this paper, we propose a client-side SIP service and supporting network infrastructure blocks that provide unified mechanisms to execute generic SIP functions. The composition of these building blocks allows for creating richer applications, e.g. a conferencing server coupled with a gaming server provides dynamic conferencing between current occupants of a game room. The main feature of our framework is its availability to all applications including the ones not inherently based on SIP. Also, the SIP service API is designed to be extensible and in addition to providing novel higher level functional primitives like adhoc conferencing and seamless transition of sessions, it also exports a low level interface for specialized applications. Another feature of the service is that it allows a user to plug-in an end device of his/her choice on a per-session basis. We demonstrate the richness of the API by describing prototypes for enhancing various applications as well as new converged applications.