Network Modeling, Simulation, and Management

A doctor cultures a sore throat and then tries different antibiotics on the cultures to see which work best. Rensselaer researchers have pioneered a similar process for diagnosing and treating computer network problems. With support from DARPA, the National Science Foundation, and other funding sources, they have developed methods to run rapid simulations to identify problems and then to apply automated traffic management techniques to solve the problems. Current research continues to improve simulation techniques, network management, and quality of service.

Genesis: Many Processors Sharing the Work

Simulation has become an accepted scientific tool for understanding the dynamics of a complex system, and the Internet is one of the most complex artifacts created by technology. With decentralized control and unintentional and deliberate disruptions, its dynamics are very difficult to understand. Attempts to simulate it are riddled with challenges. Simulations based on the lowest network level of a single packet can account for all the affects and dynamics of the Internet but tend to be slow. Packets change their status in millisecond time, and their parallel simulation requires synchronization of the simulating processors at that time scale, which kills the parallel efficiency. (They are like workers who spend so much time coordinating what they want to do that little time is spent working). Simulations based on flows of packets are fast because they synchronize at the time scale of flows, seconds, or even minutes, but cannot represent important events happening to individual packets. A new approach to this problem has been proposed by Dr. Boleslaw Szymanski, professor of computer science and founding director of the Center for Pervasive Computing and Networking, who was elected an IEEE fellow for his work on parallel and distributed systems. With strong support from DARPA, he and his team developed Genesis (The GeneralNEtworkSimulation Integration System), a novel approach to scalability and efficiency of parallel network simulation. The system divides the Internet into domains, with a separate processor used to simulate each domain over a given time interval. Each domain does the packet-level simulation but synchronizes entire flows over the time interval. When each simulation is finished, the domains exchange information about the flows and begin a new iteration over the same time interval. The iterations continue until all simulations converge, and then the system moves on to a new time interval. This approach has proven successful in many difficult tasks, such as accurately modeling the TCP (Transmission Control Protocol), which constantly adjusts to current network conditions.

In other work, Dr. Szymanski is collaborating with a group that includes the University of Genoa in Italy, the University of Girona in Spain, and the National Academic Network (NASK) in Poland to develop SNAP, the Service Negotiation and Adaptive Delivery Platform. With researchers in Girona and Warsaw, he is looking at means to use dynamic pricing to negotiate Quality of Service. Prices are set to avoid congestion and yield rational use of the system, which also monitors the service delivered and gives discounts, if needed, to compensate for times when service deteriorates. The goals are to deliver the expected service despite changing environments and to maintain customer satisfaction. Dr. Szymanski is also providing the simulation tools needed to measure and monitor service. 
 

ROSSNet: The More Work, the Better
 

Christopher Carothers, assistant professor of computer science, has built ROSSNet (Rensselaer’s Optimistic Simulation System), a very fast simulation method that uses parallel processors. With AT&T support, Dr. Carothers and Shivkumar Kalyanaraman, associate professor of electrical, computer, and systems engineering (ECSE), are using real-time simulations to optimize very complex systems in which networks using different protocols and operating at different time scales must be able to communicate with each other through the BGP (Border Gateway Protocol). ROSSNet provides them a system that is insensitive to changes in the topology of the network, that uses far less memory per connection than other systems, and that performs very rapidly. In fact, rather than slowing down as domains and processors are added, the system speeds up. Carothers explains that this is because the work on each processor remains constant, but the overhead per processor decreases.
 

Automated Traffic Management
 

Dr. Kalyanaraman is an expert in network traffic management whose work has already won him recognition by MIT’s Technology Review as one of the top 100 “Visionaries for the Millennium.” With support from both government and industry, he, his colleagues, and his students are working on a number of projects to reduce congestion, automate network management, and improve quality of service. These include:

Good Results Fast Using the slogan “good results fast,” Dr. Kalyanaraman has built a recursive random search algorithm that continuously collects real-time data on network conditions and runs simulations to discover improved settings for the millions of network parameters. His approach is designed to choose the best simulations from the many that are possible. His system then works very quickly, not to seek optimal settings, which would take too long, but to discover improved settings within a limited time frame. The improved settings can be given to network operators or set automatically to continuously improve network performance by adjusting parameters to changing conditions.

 

Overlay Services Just as the Internet developed over telephone lines, Dr. Kalyanaraman is working on “overlay” next-generation services that can be created on top of the current Internet. Such services, which could be delivered by network service providers or could be created in ad hoc peer-to-peer organizations, would scavenge bandwidth from computers not in use to gain bandwidth and would choose the best routes to ensure far better quality of service. Using overlay systems, Dr. Kalyanaraman’s methods can deliver reliable, broadband capability for such consumer-oriented services as video conferencing and chats and sending home movies to friends and relatives.
 

Going Bananas BANANAS is an evolutionary architectural Internet framework with a new coding scheme that gives messages far more flexibility in the route they take. Instead of being committed to one route, messages can be sent on alternate paths when congestion is slowing traffic, just as drivers may choose to switch to another route when one highway is badly congested.
 

Wireless Traffic Modeling
 

With support from DARPA, Biplab Sikdar, ECSE assistant professor, is working to understand traffic patterns in wireless networks. In one project, he developed a model to characterize the arrival times of packets in wireless networks that use the IEEE 802.11 MAC (media access control) protocol. His model showed significant differences between traffic patterns in wired and wireless networks. While this study assumed the nodes in the network were stationary, he now is looking at what happens when the various nodes become mobile. The insights he is developing can lead to improved network performance and can provide the modeling tools for more accurate performance evaluation.

Can We Understand the Internet?
 

Given the immense size of the Internet and the rapid changes it constantly undergoes, is it ever possible to accurately measure its properties and totally understand its behavior? Petros Drineas, assistant professor of computer science and an expert in the design and analysis of algorithms, and Bulent Yener, associate professor of computer science with strong experience in quality-of-service issues, are looking at this basic question. They are interested in the concept of “evasiveness,” the difficulty of obtaining accurate information about specific properties. If it is not possible to obtain 100 percent of the accurate information about the topology of the Internet, their goal is to understand how much accurate information is needed for various management tasks.