Hongsuda Tangmunarunkit

Heuristics for Internet map discovery

Mercator is a program that uses hop-limited probes-the same primitive used in traceroute-to infer an Internet map. It uses informed random address probing to carefully exploring the IP address space when determining router adjacencies, uses source-route capable routers wherever possible to enhance the fidelity of the resulting map, and employs novel mechanisms for resolving aliases (interfaces belonging to the same router). This paper describes the design of these heuristics and our experiences with Mercator, and presents some preliminary analysis of the resulting Internet map.

Network topology generators: degree-based vs. structural

Following the long-held belief that the Internet is hierarchical, the network topology generators most widely used by the Internet research community, Transit-Stub and Tiers, create networks with a deliberately hierarchical structure. However, in 1999 a seminal paper by Faloutsos et al. revealed that the Internets degree distribution is a power-law. Because the degree distributions produced by the Transit-Stub and Tiers generators are not power-laws, the research community has largely dismissed them as inadequate and proposed new network generators that attempt to generate graphs with power-law degree distributions.Contrary to much of the current literature on network topology generators, this paper starts with the assumption that it is more important for network generators to accurately model the large-scale structure of the Internet (such as its hierarchical structure) than to faithfully imitate its local properties (such as the degree distribution). The purpose of this paper is to determine, using various topology metrics, which network generators better represent this large-scale structure. We find, much to our surprise, that network generators based on the degree distribution more accurately capture the large-scale structure of measured topologies. We then seek an explanation for this result by examining the nature of hierarchy in the Internet more closely; we find that degree-based generators produce a form of hierarchy that closely resembles the loosely hierarchical nature of the Internet.

Scaling of multicast trees: comments on the Chuang-Sirbu scaling law

One of the many benefits of multicast, when compared to traditional unicast, is that multicast reduces the overall network load. While the importance of multicast is beyond dispute, there have been surprisingly few attempts to quantify multicasts reduction in overall network load. The only substantial and quantitative effort we are aware of is that of Chuang and Sirbu [3]. They calculate the number of links L in a multicast delivery tree connecting a random source to m random and distinct network sites; extensive simulations over a range of networks suggest that L(m) ∝ m0.8. In this paper we examine the function L(m) in more detail and derive the asymptotic form for L(m) in k-ary trees. These results suggest one possible explanation for the universality of the Chuang-Sirbu scaling behavior.

The impact of routing policy on Internet paths

The impact of routing policy on Internet paths is poorly understood. In theory, the policy can inflate shortest-router-hop paths. To our knowledge, the extent of this inflation has not been previously examined. Using a simplified model of the routing policy in the Internet, we obtain approximate indications of the impact of policy routing on Internet paths. Our findings suggest that the routing policy does impact the length of Internet paths significantly. For instance, in our model of the routing policy, some 20% of Internet paths are inflated by more than five router-level hops.

Ontology-based resource matching in the grid: the grid meets the semantic web

The Grid is an emerging technology for enabling resource sharing and coordinated problem solving in dynamic multi-institutional virtual organizations. In the Grid environment, shared resources and users typically span different organizations. The resource matching problem in the Grid involves assigning resources to tasks in order to satisfy task requirements and resource policies. These requirements and policies are often expressed in disjoint application and resource models, forcing a resource selector to perform semantic matching between the two. In this paper, we propose a flexible and extensible approach for solving resource matching in the Grid using semantic web technologies. We have designed and prototyped an ontology-based resource selector that exploits ontologies, background knowledge, and rules for solving resource matching in the Grid.

Artificial intelligence and grids: workflow planning and beyond

A key challenge for grid computing is creating large-scale, end-to-end scientific applications that draw from pools of specialized scientific components to derive elaborate new results. We develop Pegasus, an AI planning system which is integrated into the grid environment that takes a users highly specified desired results, generates valid workflows that take into account available resources, and submits the workflows for execution on the grid. We also begin to extend it as a more distributed and knowledge-rich architecture.

Network topologies, power laws, and hierarchy

It has long been thought that the Internet, and its constituent networks, are hierarchical in nature. Consequently, the network topology generators most widely used by the Internet research community, GT-ITM [7] and Tiers [11], create networks with a deliberately hierarchical structure. However, recent work by Faloutsos et al. [13] revealed that the Internet’s degree distribution — the distribution of the number of connections routers or Autonomous Systems (ASs) have — is a power-law. The degree distributions produced by the GT-ITM and Tiers generators are not power-laws. To rectify this problem, several new network generators have recently been proposed that produce more realistic degree distributions; these new generators do not attempt to create a hierarchical structure but instead focus solely on the degree distribution. There are thus two families of network generators, structural generators that treat hierarchy as fundamental and degree-based generators that treat the degree distribution as fundamental. In this paper we use several topology metrics to compare the networks produced by these two families of generators to current measurements of the Internet graph. We find that the degree-based generators produce better models, at least according to our topology metrics, of both the AS-level and router-level Internet graphs. We then seek to resolve the seeming paradox that while the Internet certainly has hierarchy, it appears that the Internet graphs are better modeled by generators that do not explicitly construct hierarchies. We conclude our paper with a brief study of other network structures, such as the pointer structure in the web and the set of airline routes, some of which turn out to have metric properties similar to that of the Internet.

Internet path inflation due to policy routing

In our previous work, we used a simplified model of routing policy in the Internet to study the impact of policy routing on Internet path-lengths. This prior work suffered from two shortcomings--it was based on a single snapshot of the Internet topology, and our simplified policy model could generate AS paths that violate peering relationships. In this paper, we address these two shortcomings by re-examining our results with respect to a more recent snapshot of the Internet, and improving the policy model to avoid peering violation. We find that our prior observations regarding the path inflation due to routing policy appear to hold both across time and with respect to a more sophisticated model of routing policy.

A semantic matchmaker service on the grid

A fundamental task on the Grid is to decide what jobs to run on what computing resources based on job or application requirements. Our previous work on ontology-based matchmaking discusses a resource matchmaking mechanism using Semantic Web technologies. We extend our previous work to provide dynamic access to such matchmaking capability by building a persistent online matchmaking service. Our implementation uses the Globus Toolkit for the Grid service development, and exploits the monitoring and discovery service in the Grid infrastructure to dynamically discover and update resource information. We describe the architecture of our semantic matchmaker service in the poster.

Experiences with DERIVA: An Asset Management Platform for Accelerating eScience

The pace of discovery in eScience is increasingly dependent on a scientist’s ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. It is all too common for investigators to spend inordinate amounts of time developing ad hoc procedures to manage their data. In previous work, we presented DERIVA, a Scientific Asset Management System, designed to accelerate data driven discovery. In this paper, we report on the use of DERIVA in a number of substantial and diverse eScience applications. We describe the lessons we have learned, both from the perspective of the DERIVA technology, as well as the ability and willingness of scientists to incorporate Scientific Asset Management into their daily workflows.