Ron Banner

Multipath routing algorithms for congestion minimization

Unlike traditional routing schemes that route all traffic along a single path, multipath routing strategies split the traffic among several paths in order to ease congestion. It has been widely recognized that multipath routing can be fundamentally more efficient than the traditional approach of routing along single paths. Yet, in contrast to the single-path routing approach, most studies in the context of multipath routing focused on heuristic methods. We demonstrate the significant advantage of optimal (or near optimal) solutions. Hence, we investigate multipath routing adopting a rigorous (theoretical) approach. We formalize problems that incorporate two major requirements of multipath routing. Then, we establish the intractability of these problems in terms of computational complexity. Finally, we establish efficient solutions with proven performance guarantees

Designing Low-Capacity Backup Networks for Fast Restoration

There are two basic approaches to allocate protection resources for fast restoration. The first allocates resources upon the arrival of each connection request; yet, it incurs significant set-up time and is often capacity-inefficient. The second approach allocates protection resources during the network configuration phase; therefore, it needs to accommodate any possible arrival pattern of connection requests, hence potentially calling for a substantial over-provisioning of resources. However, in this study we establish the feasibility of this approach. Specifically, we consider a scheme that, during the network configuration phase, constructs an (additional) low-capacity backup network. Upon a failure, traffic is rerouted through a bypass in the backup network. We establish that, with proper design, backup networks induce feasible capacity overhead. We further impose several design requirements (e.g., hop-count limits) on backup networks and their induced bypasses, and prove that, commonly, they also incur minor overhead. Motivated by these findings, we design efficient algorithms for the construction of backup networks.

Automatic Policy Rule Extraction for Configuration Management

We propose a new IT automation technology for configuration management: automatic baseline policy extraction out of the Configuration Management Data Base (CMDB). Whereas authoring a configuration policy rule manually is time consuming and unlikely to realize the actual state of the configurations in the overall organization, this new approach summarizes the de-facto configurations from the data. IT staff, instead of authoring the policy rule, is required to simply validate and possibly enhance the automatically extracted policy. Our technology applies data-mining to organizations configuration assets in the CMDB, and automatically identifies repeating structures of compound configurations. Based on these repeating structures, we build policy rules for compound configuration items. The heart of our technique is a new distance measure we introduce between the configuration assets, whose computation is reduced to a minimum-cost flow problem.