Algorithms for Computing QoS Paths With Restoration

There is a growing interest among service providers to offer new services with Quality of Service (QoS) guarantees that are also resilient to failures. Supporting QoS connections requires the existence of a routing mechanism, that computes the QoS paths, i.e., paths that satisfy QoS constraints (e.g., delay or bandwidth). Resilience to failures, on the other hand, is achieved by providing, for each primary QoS path, a set of alternative QoS paths used upon a failure of either a link or a node. The above objectives, coupled with the need to minimize the global use of network resources, imply that the cost of both the primary path and the restoration topology should be a major consideration of the routing process. We undertake a comprehensive study of problems related to finding suitable restoration topologies for QoS paths. We consider both bottleneck QoS constraints, such as bandwidth, and additive QoS constraints, such as delay and jitter. This is the first study to provide a rigorous solution, with proven guarantees, to the combined problem of computing QoS paths with restoration. It turns out that the widely used approach of disjoint primary and restoration paths is not an optimal strategy. Hence, the proposed algorithms construct a restoration topology, i.e., a set of bridges, each bridge protecting a portion of the primary QoS path. This approach guarantees to find a restoration topology with low cost when one exists

Algorithms for Computing QoS Paths With Restoration

There is a growing interest among service providers to offer new services with Quality of Service (QoS) guarantees that are also resilient to failures. Supporting QoS connections requires the existence of a routing mechanism, that computes the QoS paths, i.e., paths that satisfy QoS constraints (e.g., delay or bandwidth). Resilience to failures, on the other hand, is achieved by providing, for each primary QoS path, a set of alternative QoS paths used upon a failure of either a link or a node. The above objectives, coupled with the need to minimize the global use of network resources, imply that the cost of both the primary path and the restoration topology should be a major consideration of the routing process. We undertake a comprehensive study of problems related to finding suitable restoration topologies for QoS paths. We consider both bottleneck QoS constraints, such as bandwidth, and additive QoS constraints, such as delay and jitter. This is the first study to provide a rigorous solution, with proven guarantees, to the combined problem of computing QoS paths with restoration. It turns out that the widely used approach of disjoint primary and restoration paths is not an optimal strategy. Hence, the proposed algorithms construct a restoration topology, i.e., a set of bridges, each bridge protecting a portion of the primary QoS path. This approach guarantees to find a restoration topology with low cost when one exists

Data Discretization Unification

Data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. In this paper, we prove that discretization methods based on informational theoretical complexity and the methods based on statistical measures of data dependency are asymptotically equivalent. Furthermore, we define a notion of generalized entropy and prove that discretization methods based on MDLP, Gini Index, AIC, BIC, and Pearson’s X 2 and G 2 statistics are all derivable from the generalized entropy function. We design a dynamic programming algorithm that guarantees the best discretization based on the generalized entropy notion. Furthermore, we conducted an extensive performance evaluation of our method for several publicly available data sets. Our results show that our method delivers on the average 31 % less classification errors than many previously known discretization methods.

Topology Discovery in Heterogeneous IP Networks

Knowledge of the up-to-date physical topology of an IP network is crucial to a number of critical network management tasks, including reactive and proactive resource management, event correlation, and root-cause analysis. Given the dynamic nature of today's IP networks, keeping track of topology information manually is a daunting (if not impossible) task. Thus, effective algorithms for automatically discovering physical network topology are necessary. Earlier work has typically concentrated on either (a) discovering logical (i.e., layer-3) topology, which implies that the connectivity of all layer-2 elements (e.g., switches and bridges) is ignored, or (b) proprietary solutions targeting specific product families. In this paper, we present novel algorithms for discovering physical topology in heterogeneous (i.e., multi-vendor) IP networks. Our algorithms rely on standard SNMP MIB information that is widely supported by modern IP network elements and require no modifications to the opera..

Cost/Performance Control in SNOWBALL Distributed File Manager

Networks of workstations are an emerging architectural paradigm for highperformance parallel and distributed systems. Exploiting networks of workstations for massive data management poses exciting challenges. We consider here the problem of management of record-structured files in such an environment. The file records are accessed by a dynamically growing set of clients based on a search key. To scale up the throughput of client accesses with approximately constant response time, the files and thus also their access load are dynamically redistributed across a growing set of workstations. The redistribution method is capable of an explicit control of system cost/performance. Namely, the system maintains its cost/performance at a prescribed constant level for a wide spectrum of workloads as confirmed by experimental simulation results. Consequently, the system is capable of providing soft guarantees on the record retrieval times