2872380
Building Edge-Failure Resilient Networks
AbstractWe consider the design of resilient networks that are fault tolerant
 against link failures. Resilience against link failures can be built
 into the network by providing backup paths, which are used in
 the eventuality of an edge failure occurring on a primary path in the
 network. We consider several network design problems in this context;
 these problems are motivated by the requirements of current high-speed
 optical networks. In all the following problems the objective is to
 provide resilience in networks while minimizing the cost incurred.
 The main problem under consideration in this paper is that of backup
 allocation: this problem takes as its input an already provisioned 
 primary network and a parameter k, and allocates backup capacity 
 on the edges of the underlying network so that all the demand can be 
 routed even in the presence of k edge failures. We also consider a 
 variant of this problem where the primary network has a tree topology, 
 and it is required that the restored network retains a tree topology. 
 We then address the problem of simultaneous primary and backup
 allocation: we are given specifications of the traffic to be
 handled, and the goal is to provision both the primary as well as
 the backup network. Finally, we investigate a single-commodity
 problem motivated by a pragmatic scenario in which the primary
 network is not known in advance and demands between source--sink
 pairs arrive online.
47268289
Optimal configuration of OSPF aggregates
Open Shortest Path First (OSPF) is a popular protocol for routing within an autonomous system (AS) domain. In order to scale for large networks containing hundreds and thousands of subnets, OSPF supports a two-level hierarchical routing scheme through the use of OSPF areas. Subnet addresses within an area are aggregated, and this aggregation is a crucial requirement for scaling OSPF to large AS domains, as it results in significant reductions in routing table sizes, smaller link-state databases, and less network traffic to synchronize the router link-state databases. On the other hand, address aggregation also implies loss of information about the length of the shortest path to each subnet, which in turn, can lead to suboptimal routing.In this paper, we address the important practical problem of configuring OSPF aggregates to minimize the error in OSPF shortest-path computations due to subnet aggregation. We first develop an optimal dynamic programming algorithm that, given an upper bound k on the number of aggregates to be advertised and a weight assignment function for the aggregates, computes the k aggregates that result in the minimum cumulative error in the shortest-path computations for all source-destination subnet pairs. Subsequently, we tackle the problem of assigning weights to OSPF aggregates such that the cumulative error in the computed shortest paths is minimized. We demonstrate that, while for certain special cases (e.g., unweighted cumulative error) efficient optimal algorithms for the weight assignment problem can be devised, the general problem itself is NP-hard. Consequently, we have to rely on search heuristics to solve the weight assignment problem. To the best of our knowledge, our work is the first to address the algorithmic issues underlying the configuration of OSPF aggregates and to propose efficient configuration algorithms that are provably optimal for many practical scenarios.
206560175
A constant-factor approximation algorithm for the multicommodity rent-or-buy problem
We present the first constant factor approximation algorithm for network design with multiple commodities and economies of scale. We consider the rent-or-buy problem, a type of multicommodity buy-at-bulk network design in which there are two ways to install capacity on any given edge. Capacity can be rented, with cost incurred on a per-unit of capacity basis, or bought, which allows unlimited use after payment of a large fixed cost. Given a graph and a set of source-sink pairs, we seek a minimum-cost way of installing sufficient capacity on edges so that a prescribed amount of flow can be sent simultaneously from each source to the corresponding sink. Recent work on buy-at-bulk network design has concentrated on the special case where all sinks are identical; existing constant factor approximation algorithms for this special case make crucial use of the assumption that all commodities ship flow to the same sink vertex and do not obviously extend to the multicommodity rent-or-buy problem. Prior to our work, the best heuristics for the multicommodity rent-or-buy problem achieved only logarithmic performance guarantees and relied on the machinery of relaxed metrical task systems or of metric embeddings. By contrast, we solve the network design problem directly via a novel primal-dual algorithm.
46145059
Primal-Dual Algorithms for Connected Facility Location Problems
We consider the Connected Facility Location problem. We are given a graph G = (V, E) with cost ce on edge e, a set of facilities F ? V, and a set of demands D ? V. We are also given a parameter M ? 1. A solution opens some facilities, say F, assigns each demand j to an open facility i(j), and connects the open facilities by a Steiner tree T. The cost incurred is ?i?F fi + ?j?D djci(j)j + M ?e?T ce. We want a solution of minimum cost. A special case is when all opening costs are 0 and facilities may be opened anywhere, i.e., F = V. If we know a facility v that is open, then this problem reduces to the rent-or-buy problem. We give the first primal-dual algorithms for these problems and achieve the best known approximation guarantees. We give a 9-approximation algorithm for connected facility location and a 5-approximation for the rent-or-buy problem. Our algorithm integrates the primal-dual approaches for facility location [7] and Steiner trees [1,2]. We also consider the connected k-median problem and give a constant-factor approximation by using our primal-dual algorithm for connected facility location. We generalize our results to an edge capacitated version of these problems.
46840073
Better Algorithms for Minimizing Average Flow-Time on Related Machines
We consider the problem of minimising flow time on related machines and give an O(logP)-approximation algorithm for the offline case and an O(log2P)-competitive algorithm for the online version. This improves upon the previous best bound of O(log2P logS) on the competitive ratio. Here P is the ratio of the maximum to the minimum processing time of a job and S is the ratio of the maximum to the minimum speed of a machine.
8488383
Sorting and selection with structured costs
The study of the effect of priced information on basic algorithmic problems was initiated by M. Charikar et al. (2000). The authors continue the study of sorting and selection in the priced comparison model, i.e., when each comparison has an associated cost, and answer some of the open problems suggested by Charikar et al. If the comparison costs are allowed to be arbitrary, we show that one cannot get good approximation ratios. A different way to assign costs is based on the idea that one can distill out an intrinsic value for each item being compared, such that the cost of comparing two elements is some "well-behaved" or "structured" function of their values. We feel that most practical applications will have some structured cost property. The authors study the problems of sorting and selection (which includes finding the maximum and the median) in the structured cost model. We get a variety of approximation results for these problems, depending on the restrictions we put on the structured costs. We show that it is possible to get much improved results with the structured cost model than the case when we do not have any assumptions on comparison costs.
14897390
Meta workflows as a control and coordination mechanism for exception handling in workflow systems
A higher level control and coordination mechanism is required for exception handling in workflow systems. This paper describes such a framework based on events, states, and a new kind of process called a meta workflow. Meta workflows have five kinds of meta activities and facilitate control over base workflows. We describe the framework and illustrate it with examples to show its features. The paper gives an architecture for incorporating it into existing workflows and also provides a formal semantics of execution. This framework can be used in Web services, supply chains, and inter-organizational applications where coordination requirements are complex, and flexible and adaptable workflows are needed. It is also useful for handling not just failure recovery but also various kinds of special situations, which arise frequently in web-based applications.
17013178
Smart supply web: an application of web-based data and workflow mediation
This paper describes our vision of a Supply Web as the next major advance in the e-commerce world in terms of how e-services are delivered. After highlighting shortcomings of existing supply chain solutions, we give an architecture to show how three important technologies, namely, workow systems, data integration and on-line decision support, will have to come together to enable seamless deployment of e-service supply web solutions. We rst discuss research eorts (namely, XRL, YAT and DecisionFlows) that support the three technologies separately, and then describe the challenges of integrating them eectively.
2987975
Data streaming algorithms for efficient and accurate estimation of flow size distribution
Knowing the distribution of the sizes of traffic flows passing through a network link helps a network operator to characterize network resource usage, infer traffic demands, detect traffic anomalies, and accommodate new traffic demands through better traffic engineering. Previous work on estimating the flow size distribution has been focused on making inferences from sampled network traffic. Its accuracy is limited by the (typically) low sampling rate required to make the sampling operation affordable. In this paper we present a novel data streaming algorithm to provide much more accurate estimates of flow distribution, using a "lossy data structure" which consists of an array of counters fitted well into SRAM. For each incoming packet, our algorithm only needs to increment one underlying counter, making the algorithm fast enough even for 40 Gbps (OC-768) links. The data structure is lossy in the sense that sizes of multiple flows may collide into the same counter. Our algorithm uses Bayesian statistical methods such as Expectation Maximization to infer the most likely flow size distribution that results in the observed counter values after collision. Evaluations of this algorithm on large Internet traces obtained from several sources (including a tier-1 ISP) demonstrate that it has very high measurement accuracy (within 2%). Our algorithm not only dramatically improves the accuracy of flow distribution measurement, but also contributes to the field of data streaming by formalizing an existing methodology and applying it to the context of estimating the flow-distribution.
1151748
Scalable and Efficient Data Streaming Algorithms for Detecting Common Content in Internet Traffic
Recent research on data streaming algorithms has provided powerful tools to efficiently monitor various characteristics of traffic passing through a single network link or node. However, it is often desirable to perform data streaming analysis on the traffic aggregated over hundreds or even thousands of links/nodes, which will provide network operators with a holistic view of the network operation. Shipping raw traffic data to a centralized location (i.e., “raw aggregation”) for streaming analysis is clearly not a feasible approach for a large network. In this paper, we propose a set of novel distributed data streaming algorithms that allow scalable and efficient monitoring of aggregated traffic without the need for raw aggregation. Our algorithms target the specific network monitoring problem of finding common content in the Internet traffic traversing several nodes/links, which has applications in network-wide intrusion detection, early warning for fast propagating worms, and detection of hot objects and spam traffic. We evaluate our algorithms through extensive simulations and experiments on traffic traces collected from a tier-1 ISP. The experimental results demonstrate that our algorithms can effectively detect common content in the traffic traversing across a large network.
15446858
A new approach for asynchronous distributed rate control of elastic sessions in integrated packet networks
We develop a new class of asynchronous distributed algorithms for the explicit rate control of elastic sessions in an integrated packet network. Sessions can request for minimum guaranteed rate allocations (e.g., minimum cell rates in the ATM context), and, under this constraint, we seek to allocate the max-min fair rates to the sessions. We capture the integrated network context by permitting the link bandwidths available to elastic sessions to be stochastically time varying. The available capacity of each link is viewed as some statistic of this stochastic process [e.g., a fraction of the mean, or a large deviations-based equivalent service capacity (ESC)]. The ESC is obtained so as to satisfy an overflow probability constraint on the buffer length. For fixed available capacity at each link, we show that the vector of max-min fair rates can be computed from the root of a certain vector equation. A distributed asynchronous stochastic approximation technique is then used to develop a provably convergent distributed algorithm for obtaining the root of the equation, even when the link flows and the available capacities are obtained from on-line measurements. The switch algorithm does not require per connection monitoring, nor does it require per connection marking of control packets. A virtual buffer based approach for on-line estimation of the ESC is utilized. We also propose techniques for handling large variations in the available capacity owing to the arrivals or departures of CBR/VBR sessions. Finally, simulation results are provided to demonstrate the performance of this class of algorithms in the local and wide area network context.