Results 11  20
of
499
Lower Bounds for Online Graph Problems with Application to Online Circuit and Optical Routing
, 1996
"... We present lower bounds on the competitive ratio of randomized algorithms for a wide class of online graph optimization problems and we apply such results to online virtual circuit and optical routing problems. Lund and Yannakakis [LY93a] give inapproximability results for the problem of finding t ..."
Abstract

Cited by 54 (11 self)
 Add to MetaCart
We present lower bounds on the competitive ratio of randomized algorithms for a wide class of online graph optimization problems and we apply such results to online virtual circuit and optical routing problems. Lund and Yannakakis [LY93a] give inapproximability results for the problem of finding the largest vertex induced subgraph satisfying any nontrivial, hereditary, property . E.g., independent set, planar, acyclic, bipartite, etc. We consider the online version of this family of problems, where some graph G is fixed and some subgraph H is presented online, vertex by vertex. The online algorithm must choose a subset of the vertices of H , choosing or rejecting a vertex when it is presented, whose vertex induced subgraph satisfies property . Furthermore, we study the online version of graph coloring whose offline version has also been shown to be inapproximable [LY93b], online max edgedisjoint paths and online path coloring problems. Irrespective of the time complexity, w...
Improved Bounds for the Unsplittable Flow Problem
 In Proceedings of the 13th ACMSIAM Symposium on Discrete Algorithms
, 2002
"... In this paper we consider the unsplittable ow problem (UFP): given a directed or undirected network G = (V, E) with edge capacities and a set of terminal pairs (or requests) with associated demands, find a subset of the pairs of maximum total demand for which a single flow path can be chosen for eac ..."
Abstract

Cited by 49 (6 self)
 Add to MetaCart
In this paper we consider the unsplittable ow problem (UFP): given a directed or undirected network G = (V, E) with edge capacities and a set of terminal pairs (or requests) with associated demands, find a subset of the pairs of maximum total demand for which a single flow path can be chosen for each pair so that for every edge, the sum of the demands of the paths crossing the edge does not exceed its capacity.
IncentiveCompatible Online Auctions for Digital Goods
 In Proc. 13th Symp. on Discrete Alg. ACM/SIAM
, 2002
"... Goldberg et al. [6] recently began the study of incentivecompatible auctions for digital goods, that is, goods which are available in unlimited supply. Many digital goods, however, such as books, music, and software, are sold continuously, rather than in a single round, as is the case for traditiona ..."
Abstract

Cited by 45 (3 self)
 Add to MetaCart
Goldberg et al. [6] recently began the study of incentivecompatible auctions for digital goods, that is, goods which are available in unlimited supply. Many digital goods, however, such as books, music, and software, are sold continuously, rather than in a single round, as is the case for traditional auctions. Hence, it is important to consider what happens in the online version of such auctions. We de ne a model for online auctions for digital goods, and within this model, we examine auctions in which bidders have an incentive to bid their true valuations, that is, incentivecompatible auctions. Since the best oine auctions achieve revenue comparable to the revenue of the optimal xed pricing scheme, we use the latter as our benchmark. We show that deterministic auctions perform poorly relative to this benchmark, but we give a randomized auction which is within a factor O(exp( p log log h)) of the benchmark, where h is the ratio between the highest and lowest bids. As part of this result, we also give a new oine auction, which improves upon the previously best auction in a certain class of auctions for digital goods. We also give lower bounds for both randomized and deterministic online auctions for digital goods. 1
Allocating online advertisement space with unreliable estimates
 In Proceedings of the 8th ACM Conference on Electronic Commerce (EC
, 2007
"... We study the problem of optimally allocating online advertisement space to budgetconstrained advertisers. This problem was defined and studied from the perspective of worstcase online competitive analysis by Mehta et al. Our objective is to find an algorithm that takes advantage of the given estim ..."
Abstract

Cited by 45 (7 self)
 Add to MetaCart
We study the problem of optimally allocating online advertisement space to budgetconstrained advertisers. This problem was defined and studied from the perspective of worstcase online competitive analysis by Mehta et al. Our objective is to find an algorithm that takes advantage of the given estimates of the frequencies of keywords to compute a near optimal solution when the estimates are accurate, while at the same time maintaining a good worstcase competitive ratio in case the estimates are totally incorrect. This is motivated by realworld situations where search engines have stochastic information that provide reasonably accurate estimates of the frequency of search queries except in certain highly unpredictable yet economically valuable spikes in the search pattern. Our approach is a blackbox approach: we assume we have access to an oracle that uses the given estimates to recommend an advertiser every time a query arrives. We use this oracle to design an algorithm that provides two performance guarantees: the performance guarantee in the case that the oracle gives an accurate estimate, and its worstcase performance guarantee. Our algorithm can be fine tuned by adjusting a parameter α, giving a tradeoff curve between the two performance measures with the best competitive ratio for the worstcase scenario at one end of the curve and the optimal solution for the scenario where estimates are accurate at the other end. Finally, we demonstrate the applicability of our framework by applying it to two classical online problems, namely the lost cow and the ski rental problems.
Cooperative Negotiation in Autonomic Systems Using Incremental Utility Elicitation
 In Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence
, 2003
"... Decentralized resource allocation is a key problem for largescale autonomic (or selfmanaging) computing systems. Motivated by a data center scenario, we explore efficient techniques for resolving resource conflicts via cooperative negotiation. ..."
Abstract

Cited by 43 (9 self)
 Add to MetaCart
Decentralized resource allocation is a key problem for largescale autonomic (or selfmanaging) computing systems. Motivated by a data center scenario, we explore efficient techniques for resolving resource conflicts via cooperative negotiation.
Dynamic rightsizing for powerproportional data centers
"... Abstract—Power consumption imposes a significant cost for data centers implementing cloud services, yet much of that power is used to maintain excess service capacity during periods of predictably low load. This paper investigates how much can be saved by dynamically ‘rightsizing ’ the data center ..."
Abstract

Cited by 41 (12 self)
 Add to MetaCart
Abstract—Power consumption imposes a significant cost for data centers implementing cloud services, yet much of that power is used to maintain excess service capacity during periods of predictably low load. This paper investigates how much can be saved by dynamically ‘rightsizing ’ the data center by turning off servers during such periods, and how to achieve that saving via an online algorithm. We prove that the optimal offline algorithm for dynamic rightsizing has a simple structure when viewed in reverse time, and this structure is exploited to develop a new ‘lazy ’ online algorithm, which is proven to be 3competitive. We validate the algorithm using traces from two real data center workloads and show that significant costsavings are possible. I.
Competitive Queue Policies for Differentiated Services
, 2000
"... We consider the setting of a network providing differentiated services. As is often the case in differentiated services, we assume that the packets are tagged as either being a high priority packet or a low priority packet. Outgoing links in the network are serviced by a single FIFO queue. ..."
Abstract

Cited by 40 (10 self)
 Add to MetaCart
We consider the setting of a network providing differentiated services. As is often the case in differentiated services, we assume that the packets are tagged as either being a high priority packet or a low priority packet. Outgoing links in the network are serviced by a single FIFO queue.
Competitive HillClimbing Strategies for Replica Placement in a Distributed File System
 In DISC
, 2001
"... 1 Introduction This paper analyzes algorithms for automated placement of file replicas in the Farsite [3] system, using both theory and simulation. In the Farsite distributed file system, multiple replicas of files are stored on multiple machines, so that files can be accessed even if some of the ma ..."
Abstract

Cited by 39 (3 self)
 Add to MetaCart
1 Introduction This paper analyzes algorithms for automated placement of file replicas in the Farsite [3] system, using both theory and simulation. In the Farsite distributed file system, multiple replicas of files are stored on multiple machines, so that files can be accessed even if some of the machines are down or inaccessible. The purpose of the placement algorithm is to determine an assignment of file replicas to machines that maximally exploits the availability provided by machines. The file placement algorithm is given a fixed value, R, for the number of replicas of each file. For systems reasons, we are most interested in a value of R = 3 [9]. However, to ensure that our results are not excessively sensitive to the file replication factor, we also provide tight bounds for R = 2 and lower bounds for all R (tight at different values of R).
Optimization Problems in Congestion Control
 In IEEE Symposium on Foundations of Computer Science
, 2000
"... One of the crucial elements in the Internet’s success is its ability to adequately control congestion. This paper defines and solves several optimization problems related to Internet congestion control, as a step toward understanding the virtues of the TCP congestion control algorithm currently used ..."
Abstract

Cited by 39 (1 self)
 Add to MetaCart
One of the crucial elements in the Internet’s success is its ability to adequately control congestion. This paper defines and solves several optimization problems related to Internet congestion control, as a step toward understanding the virtues of the TCP congestion control algorithm currently used and comparing it with alternative algorithms. We focus on regulating the rate of a single unicast flow when the bandwidth available to it is unknown and may change over time. We determine nearoptimal policies when the available bandwidth is unchanging, and nearoptimal competitive policies when the available bandwidth is changing in a restricted manner under the control of an adversary. 1.