e-approximations with minimum packing constraint violation (extended abstract)
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Approximation algorithms for facility location problems (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Greedy strikes back: improved facility location algorithms
Journal of Algorithms
Improved algorithms for fault tolerant facility location
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
A new greedy approach for facility location problems
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
An approximation algorithm for the fault tolerant metric facility location problem
APPROX '00 Proceedings of the Third International Workshop on Approximation Algorithms for Combinatorial Optimization
Improved Approximation Algorithms for Metric Facility Location Problems
APPROX '02 Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization
A Greedy Facility Location Algorithm Analyzed Using Dual Fitting
APPROX '01/RANDOM '01 Proceedings of the 4th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems and 5th International Workshop on Randomization and Approximation Techniques in Computer Science: Approximation, Randomization and Combinatorial Optimization
Greedy facility location algorithms analyzed using dual fitting with factor-revealing LP
Journal of the ACM (JACM)
Improved approximation algorithms for capacitated facility location problems
Mathematical Programming: Series A and B
Improved Combinatorial Algorithms for Facility Location Problems
SIAM Journal on Computing
Approximation Algorithms for Metric Facility Location Problems
SIAM Journal on Computing
Fault-tolerant facility location
ACM Transactions on Algorithms (TALG)
The Fault-Tolerant Facility Allocation Problem
ISAAC '09 Proceedings of the 20th International Symposium on Algorithms and Computation
Optimal Resource Allocation in Clouds
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Approximation algorithms for the Fault-Tolerant Facility Placement problem
Information Processing Letters
Fault-tolerant facility location: a randomized dependent LP-Rounding algorithm
IPCO'10 Proceedings of the 14th international conference on Integer Programming and Combinatorial Optimization
Approximating the reliable resource allocation problem using inverse dual fitting
CATS '12 Proceedings of the Eighteenth Computing: The Australasian Theory Symposium - Volume 128
Improved approximation algorithms for constrained fault-tolerant resource allocation
FCT'13 Proceedings of the 19th international conference on Fundamentals of Computation Theory
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First, we study the Unconstrained Fault-Tolerant Resource Allocation (UFTRA) problem (a.k.a. FTFA problem in [19]). In the problem, we are given a set of sites equipped with an unconstrained number of facilities as resources, and a set of clients with set R as corresponding connection requirements, where every facility belonging to the same site has an identical opening (operating) cost and every client-facility pair has a connection cost. The objective is to allocate facilities from sites to satisfy R at a minimum total cost. Next, we introduce the Constrained Fault-Tolerant Resource Allocation (CFTRA) problem. It differs from UFTRA in that the number of resources available at each site i is limited by Ri. Both problems are practical extensions of the classical Fault-Tolerant Facility Location (FTFL) problem [10]. For instance, their solutions provide optimal resource allocation (w.r.t. enterprises) and leasing (w.r.t. clients) strategies for the contemporary cloud platforms. In this paper, we consider the metric version of the problems. For UFTRA with uniform R, we present a star-greedy algorithm. The algorithm achieves the approximation ratio of 1.5186 after combining with the cost scaling and greedy augmentation techniques similar to [3,14], which significantly improves the result of [19] using a phase-greedy algorithm. We also study the capacitated extension of UFTRA and give a factor of 2.89. For CFTRA with uniform R, we slightly modify the algorithm to achieve 1.5186-approximation. For a more general version of CFTRA, we show that it is reducible to FTFL using linear programming.