TY - GEN

T1 - Unconstrained and constrained fault-tolerant resource allocation

AU - Liao, Kewen

AU - Shen, Hong

N1 - Funding Information:
This work was partially supported by Australian Research Council Discovery Project grant #DP0985063.

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=80052005760&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-22685-4_48

DO - 10.1007/978-3-642-22685-4_48

M3 - Conference contribution

AN - SCOPUS:80052005760

SN - 9783642226847

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 555

EP - 566

BT - Computing and Combinatorics - 17th Annual International Conference, COCOON 2011, Proceedings

T2 - 17th Annual International Computing and Combinatorics Conference, COCOON 2011

Y2 - 14 August 2011 through 16 August 2011

ER -