The multicast policy and its relationship to replicated data placement
ACM Transactions on Database Systems (TODS)
Resource Placement with Multiple Adjacency Constraints in k-ary n-Cubes
IEEE Transactions on Parallel and Distributed Systems
An online video placement policy based on bandwidth to space ratio (BSR)
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Resource Allocation in Cube Network Systems Based on the Covering Radius
IEEE Transactions on Parallel and Distributed Systems
Approximation algorithms for facility location problems (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Exploiting local data in parallel array I/O on a practical network of workstations
Proceedings of the fifth workshop on I/O in parallel and distributed systems
Resource Placement in Torus-Based Networks
IEEE Transactions on Computers
Parallel I/O for scientific applications on heterogeneous clusters: a resource-utilization approach
ICS '99 Proceedings of the 13th international conference on Supercomputing
Load-sensitive routing of long-lived IP flows
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
An algorithm for finding a K-median in a directed tree
Information Processing Letters - Special issue analytical theory of fuzzy control with applications
Optimal Placement of Replicas in Trees with Read, Write, and Storage Costs
IEEE Transactions on Parallel and Distributed Systems
Algorithms for provisioning virtual private networks in the hose model
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
IDMaps: a global internet host distance estimation service
IEEE/ACM Transactions on Networking (TON)
High-density model for server allocation and placement
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Optimal allocation of electronic content
Computer Networks: The International Journal of Computer and Telecommunications Networking
Journal of Algorithms - Special issue: Twelfth annual ACM-SIAM symposium on discrete algorithms
QoS-Aware Replica Placement for Content Distribution
IEEE Transactions on Parallel and Distributed Systems
Optimal Replica Placement Strategy for Hierarchical Data Grid Systems
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Optimizing I/O server placement for parallel I/O on switch-based irregular networks
The Journal of Supercomputing
Optimizing server placement in hierarchical grid environments
The Journal of Supercomputing
Adaptive server selection for large scale interactive online games
Computer Networks: The International Journal of Computer and Telecommunications Networking
Server placement in the presence of competition
GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing
A new template for solving p-median problems for trees in sub-quadratic time
ESA'05 Proceedings of the 13th annual European conference on Algorithms
MMPacking: a load and storage balancing algorithm for distributed multimedia servers
IEEE Transactions on Circuits and Systems for Video Technology
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Although the problem of data server placement in parallel and distributed systems has been studied extensively, most of the existing work assumes there is no competition between servers. Hence, their goal is to minimize read, update and storage cost. In this paper, we study the server placement problem in which a new server has to compete with existing servers for user requests. Therefore, in addition to minimizing cost, we also need to maximize the benefit of building a new server. Our major results include three parts. First, for tree-structured systems, we propose an O(|V|^3k) time dynamic programming algorithm to find the optimal placement of k extra servers that maximizes the benefit in a tree with |V| nodes. We also propose an O(|V|^3) time dynamic programming algorithm to find the optimal placement of extra servers that maximizes the benefit, without any constraint on the number of extra servers. Second, for general connected graphs, we prove that the server placement problems are NP-complete, and present three greedy heuristic algorithms, called Greedy Add, Greedy Remove and Greedy Add-Remove, to solve them. Third, we show that if the number of requests a server can handle (i.e., server capacity) is bounded, the server placement problem is NP-complete even for tree networks. We then derive a variation of the same set of greedy heuristic algorithms, with consideration of server capacity constraint, to solve the problem. Our experiment results demonstrate that the greedy algorithms achieve good results, when compared with the upper bounds found by a linear programming algorithm. Greedy Add performs best in the unconstrained model, yielding a benefit within 12% difference from the theoretical upper bound in average. For the constrained model, Greedy Remove performs best for smaller network sizes, while Greedy Add-Remove performs best for larger network sizes. On average, the heuristic algorithms yield a benefit within 13% difference from the theoretical upper bound in the constrained model.