Resource Allocation Strategies for In-Network Stream Processing
| dc.creator | Benoit, Anne | |
| dc.creator | Casanova, Henri | |
| dc.creator | Rehn-Sonigo, Veronika | |
| dc.creator | Robert, Yves | |
| dc.date | 2008-07-10 | |
| dc.date.accessioned | 2026-07-07T09:49:38Z | |
| dc.date.available | 2026-07-07T09:49:38Z | |
| dc.description | In this paper we consider the operator mapping problem for in-network stream processing applications. In-network stream processing consists in applying a tree of operators in steady-state to multiple data objects that are continually updated at various locations on a network. Examples of in-network stream processing include the processing of data in a sensor network, or of continuous queries on distributed relational databases. We study the operator mapping problem in a ``constructive'' scenario, i.e., a scenario in which one builds a platform dedicated to the application buy purchasing processing servers with various costs and capabilities. The objective is to minimize the cost of the platform while ensuring that the application achieves a minimum steady-state throughput. The first contribution of this paper is the formalization of a set of relevant operator-placement problems as linear programs, and a proof that even simple versions of the problem are NP-complete. Our second contribution is the design of several polynomial time heuristics, which are evaluated via extensive simulations and compared to theoretical bounds for optimal solutions. | |
| dc.identifier | https://arxiv.org/abs/0807.1720 | |
| dc.identifier | http://arxiv.org/abs/0807.1720 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/164663 | |
| dc.subject | Distributed, Parallel, and Cluster Computing | |
| dc.title | Resource Allocation Strategies for In-Network Stream Processing | |
| dc.type | text |