The advent of the mobileWeb and the increasing demand for personalized contents arise the need for computationally expensive services, such as dynamic generation and on-the-fly adaptation of contents. Providing these services exacerbates the performance issues that have to be addressed by the underlying Web architecture. When performance issues are addressed through geographically distributed Web systems with a large number of nodes located on the network edge, the dispatching mechanism that distributes requests among the system nodes becomes a critical element. In this paper, we investigate how the granularity of request dispatching may affect the performance of a distributed Web system for personalized contents. Through a real prototype, we compare dispatching mechanisms operating at various levels of granularity for different workload and network scenarios. We demonstrate that the choice of the best granularity for request dispatching strongly depends on the characteristics of the workload in terms of heterogeneity and computational requirements. A coarsegrain dispatching is preferable only when the requests have similar computational requirements. In all other instances of skewed workloads, that we can consider more realistic, a fine-grain dispatching augments the control on the node load and allows the system to achieve better performance.

Impact of request dispatching granularity in geographically distributed Web systems / Andreolini, Mauro; Canali, Claudia; Lancellotti, Riccardo. - STAMPA. - N/A(2007), pp. 45-52. ((Intervento presentato al convegno 6th IEEE International Symposium on Network Computing and Applications (NCA07) tenutosi a Cambridge, MA nel July 2007.

I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Powered by IRIS-about IRIS-Utilizzo dei cookie

 Copyright © 2021