Towards Autonomic Service Provisioning Systems

TL;DR

This paper presents SPIRE, an autonomic system for service provisioning that dynamically manages server resources and traffic to optimize revenue while meeting QoS constraints, demonstrating adaptability and performance improvements.

Contribution

The paper introduces a novel autonomic architecture for service provisioning that optimizes revenue through dynamic resource allocation and traffic management based on utility functions.

Findings

Revenues significantly increase with proper traffic acceptance conditions.

System adapts effectively to different traffic patterns.

Performance remains robust under changing environmental conditions.

Abstract

This paper discusses our experience in building SPIRE, an autonomic system for service provision. The architecture consists of a set of hosted Web Services subject to QoS constraints, and a certain number of servers used to run session-based traffic. Customers pay for having their jobs run, but require in turn certain quality guarantees: there are different SLAs specifying charges for running jobs and penalties for failing to meet promised performance metrics. The system is driven by an utility function, aiming at optimizing the average earned revenue per unit time. Demand and performance statistics are collected, while traffic parameters are estimated in order to make dynamic decisions concerning server allocation and admission control. Different utility functions are introduced and a number of experiments aiming at testing their performance are discussed. Results show that revenues can be dramatically improved by imposing suitable conditions for accepting incoming traffic; the proposed system performs well under different traffic settings, and it successfully adapts to changes in the operating environment.