EXPERIMENTAL RESULTS

This section presents experimental results from the Muse prototype to show the behavior of dynamic server resource management. These experiments consider the simple case of a symmetric cluster with a single server pool.

Experimental Setup
Depicts the data center testbed, which consists of a server pool driven by traffic-generating clients through two redirecting switches. The servers are 450 MHz Pentium-III systems (Asus P2B/440BX). These servers run FreeBSD 4.3 and multiple instances of Apache version 1.3.12, each in its own resource container. Read the rest of this entry »

PROTOTYPE

The Muse prototype includes a user-level executive server and two loadable kernel modules for the FreeBSD operating system, implementing a host-based redirecting server switch and load monitoring extensions for the servers. In addition, the prototype uses the Resource Containers kernel modules from Rice University [10, 8] as a mechanism to allocate resources to service classes on individual servers. The following subsections discuss key elements of the prototype in more detail. Read the rest of this entry »

THE RESOURCE ECONOMY

This section details the system’s framework for allocating resources to competing co-hosted services (customers). The basic challenge is to determine the resource demand of each customer at its current request load level, and to allocate resources to their most efficient and productive use. Resources are left idle if the marginal cost to use them (e.g., energy) is less than the marginal value of deploying them to improve performance at current load levels. To simplify the discussion, we consider a single server pool with a common unit of hosting service resource. This unit could represent CPU time or a combined measure reflecting a share of aggregate CPU, memory, and storage resources. Section 4.6 discusses the problem of provisioning multiple resource classes. Read the rest of this entry »

OVERVIEW OF MUSE

Muse is an operating system for a hosting center. The components of the hosting center are highly specialized, governed by their own internal operating systems and interacting at high levels of abstraction. The role of the center’s operating system is to establish and coordinate these interactions, supplementing the operating systems of the individual components.

 Generic server appliances. Pools of shared servers act together to serve the request load of each co-hosted service.
Server resources are generic and interchangeable.
 Reconfigurable network switching fabric. Switches dynamically redirect incoming request traffic to eligible servers. Read the rest of this entry »

MOTIVATION

Hosting utilities provision server resources for their customers-co-hosted server applications or services-according to their resource demands at their expected loads. Since outsourced hosting is a competitive business, hosting centers must manage their resources efficiently. Rather than overprovisioning for the worstcase load, efficient admission control and capacity planning policies may be designed to limit rather than eliminate the risk of failing to meet demand [8, 2]. An efficient resource management scheme would automatically allocate to each service the minimal server resources needed for acceptable service quality, leaving surplus resources free to deploy elsewhere. Provisioning choices must adapt to changes in load as they occur, and respond gracefully to unanticipated demand surges or resource failures. Read the rest of this entry »

INTRODUCTION

The Internet buildout is driving a shift toward server-based computing. Internet-based services host content and applications in data centers for networked access from diverse client devices. Service providers are adding new data center capacity for Web hosting, application services, outsourced storage, electronic markets, and other network services. Many of these services are co-hosted in shared data centers managed by third-party hosting providers.
Managed hosting in shared centers offers economies of scale and a potential for dynamic capacity provisioning to respond to request traffic, quality-of-service specifications, and network conditions. Read the rest of this entry »

ABSTRACT

Internet hosting centers serve multiple service sites from a common hardware base. This paper presents the design and implementation of an architecture for resource management in a hosting center operating system, with an emphasis on energy as a driving resource management issue for large server clusters. The goals are to prov sion server resources for co-hosted services in a way that automatically adapts to offered load, improve the energy efficiency of server clusters by dynamically resizing the active server set, and respond to power supply disruptions or thermal events by degrading service in accordance with negotiated Service Level Agreements (SLAs). Read the rest of this entry »