Elastic Remote Methods

TL;DR

ElasticRMI is a middleware system that enables dynamic, application-aware elasticity management for distributed applications, simplifying scaling and increasing portability across cloud environments.

Contribution

It introduces ElasticRMI, a middleware that allows dynamic scaling based on workload and application-specific metrics, with a high-level framework and cloud portability.

Findings

Supports dynamic scaling without major client changes

Uses application-specific data for scaling decisions

Enhances portability across cloud platforms

Abstract

For distributed applications to take full advantage of cloud computing systems, we need middleware systems that allow developers to build elasticity management components right into the applications. This paper describes the design and implementation of ElasticRMI, a middleware system that (1) enables application developers to dynamically change the number of (server) objects available to handle remote method invocations with respect to the application's workload, without requiring major changes to clients (invokers) of remote methods, (2) enables flexible elastic scaling by allowing developers to use a combination of resource utilization metrics and fine-grained application-specific information like the properties of internal data structures to drive scaling decisions, (3) provides a high-level programming framework that handles elasticity at the level of classes and objects, masking low-level platform specific tasks (like provisioning VM images) from the developer, and (4) increases the portability of ElasticRMI applications across different private data centers/IaaS clouds through Apache Mesos.