Analysis of Application Delivery Platform for Software Defined Infrastructures

TL;DR

This paper discusses the challenges faced by application service providers in managing multi-cloud environments and introduces OpenADN as a solution, emphasizing the importance of performance data collection for optimization.

Contribution

It highlights the need for fine-grained behavioral data collection in multi-cloud platforms like OpenADN to improve performance and operational efficiency.

Findings

OpenADN addresses multi-cloud management challenges.

Performance issues impact application delivery efficiency.

Data collection can optimize cost, latency, and energy use.

Abstract

Application Service Providers (ASPs) obtaining resources from multiple clouds have to contend with different management and control platforms employed by the cloud service providers (CSPs) and network service providers (NSP). Distributing applications on multiple clouds has a number of benefits but the absence of a common multi-cloud management platform that would allow ASPs dynamic and real-time control over resources across multiple clouds and interconnecting networks makes this task arduous. OpenADN, being developed at Washington University in Saint Louis, fills this gap. However, performance issues of such a complex, distributed and multi-threaded platform, not tackled appropriately, may neutralize some of the gains accruable to the ASPs. In this paper, we establish the need for and methods of collecting precise and fine-grained behavioral data of OpenADN like platforms that can be used to optimize their behavior in order to control operational cost, performance (e.g., latency) and energy consumption.