Platforms for Building and Deploying Applications for Cloud Computing

Cloud computing is rapidly emerging as a new paradigm for delivering IT services as utlity-oriented services on subscription-basis. The rapid development of applications and their deployment in Cloud computing environments in efficient manner is a complex task. In this article, we give a brief introduction to Cloud computing technology and Platform as a Service, we examine the offerings in this category, and provide the basis for helping readers to understand basic application platform opportunities in Cloud by technologies such as Microsoft Azure, Sales Force, Google App, and Aneka for Cloud computing. We demonstrate that Manjrasoft Aneka is a Cloud Application Platform (CAP) leveraging these concepts and allowing an easy development of Cloud ready applications on a Private/Public/Hybrid Cloud. Aneka CAP offers facilities for quickly developing Cloud applications and a modular platform where additional services can be easily integrated to extend the system capabilities, thus being at pace with the rapidly evolution of Cloud computing.

💡 Research Summary

The paper provides a comprehensive overview of cloud computing with a particular focus on the Platform‑as‑a‑Service (PaaS) layer, comparing mainstream commercial offerings (Microsoft Azure, Google App Engine, Salesforce Force.com) with the authors’ own solution, Manjrasoft Aneka. It begins by outlining the evolution of cloud computing from utility‑style IT delivery to the three primary service models—Infrastructure‑as‑a‑Service (IaaS), Platform‑as‑a‑Service (PaaS), and Software‑as‑a‑Service (SaaS)—and the three deployment models (public, private, hybrid). A concise taxonomy of providers for each model is presented, establishing the context for the subsequent analysis.

In the second section the four PaaS platforms are examined in detail. Azure is described as a Microsoft‑centric environment that requires SQL Azure for database services, limiting flexibility for non‑SQL workloads. Google App Engine is highlighted for its language support (Java, Python), local development simulator, and seamless scaling on Google’s infrastructure. Force.com is portrayed as a CRM‑focused platform that uses the proprietary Apex language, offering rapid development for business applications but with limited general‑purpose capabilities.

The core contribution of the paper is the in‑depth description of the Aneka Cloud Application Platform (CAP). Aneka is built on a Service‑Oriented Architecture (SOA) that separates concerns into three hierarchical service layers:

1. Fabric Services – responsible for low‑level cloud infrastructure functions such as node membership, high‑availability, fault‑tolerance, resource provisioning, hardware profiling, and performance monitoring.
2. Foundation Services – provide cross‑cutting capabilities including storage management, resource reservation, accounting, billing, licensing, and system‑wide monitoring. These services are accessible to both administrators and developers.
3. Application Programming Services – expose runtime environments for specific programming models. Aneka currently supports three models: a Task model for parameter‑sweep and embarrassingly parallel workloads, a Thread model that mimics local multithreading on remote nodes, and a .NET implementation of the MapReduce paradigm for data‑intensive processing.

The platform’s extensibility is emphasized: new services or programming models can be plugged into the existing architecture with minimal code changes, and the middleware runs on both Windows and Linux hosts, allowing deployment on physical desktops, clusters, virtual machines, or public clouds (e.g., Amazon EC2, GoGrid).

Aneka’s developer‑facing tools are the Software Development Kit (SDK) and the Management Kit. The SDK enables rapid construction of distributed applications, integration of scaling logic into legacy code, and creation of custom services. The Management Kit offers a graphical interface for provisioning, monitoring, accounting, and user management, thereby reducing operational overhead.

Section 4 presents three real‑world case studies that demonstrate Aneka’s practical impact. In the manufacturing and engineering domain, the GoFront division of China Southern Railway used Aneka to build an internal cloud of networked PCs for Autodesk Maya rendering; the time to render 2,000 frames dropped from three days on a single four‑core machine to a few hours across the Aneka cluster. In the geospatial domain, large satellite image processing pipelines were parallelized using the Task model, achieving significant throughput gains. In life‑science research, a genomics workflow was ported to the Thread model, allowing seamless scaling from a laboratory server to a hybrid cloud without code modification. All three examples illustrate Aneka’s ability to run unchanged on private, public, or hybrid clouds, confirming its claim of vendor‑agnostic elasticity.

The paper concludes by summarizing Aneka’s strengths: vendor independence, cross‑platform support, modular SOA design, built‑in accounting/billing, and support for multiple programming models. It also acknowledges limitations, notably the lack of detailed security and multi‑tenant isolation studies, and the relatively sparse performance benchmarking against competing PaaS solutions. Future work is suggested to address these gaps, to enrich the platform with additional programming models, and to automate scaling policies.

Overall, the article situates Aneka within the broader PaaS landscape, argues convincingly for its technical advantages, and validates its utility through concrete industrial applications, making a solid case for its adoption in scenarios requiring flexible, scalable, and manageable cloud‑based application execution.