AJAX vs HTML Performance on XML and TCP/IP Networks
This paper describes the research methodology for a dissertation investigating how AJAX and HTML applications perform across different network types. The study employs a two-by-two matrix design comparing application types (AJAX vs. HTML) against network protocols (TCP/IP vs. XML). The research comprises three phases: construction of a standardized test-bed using Linux servers and SQL Server databases, development of AJAX applications using Ruby on Rails to ensure coding consistency, and execution of automated performance testing using Cisco network analyzers. The methodology emphasizes minimizing variation through identical server configurations, standardized application code, and simulated real-world network traffic patterns. Key findings indicate that AJAX code quality and conciseness significantly outweigh XML compression techniques in determining application performance.
- Research Design Overview: 2×2 matrix comparing AJAX and HTML applications
- Phase 1: Test-Bed Construction and Configuration: Linux servers, SQL databases, network traffic simulation
- Phase 2: AJAX Application Development: Ruby on Rails coding standardization and API selection
- Phase 3: Testing Execution and Analysis: Cisco analyzer testing, automation, and performance measurement
- Conclusion: Implications and Key Findings: AJAX code quality drives mobile and enterprise optimization
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What makes this paper effective
- Provides a clear, systematic structure that walks readers through three distinct phases of research methodology, making the experimental design easy to follow and replicate.
- Emphasizes control of variables throughout, explicitly stating why each decision (server configuration, programming language, database setup) was made to reduce experimental error.
- Connects abstract methodology to practical implications, particularly regarding mobile platform optimization and real-world business applications.
- Uses concrete technical details (Intel blade servers, Red Hat Linux, SQL Server, Ruby on Rails, Cisco analyzers) to ground the methodology in actual implementation rather than theory.
Key academic technique demonstrated
The paper employs controlled experimental design by deliberately standardizing all variables except those being tested (network type and application type). This is evident in the insistence on identical server configurations, matching SQL Server installations, and consistent AJAX coding standards. The author justifies each methodological choice by referencing either technical reliability (proven APIs) or research literature, demonstrating how rigorous methodology supports defensible conclusions.
Structure breakdown
The paper follows a logical progression from design overview through three sequential implementation phases to conclusion. The introduction establishes the 2×2 matrix framework and validates the research design. Each phase section details what was accomplished, why specific technologies were chosen, and how choices minimized variation. The conclusion synthesizes the methodology's outcome, presents key findings about AJAX code quality, and extrapolates implications for mobile and enterprise applications, bridging technical detail with practical value.
Research Design Overview
The primary objective of this dissertation is to measure the performance of optimized AJAX (asynchronous JavaScript and XML) applications on both XML and TCP/IP-based networks. To define the research plan clearly and concisely, a two-by-two matrix comparing the performance of applications by network type was created. The two application types compared were AJAX and HTML; the two networks were TCP/IP and XML.
This research design effectively captures page-based performance of HTML across two different networks, consistent with HTML's approach to defining web applications. AJAX performance was captured at the component level, allowing for granular analysis of optimization techniques. The two-by-two matrix simplified the research design and isolated the effects of HTML versus AJAX-based applications, enabling clear attribution of performance differences to either application architecture or network protocol rather than confounding factors.
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