Optimizing Performance in Mobile Applications with Edge Computing
DOI:
https://doi.org/10.36676/urr.v10.i2.1329Keywords:
Edge computing, mobile applications, performance optimization, latency reduction, real-time analyticsAbstract
In the ever-evolving landscape of mobile computing, the performance and responsiveness of mobile applications are critical factors influencing user satisfaction and engagement. Traditional cloud-based approaches, while effective, often suffer from latency issues due to the distance data must travel between the user’s device and the cloud servers. This latency can significantly impact the user experience, especially in applications requiring real-time data processing and responsiveness. Edge computing has emerged as a promising solution to address these challenges by bringing computational resources closer to the end user.
Edge computing decentralizes data processing by distributing computational tasks across a network of local nodes, or "edges," which are closer to the source of data. This architecture reduces the distance data must travel, thereby decreasing latency and improving application performance. The integration of edge computing in mobile applications allows for faster data processing, real-time analytics, and improved overall user experience.
This paper explores the optimization of mobile application performance through the implementation of edge computing strategies. It begins with an overview of edge computing principles, highlighting its benefits over traditional cloud computing, including reduced latency, improved bandwidth efficiency, and enhanced data privacy. The paper then delves into various use cases where edge computing can be particularly beneficial for mobile applications, such as augmented reality (AR), virtual reality (VR), and Internet of Things (IoT) applications. By examining these use cases, the paper illustrates how edge computing can address specific performance challenges and enhance the functionality of mobile apps.
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