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Informative Article | Information Technology | India | Volume 11 Issue 6, June 2022 | Popularity: 5.3 / 10
Optimizing Colocation Infrastructure for AR/VR Workloads: A Granular Bottoms - Up Forecasting Approach
Anurag Reddy
Abstract: This paper presents a comprehensive methodology for achieving precise colocation demand forecasts through a bottoms - up approach. Colocation services play a crucial role in modern IT infrastructure, necessitating accurate predictions for effective resource allocation. The bottoms - up methodology involves a detailed analysis of individual components within the colocation landscape, such as server capacity, network capabilities, and storage requirements. By dissecting the ecosystem into fundamental elements, this approach aims to enhance the granularity of the forecasting process, providing actionable insights for organizations. The exploration delves into key elements critical to the success of bottoms - up forecasting, addressing the nuances of understanding and quantifying server capacity, network capabilities, and storage requirements. This examination contributes to a nuanced understanding of the colocation landscape, enabling informed decisions based on specific infrastructure needs. This paper unfolds a comprehensive bottoms - up methodology designed to forecast colocation demand with unparalleled precision, aligning seamlessly with the evolving needs of AR/VR landscapes. Despite the benefits, implementing bottoms - up forecasting poses challenges, including issues of data accuracy, integrating diverse components, and external factors like technological advancements and market fluctuations. The paper identifies best practices to overcome these challenges, emphasizing continuous monitoring, adaptability to evolving technologies, and flexibility in the forecasting model.
Keywords: Colocation, network failover, overflow site, hard and soft constraints, interconnectivity, PoP, AR/VR applications
Edition: Volume 11 Issue 6, June 2022
Pages: 1973 - 1976
DOI: https://www.doi.org/10.21275/SR24304164522
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