Data Locality Optimization for Low Latency Distributed Systems

Arunkumar Sambandam

Data Locality Optimization for Low Latency Distributed Systems

Author(s)	Arunkumar Sambandam
Country	United States
Abstract	Distributed systems rely on partitioned data placement across multiple nodes to achieve scalability and parallel processing. As the number of nodes increases, client requests frequently traverse several intermediate machines before reaching the target data location. This multi hop communication introduces additional routing overhead, longer transmission paths, and increased network delay. Although simple to implement, this approach often leads to inefficient communication patterns where requests are forced to travel across distant nodes even when closer alternatives exist. In large scale environments, the effect of excessive hop traversal becomes more pronounced. Each additional hop contributes to higher message propagation time, increased switch processing, and greater network congestion. As cluster size grows, the average hop count rises steadily, resulting in longer response times and reduced overall efficiency. Systems experiencing high hop counts also consume more bandwidth and incur higher infrastructure overhead due to repeated inter node communication. These inefficiencies degrade performance and limit scalability despite the availability of additional computational resources. Workloads with frequent cross node interactions further amplify this problem. Static data placement fails to adapt to evolving access patterns, causing requests to repeatedly traverse unnecessary network paths. The accumulation of such traversals increases latency variability and reduces predictable system behavior. Consequently, minimizing hop distance between clients and data becomes critical for improving communication efficiency in distributed architectures. These limitations highlight the need for placement strategies that prioritize proximity and reduce inter node traversal. This paper addresses the problem of excessive hop count in distributed systems and focuses on improving communication efficiency by reducing the average number of hops required for data access.
Keywords	Distributed, Locality, Partitioning, Hops, Latency, Routing, Placement, Scalability, Clustering, Proximity, Communication, Optimization, Throughput, Efficiency, Networking.
Published In	Volume 16, Issue 2, July-December 2025
Published On	2025-09-01
Cite This	Data Locality Optimization for Low Latency Distributed Systems - Arunkumar Sambandam - IJAIDR Volume 16, Issue 2, July-December 2025.

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Data Locality Optimization for Low Latency Distributed Systems

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