Ensuring Fault Tolerance and Consistency in Distributed Systems Using Zab

Authors: Naveen Srikanth Pasupuleti

DOI: https://doi.org/10.37082/IJIRMPS.v9.i4.232536

Short DOI: https://doi.org/g9p7mw

Country: USA

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Abstract: In modern distributed systems, efficient write operations are critical to achieving high performance and responsiveness. However, as systems scale, the overhead associated with managing writes can become a bottleneck, particularly when batching techniques are used. Write batching is a common strategy to reduce the overhead of frequent write operations by grouping them together into a single batch. This approach reduces the number of transactions or communication rounds required to commit data, thus improving throughput. However, it also introduces a significant challenge: high write latency. High write latency occurs when the time it takes to write data to the system becomes excessive, resulting in delayed responses to clients and reduced overall system efficiency. The latency in write batching systems is often influenced by several factors, including the time required to accumulate enough writes to form a full batch, the coordination required between nodes, and the delay in flushing the batch to persistent storage or replicating it across the system If there are many write requests arriving at the same time, the system might need to handle conflicts or lock resources, leading to delays before writes can be committed. In some cases, partial batches—where not enough writes have accumulated—may need to be handled separately, further adding to the overhead. The high write latency in batching systems becomes especially pronounced when dealing with large numbers of nodes or when the network communication is slow or unreliable. As the system scales horizontally, the coordination and communication overhead grow, potentially exacerbating the delay in committing batches. This trade-off between write efficiency and latency is a fundamental challenge in distributed systems. If the system has a large batch size or a long flush period, this waiting time can lead to a noticeable delay in processing individual write requests. To address this issue, optimizing write batching systems requires strategies that balance the need for efficient coordination with minimizing delays. Reducing quorum requirements, implementing more efficient conflict resolution mechanisms, and dynamically adjusting batch sizes can help mitigate the impact of high write latency. Furthermore, leveraging algorithms that reduce the number of communication rounds, such as optimizing consensus protocols, can also help achieve better performance while ensuring consistency across the system. This paper addresses the high write latency issue which write operations are facing with the help of fast paxos algorithm.

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Paper Id: 232536

Published On: 2021-08-13

Published In: Volume 9, Issue 4, July-August 2021

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