Equal Requests are Asymptotically Hardest for Data Recovery
J\"uri Lember, Ago-Erik Riet

TL;DR
This paper investigates the difficulty of serving equal user requests in distributed storage, showing they are asymptotically hardest to serve and establishing limits on serviceability for different server content distributions.
Contribution
It provides theoretical evidence that equal requests are asymptotically hardest to serve and introduces new bounds and limits for data recovery in distributed storage systems.
Findings
Equal request sequences are locally hardest to serve.
For uniform server contents, the maximum service ratio approaches 1/2.
The results confirm equal requests are at least as hard to serve as any requests.
Abstract
In a distributed storage system serving hot data, the data recovery performance becomes important, captured e.g. by the service rate. We give partial evidence for it being hardest to serve a sequence of equal user requests (as in PIR coding regime) both for concrete and random user requests and server contents. We prove that a constant request sequence is locally hardest to serve: If enough copies of each vector are stored in servers, then if a request sequence with all requests equal can be served then we can still serve it if a few requests are changed. For random iid server contents, with number of data symbols constant (for simplicity) and the number of servers growing, we show that the maximum number of user requests we can serve divided by the number of servers we need approaches a limit almost surely. For uniform server contents, we show this limit is 1/2, both for sequences…
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Taxonomy
TopicsBig Data Technologies and Applications · Data Quality and Management · Big Data and Business Intelligence
