are more practical and are currently used in all existing literatures [@el2010fractional; @gopalan2012locality; @papailiopoulos2012locally; @kamath2014codes]; and the [*dynamic helper selection*]{} (DHS) schemes, which are the most general form of helper selection.

However, a complete characterization of the effect of choosing the helper nodes in RCs, including SHS and DHS, on the storage-bandwidth tradeoff is still lacking. This motivates the following open questions: Under what condition is it beneficial to proactively choose the helper nodes (including SHS and DHS)? Is it possible to analytically quantify the benefits of choosing the good helpers? Specifically, the answers to the aforementioned fundamental questions were still unknown.

In this paper, we answer the first question by providing a necessary and sufficient condition under which optimally choosing the helpers strictly improves the storage-bandwidth tradeoff. By answering such a fundamental information-theoretic question, our answers will provide a rigorous benchmark/guideline when designing the next-generation smart helper selection solutions.

The main contribution of this work is two-fold. Firstly, we prove that, under a certain condition, even the best optimal helper selection can do no better than the simplest BHS scheme. Using information-theoretic terminology, this answers the [*converse*]{} part of the problem. Secondly, we prove that when those conditions are 