  We consider load balancing problem in a cache network consisting of
storage-enabled servers forming a distributed content delivery scenario.
Previously proposed load balancing solutions cannot perfectly balance out
requests among servers, which is a critical issue in practical networks.
Therefore, in this paper, we investigate a coded cache content placement where
coded chunks of original files are stored in servers based on the files
popularity distribution. In our scheme, upon each request arrival at the
delivery phase, by dispatching enough coded chunks to the request origin from
the nearest servers, the requested file can be decoded.
  Here, we show that if $n$ requests arrive randomly at $n$ servers, the
proposed scheme results in the maximum load of $O(1)$ in the network. This
result is shown to be valid under various assumptions for the underlying
network topology. Our results should be compared to the maximum load of two
baseline schemes, namely, nearest replica and power of two choices strategies,
which are $\Theta(\log n)$ and $\Theta(\log \log n)$, respectively. This
finding shows that using coding, results in a considerable load balancing
performance improvement, without compromising communications cost performance.
This is confirmed by performing extensive simulation results, in non-asymptotic
regimes as well.
