In wireless distributed computing, networked nodes perform intermediate computations over data placed in their memory and exchange these intermediate values to calculate function values. In this paper we consider an asymmetric setting where each node has access to a random subset of the data, i.e., we cannot control the data placement. The paper makes a simple point: we can realize significant benefits if we are allowed to be "flexible", and decide which node computes which function, in our system. We make this argument in the case where each function depends on only two of the data messages, as is the case in similarity searches. We establish a percolation in the behaviour of the system, where, depending on the amount of observed data, by being flexible, we may need no communication at all.
In REF , the authors propose a scheme which gives each server access to a random subset of the input files and not all Reduce functions depend on the entire data set.
The benefit of being flexible in distributed computation
2017 IEEE Information Theory Workshop (ITW)
2017 IEEE Information Theory Workshop (ITW)
Computer Science Mathematics