Faster Deterministic All Pairs Shortest Paths in Congest Model

We present a new deterministic algorithm for distributed weighted all pairs shortest paths (APSP) in both undirected and directed graphs. Our algorithm runs in ~O(n4/3 ) rounds in the Congest models on graphs with arbitrary edge weights, and it improves on the previous ~O(n3/2) bound of Agarwal et al. [ARKP18]. The main components of our new algorithm are a new faster technique for constructing blocker set deterministically and a new pipelined method for deterministically propagating distance values from source nodes to the blocker set nodes in the network. Both of these techniques have potential applications to other distributed algorithms. Our new deterministic algorithm for computing blocker set adapts the NC approximate hypergraph set cover algorithm in Berger et al. [BRS94] to the distributed construction of a blocker set. It follows the two-step process of first designing a randomized algorithm that uses only pairwise independence, and then derandomizes this algorithm using a sample space of linear size. This algorithm runs in almost the same number of rounds as the initial step in our APSP algorithm that computes h-hops shortest paths. This result significantly improves on the deterministic blocker set algorithms in [ARKP18, AR19] by removing an additional n ·|Q| term in the round bound, where Q is the blocker set. The other new component in our APSP algorithm is a deterministic pipelined approach to propagate distance values from source nodes to blocker nodes. We use a simple natural round-robin method for this step, and we show using a suitable progress measure that it achieve the ~O(n4/3) bound on the number of rounds. It appears that the standard deterministic methods for efficiently broadcasting multiple values, and for sending or receiving messages using the routing schedule in an undirected APSP algorithm [HPDG+19,LSP19] do not apply to this setting.