Given a set T of n points in , a Manhattan Network G is a network with all its edges horizontal or vertical segments, such that for all p,q ∈ T, in G there exists a path (named a Manhattan path) of the length exactly the Manhattan distance between p and q. The Minimum Manhattan Network problem is to find a Manhattan network of the minimum length, i.e., the total length of the segments of the network is to be minimized. In this paper we present a 2-approximation algorithm with time complexity O(nlogn), which improves the 2-approximation algorithm with time complexity O(n²). Moreover, compared with other 2-approximation algorithms employing linear programming or dynamic programming technique, it was first discovered that only greedy strategy suffices to get 2-approximation network.