The wireless sensor network node optimal coverage is a typical multi-objective optimization problem, this problem can be expressed as follows: existing sensor set S = (s 1, s 2, ⋯, s i, ⋯, s N ), seeking the working set S′, which can obtain the maximum network coverage rate, and the minimum working node set.
When the maximum network coverage rate is selected as the optimal objective, network sensor nodes with hexagon structure distributed in the monitoring area, the minimum working nodes set can be obtained [33].
From formula (5), we know that the maximum network coverage f 1(S′) and minimum working nodes set f 2(S′) are contradictory; compromising the two, the multi-objective optimization coverage model of wireless sensor network is changed into the maximum objective function f(S′).
For any set S of aligned binary sequences, the median network comprises as nodes all sequences that can be successively generated from S by taking majority consensus, so that the links constitute the minimum spanning network for the total node set [35], [41].
We therefore post-process the ML trees by collapsing all nodes of common sequence (both observed haplotypes and inferred Steiner nodes) and relinking the resulting non-redundant node set into a minimum-cost spanning tree.
Though the heuristics for both the minimum edge dominating set and minimum node connected dominating set problems have a computational time-complexity that is smaller than our proposed O(EVlogV) heuristic for maximal assortative matching, these heuristics cannot be applied for the problem of focus in this paper.
The nodes in TCTSP are partitioned into two kinds of subsets: clusters and tabu node sets, then the salesman has to visit exactly one node for each tabu node set and ensures that the nodes within a same cluster are visited consecutively, and the problem calls for a minimum cost cycle.
Furthermore, the storage nodes are divided into a hot node set and a cold node set.
Having received the messages, each node sets the neighbor with the minimum cost as its parent.
