In a multihop network, radio packets are often relayed through inter-mediate stations (repeaters) in order to transfer a radio packet from a source to its destination. We consider a scheduling problem in a multihop network using a graphtheoretical model. Let D=(V,A) be the digraph with a vertex set V and an arc set A. Let f be a labeling of positive integers on the arcs of A. The value of f(u,v) means a frequency band assigned on the link from u to v. We call f antitransitive if f(u,v)f(v,w) for any adjacent arcs (u,v) and (v,w) of D. The minimum antitransitive-labeling problem is the problem of finding a minimum antitransitive-labeling such that the number of integers assigned in an antitransitive labeling is minimum. In this paper, we prove that this problem is NP-hard, and we propose a simple distributed approximation algorithm for it.

The lower-bounded p-collection problem is the problem where to locate p sinks in a flow network with lower bounds such that the value of a maximum flow is maximum. This paper discusses the cover problems corresponding to the lower bounded p-collection problem. We consider the complexity of the cover problem, and we show polynomial time algorithms for its subproblems in a network with tree structure.

Problems of realizing a vertex-weighted tree with a given weighted tranamission number sequence are discussed in this paper. First we consider properties of the weighted transmission number sequence of a vertex-weighted tree. Let S be a sequence whose terms are pairs of a non-negative integer and a positive integer. The problem determining whether S is the weighted transmission number sequence of a vertex-weighted tree or not, is called w-TNS. We prove that w-TNS is NP-complete, and we show an algorithm using backtracking. This algorithm always gives a correct solution. And, if each transmission number of S is different to the others, then the time complexity of this is only 0( S 2).Next we consider the d2-transmission number sequence so that the distance function is defined by a special convex function.

The p-collection problem is where to locate p sinks in a flow network such that the value of a maximum flow is maximum. In this paper we show complexity results of the p-collection problem. We prove that the decision problem corresponding to the p-collection problem is strongly NP-complete. Although location problems (the p-center problem and the p-median problem) in networks and flow networks with tree structure is solvable in polynomial time, we prove that the decision problem of the p-collection problem in networks with tree structure, is weakly NP-complete. And we show a polynomial time algorithm for the subproblem of the p-collection problem such that the degree sum of vertices with degree3 in a network, is bound to some constant K0.

In this paper we extend the p-collection problem to a flow network with lower bounds, and call the extended problem the lower-bounded p-collection problem. First we discuss the complexity of this problem to show NP-hardness for a network with path structure. Next we present a linear time algorithm for the lower-bounded 1-collection problem in a network with tree structure, and a pseudo-polynomial time algorithm with dynamic programming type for the lower-bounded p-collection problem in a network with tree structure. Using the pseudo-polynomial time algorithm, we show an exponential algorithm, which is efficient in a connected network with few cycles, for the lower-bounded p-collection problem.