The bounded diameter minimum spanning tree (BDMST) problem is NP-hard and appears e.g. in communication network design when considering certain quality of service requirements. Prior exact approaches for the BDMST problem mostly rely on network flow-based mixed integer linear programming and Miller-Tucker-Zemlin-based formulations. This article presents a new, compact 0–1 integer linear programming model, which is further strengthened by dynamically adding violated connection and cycle elimination constraints within a branch-and-cut environment. The proposed approach is empirically compared to two recently published formulations. It turns out to work well in particular on dense instances with tight diameter bounds.

In numerous practical applications, it is necessary to find the smallest possible tree with a bounded diameter. A diameter-constrained minimum spanning tree (DCMST) of a given undirected, edge-weighted graph, G, is the smallest-weight spanning tree of all spanning trees of G which contain no path with more than k edges, where k is a given positive integer. The problem of finding a DCMST is NP-complete for all values of k; 4 k (n -- 2), except when all edge-weights are identical. A DCMST is essential for the efficiency of various distributed mutual exclusion algorithms, where it can minimize the number of messages communicated among processors per critical section. It is also useful in linear lightwave networks, where it can minimize interference in the network by limiting the traffic in the network lines. Another practical application requiring a DCMST arises in data compression, where some algorithms compress a file utilizing a tree data-structure, and decompress a path in the tree to access a record. A DCMST helps such algorithms to be fast without sacrificing a lot of storage space. We present a survey of the literature on the DCMST problem, study the expected diameter of a random labeled tree, and present five new polynomial-time algorithms for an approximate DCMST. One of our new algorithms constructs an approximate DCMST in a modified greedy fashion, employing a heuristic for selecting an edge to be added to iii the tree in each stage of the construction. Three other new algorithms start with an unconstrained minimum spanning tree, and iteratively refine it into an approximate DCMST. We also present an algorithm designed for the special case when the diameter is required to be no more than 4. Such a diameter-4 tree is also used for evaluating the quality of o...

Abstract. Given a set S of points (stations) located in the d-dim. Euclidean space and a root b ∈ S, the h-hops Convergecast problem asks to find for a minimal energy-cost range assignment which allows to perform the converge-cast primitive (i.e. node accumulation) towards b in at most h hops. For this problem no polynomial time algorithm is known even for h = 2. The main goal of this work is the design of an efficient distributed heuristic (i.e. protocol) and the analysis (both theoretical and experimental) of its expected solution cost. In particular, we introduce an efficient parameterized randomized protocol for h-hops Convergecast and we analyze it on random instances created by placing n points uniformly at random in a d-cube of side length L. We prove that for h = 2, its expected approximation ratio is bounded by some constant factor. Finally, for h = 3,..., 8, we provide a wide experimental study showing that our protocol has very good performances when compared with previously introduced (centralized) heuristics. 1

Due to the extraordinary growth in the demand of mobile communication services in general, design of efficient systems for providing specialized services has also be-come an important issue in wireless mobility research. Broadly speaking, there are two major models for wireless networking: single-hop and multi-hop. The single-

To generate a multicast routing tree guaranteeing the quality of service (QoS), we consider the hop constrained Steiner tree problem and propose a new mathematical formulation for it, which contains fewer constraints than a known formulation. An efficient procedure is also proposed to solve the problem. Preliminary tests show that the procedure reduces the computing time significantly.

Spanning Tree Problem is about finding a minimum cost spanning tree, subjected to pre-defined constraints on the number of edges that can integrate the path between any pair of nodes. This problem typically models network design applications where all vertices must communicate with each other at a minimum cost, while meeting a given quality requirement. This is the typical situation addressed in an environment of Multi-Protocol Label Switching networks over Wavelength Division Multiplexing network design, in which an IP travelling pack goes through a delay queuing, proportional to the number of Label Switching Routers that it crosses. In this paper we describe different types of heuristics that were implemented in order to find optimal or near-optimal solutions to solve this problem. Index Terms — Diameter constrained spanning tree, heuristics, graphs, network optimization.

The d-Dim h-hops MST problem is defined as follows: Given a set S of points in the d-dimensional Euclidean space and s ∈ S, find a minimum-cost spanning tree for S rooted at s with height at most h. We investigate the problem for any constant h and d> 0. We prove the first non trivial lower bound on the solution cost for almost all Euclidean instances (i.e. the lower-bound holds with high probability). Then we introduce an easy-to-implement, fast divide et impera heuristic and we prove that its solution cost matches the lower bound.