Online Multi-Coloring with Advice

We consider the problem of online graph multi-coloring with advice. Multi-coloring is often used to model frequency allocation in cellular networks. We give several nearly tight upper and lower bounds for the most standard topologies of cellular networks, paths and hexagonal graphs. For the path, negative results trivially carry over to bipartite graphs, and our positive results are also valid for bipartite graphs. The advice given represents information that is likely to be available, studying for instance the data from earlier similar periods of time.Comment: IMADA-preprint-c

Graph multicoloring reduction methods and application to McDiarmid-Reed's Conjecture

A $(a,b)$-coloring of a graph $G$ associates to each vertex a set of $b$ colors from a set of $a$ colors in such a way that the color-sets of adjacent vertices are disjoints. We define general reduction tools for $(a,b)$-coloring of graphs for $2\le a/b\le 3$. In particular, we prove necessary and sufficient conditions for the existence of a $(a,b)$-coloring of a path with prescribed color-sets on its end-vertices. Other more complex $(a,b)$-colorability reductions are presented. The utility of these tools is exemplified on finite triangle-free induced subgraphs of the triangular lattice. Computations on millions of such graphs generated randomly show that our tools allow to find (in linear time) a $(9,4)$-coloring for each of them. Although there remain few graphs for which our tools are not sufficient for finding a $(9,4)$-coloring, we believe that pursuing our method can lead to a solution of the conjecture of McDiarmid-Reed.Comment: 27 page

Approximation and online algorithms in scheduling and coloring

In the last three decades, approximation and online algorithms have become a major area of theoretical computer science and discrete mathematics. Scheduling and coloring problems are among the most popular ones for which approximation and online algorithms have been analyzed. On one hand, motivated by the well-known difficulty to obtain good lower bounds for the problems, it is particularly hard to prove results on the online and offline performance of algorithms. On the other hand, the theoretically oriented studies of approximation and online algorithms for scheduling and coloring have also impact on the development of better algorithms for real world applications. In the thesis we present approximation algorithms and online algorithms for a number of scheduling and labeling (coloring) problems. Our work in the first part of the thesis is devoted to scheduling problems with the average weighted completion time objective function, that is primarily motivated by some theoretical questions which were open for a number of recent years. Here we present a general method which leads to the design of polynomial time approximation schemes (PTASs), best possible approximation results. In contrast, our work in the second part of the thesis is motivated by practical applications. We consider a number of new labeling and scheduling problems which occur in the design of communication networks. Here we present and analyze efficient approximation and online algorithms. We use very simple techniques which do not require large computational resources

1-local 33/24-competitive Algorithm for Multicoloring Hexagonal Graphs

Graph TheoryIn the frequency allocation problem, we are given a cellular telephone network whose geographical coverage area is divided into cells, where phone calls are serviced by assigned frequencies, so that none of the pairs of calls emanating from the same or neighboring cells is assigned the same frequency. The problem is to use the frequencies efficiently, i.e. minimize the span of frequencies used. The frequency allocation problem can be regarded as a multicoloring problem on a weighted hexagonal graph, where each vertex knows its position in the graph. We present a 1-local 33/24-competitive distributed algorithm for multicoloring a hexagonal graph, thereby improving the previous 1-local 7/5-competitive algorithm

Spectrum and power optimization for wireless multiple access networks.

Emerging high-density wireless networks in urban area and enterprises offer great potential to accommodate the anticipated explosion of demand for wireless data services. To make it successful, it is critical to ensure the efficient utilisation of limited radio resources while satisfying predefined quality of service. The objective of this dissertation is to investigate the spectrum and power optimisation problem for densely deployed access points (APs) and demonstrate the potential to improve network performance in terms of throughput and interference. Searching the optimal channel assignment with minimum interference is known as an AfV-haxd problem. The increased density of APs in contrary to the limited usable frequencies has aggravated the difficulty of the problem. We adopt heuristic based algorithms to tackle both centralised and distributed dynamic channel allo cation (DCA) problem. Based on a comparison between Genetic Algorithm and Simulated Annealing, a hybrid form that combines the two algorithms achieves good trade-off between fast convergence speed and near optimality in centralised scenario. For distributed DCA, a Simulated Annealing based algorithm demon strates its superiority in terms of good scalability and close approximation to the exact optimal solution with low algorithm complexity. The high complexity of interactions between transmit power control (TPC) and DCA renders analytical solutions to the joint optimisation problems intractable. A detailed convergence analysis revealed that optimal channel assignment can strengthen the stability condition of TPC. Three distributed algorithms are pro posed to interactively perform the DCA and TPC in a real time and open ended manner, with the ability to appropriately adjust power and channel configurations according to the network dynamics. A real network with practical measurements is employed to quantify and verify the theoretical throughput gain of their inte gration. It shows that the integrated design leads to a substantial throughput improvement and power saving compared with conventional fixed-power random channel allocation system

1-local 33/24-competitive Algorithm for Multicoloring Hexagonal Graphs

Graph Theor

Software for Exascale Computing - SPPEXA 2016-2019

This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest