Buffer Sharing in CSP-like Programs

Most compilers focus on optimizing performance, often at the expense of memory, but efficient memory use can be just as important in constrained environments such as embedded systems. In this paper, we present a memory reduction technique for the deterministic concurrent programming language SHIM. We focus on reducing memory consumption by sharing buffers among the tasks, which use them to communicate using CSP-style rendezvous. We determine pairs of buffers that can never be in use simultaneously and use a shared region of memory for each pair. Our technique produces a static abstraction of a SHIM program’s dynamic behavior, which we then analyze to find buffers that can share memory. Experimentally, we find our technique runs quickly on modest-sized programs and often reduces memory requirements by half

Buffer Sharing in Rendezvous Programs

Most compilers focus on optimizing performance, often at the expense of memory, but efficient memory use can be just as important in constrained environments such as embedded systems. This paper presents a memory reduction technique for rendezvous communication, which is applied to the deterministic concurrent programming language SHIM. It focuses on reducing memory consumption by sharing communication buffers among tasks. It determines pairs of buffers that can never be in use simultaneously and use a shared region of memory for each pair. The technique produces a static abstraction of a SHIM program's dynamic behavior, which is then analyzed to find buffers that are never occupied simultaneously. Experiments show the technique runs quickly on modest-sized programs and can sometimes reduce memory requirements by half

Two genetic algorithms for the bandwidth multicoloring problem

In this paper the Bandwidth Multicoloring Problem (BMCP) and the Bandwidth Coloring Problem (BCP) are considered. The problems are solved by two genetic algorithms (GAs) which use the integer encoding and standard genetic operators adapted to the problems. In both proposed implementations, all individuals are feasible by default, so search is directed into the promising regions. The first proposed method named GA1 is a constructive metaheuristic that construct solution, while the second named GA2 is an improving metaheuristic used to improve an existing solution. Genetic algorithms are tested on the publicly-available GEOM instances from the literature. Proposed GA1 has achieved a much better solution than the calculated upper bound for a given problem, and GA2 has significantly improved the solutions obtained by GA1. The obtained results are also compared with the results of the existing methods for solving BCP and BMCP

On properly ordered coloring of vertices in a vertex-weighted graph

We introduce the notion of a properly ordered coloring (POC) of a weighted graph, that generalizes the notion of vertex coloring of a graph. Under a POC, if xy is an edge, then the larger weighted vertex receives a larger color; in the case of equal weights of x and y, their colors must be different. In this paper, we shall initiate the study of this special coloring in graphs. For a graph G, we introduce the function f(G) which gives the maximum number of colors required by a POC over all weightings of G. We show that f(G) = ℓ(G), where ℓ(G) is the number of vertices of a longest path in G. Another function we introduce is χ POC(G; t) giving the minimum number of colors required over all weightings of G using t distinct weights. We show that the ratio of χ POC(G; t) − 1 to χ(G) − 1 can be bounded by t for any graph G; in fact, the result is shown by determining χ POC(G; t) when G is a complete multipartite graph. We also determine the minimum number of colors to give a POC on a vertex-weighted graph in terms of the number of vertices of a longest directed path in an orientation of the underlying graph. This extends the so called Gallai-Hasse-Roy-Vitaver theorem, a classical result concerning the relationship between the chromatic number of a graph G and the number of vertices of a longest directed path in an orientation of G

OLSR-Aware cross-layer channel access scheduling in wireless mesh networks

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Master's) -- Bilkent University, 2009.Includes bibliographical references leaves 63-68.A wireless mesh network (WMN) is a communications network in which the nodes are organized to form a mesh topology. WMNs are expected to resolve the limitations and significantly improve the performance of wireless ad-hoc, local area, personal area, and metropolitan area networks, which is the reason that they are experiencing fast-breaking progress and deployments. WMNs typically employ spatial TDMA (STDMA) based channel access schemes which are suitable for the high traffic demands of WMNs. Current research trends focus on using loosening the strict layered network implementation in order to look for possible ways of performance improvements. In this thesis, we propose two STDMA-based cross-layer OLSR-Aware channel access scheduling schemes (one distributed, one centralized) that aim better utilizing the network capacity and increasing the overall application throughput by using OLSR-specific routing layer information in link layer scheduling. The proposed centralized algorithm provides a modification of the traditional vertex coloring algorithm while the distributed algorithm is a fully distributed pseudo-random algorithm in which each node makes decisions using local information. Proposed schemes are compared against one another and against their Non-OLSR-Aware versions via extensive ns-2 simulations. Our simulation results indicate that MAC layer can obtain OLSR-specific information with no extra control overhead and utilizing OLSR-specific information significantly improves the overall network performance both in distributed and centralized schemes. We further show that link layer algorithms that target the maximization of concurrent slot allocations do not necessarily increase the application throughput.Kaş, MirayM.S

Algoritmi euristici per la risoluzione di problemi di graph coloring

Il problema del graph coloring è NP-hard, da qui la necessità di usare strategie euristiche che permettano di individuare soluzioni di buona qualità (anche se non ottime) in tempi rapidi e per istanze complesse. L’euristica utilizzata è quella della ricerca locale, con l’obiettivo di studiare gli effetti del principio di prossimità tra soluzioni andando ad utilizzare un solver, come CPLEX, a scatola chiusa per la risoluzione del problema attraverso algoritmi euristici di prossimitàope