6414828
Local Search Genetic Algorithm for Optimization of Highly Reliable Communications Networks
This paper presents a genetic algorithm (GA) with specialized encoding, initialization and local search genetic operators to optimize communication network topologies. This NPhard problem is often highly constrained so that random initialization and standard genetic operators usually generate infeasible network architectures. Compounding this infeasibility issue is that the fitness function involves calculating the all-terminal reliability of the network, a calculation which is computationally expensive. Therefore, it is imperative that the search balances the need to thoroughly explore the boundary between feasible and infeasible networks, along with calculating fitness on only the most promising candidate networks. The algorithm results are compared to optimum results found by branch and bound and also to GA results without local search operators on a suite of 79 test problems. This GA strategy of employing bounds, simple heuristic checks and problem specific repair and local search operators can be used on other highly constrained combinatorial applications where numerous fitness calculations are prohibitive.
24475
Designing resilient networks using a hybrid genetic algorithm approach
As high-speed networks have proliferated across the globe, their topologies have become sparser due to the increased capacity of communication media and cost considerations. Reliability has been a traditional goal within network design optimization of sparse networks. This paper proposes a genetic approach that uses network resilience as a design criterion in order to ensure the integrity of network services in the event of component failures. Network resilience measures have been previously overlooked as a network design objective in an optimization framework because of their computational complexity - requiring estimation by simulation. This paper analyzes the effect of noise in the simulation estimator used to evaluate network resilience on the performance of the proposed optimization approach.
39614676
Branch Target Buffer Design and Optimization
A branch target buffer (BTB) can reduce the performance penalty of branches in pipelined processors by predicting the path of the branch and caching information used by the branch. Two major issues in the design of BTBs that achieves maximum performance with a limited number of bits allocated to the BTB implementation are discussed. The first is BTB management. A method for discarding branches from the BTB is examined. This method discards the branch with the smallest expected value for improving performance; it outperforms the least recently used (LRU) strategy by a small margin, at the cost of additional complexity. The second issue is the question of what information to store in the BTB. A BTB entry can consist of one or more of the following: branch tag, prediction information, the branch target address, and instructions at the branch target. Various BTB designs, with one or more of these fields, are evaluated and compared. >
3332151
Blue screen matting
A classical problem of imaging—the matting problem—is separation of a non-rectangular foreground image from a (usually) rectangular background image—for example, in a film frame, extraction of an actor from a background scene to allow substitution of a different background. Of the several attacks on this difficult and persistent problem, we discuss here only the special case of separating a desired foreground image from a background of a constant, or almost constant, backing color. This backing color has often been blue, so the problem, and its solution, have been called blue screen matting. However, other backing colors, such as yellow or (increasingly) green, have also been used, so we often generalize to constant color matting. The mathematics of constant color matting is presented and proven to be unsolvable as generally practiced. This, of course, flies in the face of the fact that the technique is commonly used in film and video, so we demonstrate constraints on the general problem that lead to solutions, or at least significantly prune the search space of solutions. We shall also demonstrate that an algorithmic solution is possible by allowing the foreground object to be shot against two constant backing colors—in fact, against two completely arbitrary backings so long as they differ everywhere.
6758603
Sector cache design and performance
The first commercially available CPU cache memory used a sector design, by which the cache consisted of sectors (address tags) and subsectors (or blocks, with valid bits). It rapidly became clear that superior performance could be obtained with the now familiar set-associative cache design. Because of changes in technology, the time has come to revisit the design of sector caches. Sector caches have the feature that large numbers of bytes can be controlled using relatively small numbers of tag bits, while not having to transfer very large blocks. This suggests the use of sector caches for multi-level cache designs. In such a design, the cache tags can be placed at a high level (e.g., on the processor chip) and the cache data array can be placed at a lower level (e.g., off-chip). We present a thorough analysis of the design and use of uniprocessor sector caches. We start by creating a standard workload and then through simulation derive miss ratios for a wide range of sector cache designs. Those miss ratios are transformed into design target miss ratios, which are intended to be representative of a wide range of workloads. The miss ratios are then used to estimate performance, using typical timings, for a variety of one-level and true-level cache designs.
7048039
Establishing Communication Systems without Explicit Meaning Transmission
This paper investigates the development of experience-based meaning creation and explores the problem of establishing successful communication systems in a population of agents. The aim of the work is to investigate how such systems can develop, without reliance on phenomena not found in actual human language learning, such as the explicit transmission of meaning or the provision of reliable error feedback to guide learning. Agents develop individual, distinct meaning structures, and although they can communicate despite this, communicative success is closely related to the proportion of shared lexicalised meaning, and the communicative systems have a large degree of redundant synonymy.
519042
Evolving a Scalable Multirobot Controller Using an Artificial Neural Tissue Paradigm
We present an "artificial neural tissue" (ANT) architecture as a control system for autonomous multirobot tasks. This architecture combines a typical neural-network structure with a coarse-coding strategy that permits specialized areas to develop in the tissue which in turn allows such emergent capabilities as task decomposition. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to derive controllers for the task in simulation. This process results in the emergence of novel functionality through the task decomposition of mission goals. ANT-based controllers are shown to exhibit self-organization, employ stigmergy and make use of templates (unlabeled environmental cues). These controllers have been tested on a multirobot resource-collection task in which teams of robots with no explicit supervision can successfully avoid obstacles, explore terrain, locate resource material and collect it in a designated area by using a light beacon for reference and interpreting unlabeled perimeter markings. The issues of scalability and antagonism are addressed