Applying autonomic computing concepts to parallel computing using intelligent agents

The work reported in this paper is motivated by the fact that there is a need to apply autonomic computing concepts to parallel computing systems. Advancing on prior work based on intelligent cores [36], a swarm-array computing approach, this paper focuses on ‘Intelligent agents’ another swarm-array computing approach in which the task to be executed on a parallel computing core is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and is seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed swarm-array computing approach is validated on a multi-agent simulator.

Towards self-ware via swarm-array computing

The work reported in this paper proposes Swarm-Array computing, a novel technique inspired by swarm robotics, and built on the foundations of autonomic and parallel computing. The approach aims to apply autonomic computing constructs to parallel computing systems and in effect achieve the self-ware objectives that describe self-managing systems. The constitution of swarm-array computing comprising four constituents, namely the computing system, the problem/task, the swarm and the landscape is considered. Approaches that bind these constituents together are proposed. Space applications employing FPGAs are identified as a potential area for applying swarm-array computing for building reliable systems. The feasibility of a proposed approach is validated on the SeSAm multi-agent simulator and landscapes are generated using the MATLAB toolkit.

Achieving intelligent agents and its feasibility in swarm-array computing

The work reported in this paper proposes ‘Intelligent Agents’, a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent approach, a task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and can be seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-* objectives of autonomic computing. The approach is validated on a multi-agent simulator.

Comparison of the computational cost of a Monte Carlo and deterministic algorithm for computing bilinear forms of matrix powers

In this paper we consider bilinear forms of matrix polynomials and show that these polynomials can be used to construct solutions for the problems of solving systems of linear algebraic equations, matrix inversion and finding extremal eigenvalues. An almost Optimal Monte Carlo (MAO) algorithm for computing bilinear forms of matrix polynomials is presented. Results for the computational costs of a balanced algorithm for computing the bilinear form of a matrix power is presented, i.e., an algorithm for which probability and systematic errors are of the same order, and this is compared with the computational cost for a corresponding deterministic method.

A blueprint for affective computing: A sourcebook

A Blueprint for Affective Computing: A sourcebook and manual is the very first attempt to ground affective computing within the disciplines of psychology, affective neuroscience, and philosophy. This book illustrates the contributions of each of these disciplines to the development of the ever-growing field of affective computing. In addition, it demonstrates practical examples of cross-fertilization between disciplines in order to highlight the need for integration of computer science, engineering and the affective sciences.

Influence of birth weight on gene regulators of lipid metabolism and utilization in subcutaneous adipose tissue and skeletal muscle of neonatal pigs.

Epidemiological studies suggest that low-birth weight infants show poor neonatal growth and increased susceptibility to metabolic syndrome, in particular, obesity and diabetes. Adipose tissue development is regulated by many genes, including members of the peroxisome proliferator-activated receptor (PPAR) and the fatty acid-binding protein (FABP) families. The aim of this study was to determine the influence of birth weight on key adipose and skeletal muscle tissue regulating genes. Piglets from 11 litters were ranked according to birth weight and 3 from each litter assigned to small, normal, or large-birth weight groups. Tissue samples were collected on day 7 or 14. Plasma metabolite concentrations and the expression of PPARG2, PPARA, FABP3, and FABP4 genes were determined in subcutaneous adipose tissue and skeletal muscle. Adipocyte number and area were determined histologically. Expression of FABP3 and 4 was significantly reduced in small and large, compared with normal, piglets in adipose tissue on day 7 and in skeletal muscle on day 14. On day 7, PPARA and PPARG2 were significantly reduced in adipose tissue from small and large piglets. Adipose tissue from small piglets contained more adipocytes than normal or large piglets. Birth weight had no effect on adipose tissue and skeletal muscle lipid content. Low-birth weight is associated with tissue-specific and time-dependent effects on lipid-regulating genes as well as morphological changes in adipose tissue. It remains to be seen whether these developmental changes alter an individual's susceptibility to metabolic syndrome.

Associations between dairy consumption and body weight: a review of the evidence and underlying mechanisms

As the incidence of obesity is reaching 'epidemic' proportions, there is currently widespread interest in the impact of dietary components on body-weight and food intake regulation. The majority of data available from both epidemiological and intervention studies provide evidence of a negative but modest association between milk and dairy product consumption and BMI and other measures of adiposity, with indications that higher intakes result in increased weight loss and lean tissue maintenance during energy restriction. The purported physiological and molecular mechanisms underlying the impact of dairy constituents on adiposity are incompletely understood but may include effects on lipolysis, lipogeneis and fatty acid absorption. Furthermore, accumulating evidence indicates an impact of dairy constituents, in particular whey protein derivatives, on appetite regulation and food intake. The present review summarises available data and provides an insight into the likely contribution of dairy foods to strategies aimed at appetite regulation, weight loss or the prevention of weight gain.

Exploring carrier agents in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? The work reported in this paper is motivated towards bridging this gap by proposing a swarm-array computing approach based on ‘Intelligent Agents’ to achieve autonomy for distributed parallel computing systems. In the proposed approach, a task to be executed on parallel computing cores is carried onto a computing core by carrier agents that can seamlessly transfer between processing cores in the event of a predicted failure. The cognitive capabilities of the carrier agents on a parallel processing core serves in achieving the self-ware objectives of autonomic computing, hence applying autonomic computing concepts for the benefit of parallel computing systems. The feasibility of the proposed approach is validated by simulation studies using a multi-agent simulator on an FPGA (Field-Programmable Gate Array) and experimental studies using MPI (Message Passing Interface) on a computer cluster. Preliminary results confirm that applying autonomic computing principles to parallel computing systems is beneficial.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Trans fatty acids and weight gain

Increasing rates of obesity have stimulated research into possible contributing factors, including specific dietary components such as trans fatty acids (TFAs). This review considers the evidence for an association between TFA intake and weight gain. It concludes that there is limited but consistent evidence from epidemiological studies, and from a primate model, that increased TFA consumption may result in a small additional weight gain. Data from a long-term study in a primate model suggest that TFA may have a greater adipogenic effect than cis monounsaturated fatty acids; however, there are currently inadequate mechanistic data to provide a comprehensive and plausible explanation for any such metabolic differences between the types of fatty acids.