Recursive circulants and their embeddings among hypercubes

AbstractWe propose an interconnection structure for multicomputer networks, called recursive circulant. Recursive circulant G(N,d) is defined to be a circulant graph with N nodes and jumps of powers of d. G(N,d) is node symmetric, and has some strong hamiltonian properties. G(N,d) has a recursive structure when N=cdm, 1⩽c<d. We develop a shortest-path routing algorithm in G(cdm,d), and analyze various network metrics of G(cdm,d) such as connectivity, diameter, mean internode distance, and visit ratio. G(2m,4), whose degree is m, compares favorably to the hypercube Qm. G(2m,4) has the maximum possible connectivity, and its diameter is ⌈(3m−1)/4⌉. Recursive circulants have interesting relationship with hypercubes in terms of embedding. We present expansion one embeddings among recursive circulants and hypercubes, and analyze the costs associated with each embedding. The earlier version of this paper appeared in Park and Chwa (Proc. Internat. Symp. Parallel Architectures, Algorithms and Networks ISPAN’94, Kanazawa, Japan, December 1994, pp. 73–80)

DeMMon Decentralized Management and Monitoring Framework

The centralized model proposed by the Cloud computing paradigm mismatches the decentralized nature of mobile and IoT applications, given the fact that most of the data production and consumption is performed by end-user devices outside of the Data Center (DC). As the number of these devices grows, and given the need to transport data to and from DCs for computation, application providers incur additional infrastructure costs, and end-users incur delays when performing operations. These reasons have led us into a post-cloud era, where a new computing paradigm arose: Edge Computing. Edge Computing takes into account the broad spectrum of devices residing outside of the DC, closer to the clients, as potential targets for computations, potentially reducing infrastructure costs, improving the quality of service (QoS) for end-users and allowing new interaction paradigms between users and applications. Managing and monitoring the execution of these devices raises new challenges previously unaddressed by Cloud computing, given the scale of these systems and the devices’ (potentially) unreliable data connections and heterogenous computational power. The study of the state-of-the-art has revealed that existing resource monitoring and management solutions require manual configuration and have centralized components, which we believe do not scale for larger-scale systems. In this work, we address these limitations by presenting a novel Decentralized Management and Monitoring (“DeMMon”) system, targeted for edge settings. DeMMon provides primitives to ease the development of tools that manage computational resources that support edge-enabled applications, decomposed in components, through decentralized actions, taking advantage of partial knowledge of the system. Our solution was evaluated to amount to its benefits regarding information dissemination and monitoring capabilities across a set of realistic emulated scenarios of up to 750 nodes with variable failure rates. The results show the validity of our approach and that it can outperform state-of-the-art solutions regarding scalability and reliabilityO modelo centralizado de computação utilizado no paradigma da Computação na Nuvem apresenta limitações no contexto de aplicações no domínio da Internet das Coisas e aplicações móveis. Neste tipo de aplicações, os dados são produzidos e consumidos maioritariamente por dispositivos que se encontram na periferia da rede. Desta forma, transportar estes dados de e para os centros de dados impõe uma carga excessiva nas infraestruturas de rede que ligam os dispositivos aos centros de dados, aumentando a latência de respostas e diminuindo a qualidade de serviço para os utilizadores. Para combater estas limitações, surgiu o paradigma da Computação na Periferia, este paradigma propõe a execução de computações, e potencialmente armazenamento de dados, em dispositivos fora dos centros de dados, mais perto dos clientes, reduzindo custos e criando um novo leque de possibilidades para efetuar computações distribuídas mais próximas dos dispositivos que produzem e consomem os dados. Contudo, gerir e supervisionar a execução desses dispositivos levanta obstáculos não equacionados pela Computação na Nuvem, como a escala destes sistemas, ou a variabilidade na conectividade e na capacidade de computação dos dispositivos que os compõem. O estudo da literatura revela que ferramentas populares para gerir e supervisionar aplicações e dispositivos possuem limitações para a sua escalabilidade, como por exemplo, pontos de falha centralizados, ou requerem a configuração manual de cada dispositivo. Nesta dissertação, propõem-se uma nova solução de monitorização e disseminação de informação descentralizada. Esta solução oferece operações que permitem recolher informação sobre o estado do sistema, de modo a ser utilizada por soluções (também descentralizadas) que gerem aplicações especializadas para executar na periferia da rede. A nossa solução foi avaliada em redes emuladas de várias dimensões com um máximo de 750 nós, no contexto de disseminação e de monitorização de informação. Os nossos resultados mostram que o nosso sistema consegue ser mais robusto ao mesmo tempo que é mais escalável quando comparado com o estado da arte

Reliability and fault tolerance modelling of multiprocessor systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Reliability evaluation by analytic modelling constitute an important issue of designing a reliable multiprocessor system. In this thesis, a model for reliability and fault tolerance analysis of the interconnection network is presented, based on graph theory. Reliability and fault tolerance are considered as deterministic and probabilistic measures of connectivity. Exact techniques for reliability evaluation fail for large multiprocessor systems because of the enormous computational resources required. Therefore, approximation techniques have to be used. Three approaches are proposed, the first by simplifying the symbolic expression of reliability; the other two by applying a hierarchical decomposition to the system. All these methods give results close to those obtained by exact techniques.Consejo Nacional de Ciencia y Tecnologia" (National Council for Science and Technology of Mexico) and "Instituto de Investigaciones Electricas" (Institute for Electrical Research

Parallel Architectures and Parallel Algorithms for Integrated Vision Systems

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems

Properties and algorithms of the hyper-star graph and its related graphs

The hyper-star interconnection network was proposed in 2002 to overcome the drawbacks of the hypercube and its variations concerning the network cost, which is defined by the product of the degree and the diameter. Some properties of the graph such as connectivity, symmetry properties, embedding properties have been studied by other researchers, routing and broadcasting algorithms have also been designed. This thesis studies the hyper-star graph from both the topological and algorithmic point of view. For the topological properties, we try to establish relationships between hyper-star graphs with other known graphs. We also give a formal equation for the surface area of the graph. Another topological property we are interested in is the Hamiltonicity problem of this graph. For the algorithms, we design an all-port broadcasting algorithm and a single-port neighbourhood broadcasting algorithm for the regular form of the hyper-star graphs. These algorithms are both optimal time-wise. Furthermore, we prove that the folded hyper-star, a variation of the hyper-star, to be maixmally fault-tolerant

Properties and algorithms of the (n, k)-star graphs

The (n, k)-star interconnection network was proposed in 1995 as an attractive alternative to the n-star topology in parallel computation. The (n, k )-star has significant advantages over the n-star which itself was proposed as an attractive alternative to the popular hypercube. The major advantage of the (n, k )-star network is its scalability, which makes it more flexible than the n-star as an interconnection network. In this thesis, we will focus on finding graph theoretical properties of the (n, k )-star as well as developing parallel algorithms that run on this network. The basic topological properties of the (n, k )-star are first studied. These are useful since they can be used to develop efficient algorithms on this network. We then study the (n, k )-star network from algorithmic point of view. Specifically, we will investigate both fundamental and application algorithms for basic communication, prefix computation, and sorting, etc. A literature review of the state-of-the-art in relation to the (n, k )-star network as well as some open problems in this area are also provided

Approximate logic circuits: Theory and applications

CMOS technology scaling, the process of shrinking transistor dimensions based on Moore's law, has been the thrust behind increasingly powerful integrated circuits for over half a century. As dimensions are scaled to few tens of nanometers, process and environmental variations can significantly alter transistor characteristics, thus degrading reliability and reducing performance gains in CMOS designs with technology scaling. Although design solutions proposed in recent years to improve reliability of CMOS designs are power-efficient, the performance penalty associated with these solutions further reduces performance gains with technology scaling, and hence these solutions are not well-suited for high-performance designs. This thesis proposes approximate logic circuits as a new logic synthesis paradigm for reliable, high-performance computing systems. Given a specification, an approximate logic circuit is functionally equivalent to the given specification for a "significant" portion of the input space, but has a smaller delay and power as compared to a circuit implementation of the original specification. This contributions of this thesis include (i) a general theory of approximation and efficient algorithms for automated synthesis of approximations for unrestricted random logic circuits, (ii) logic design solutions based on approximate circuits to improve reliability of designs with negligible performance penalty, and (iii) efficient decomposition algorithms based on approxiiii mate circuits to improve performance of designs during logic synthesis. This thesis concludes with other potential applications of approximate circuits and identifies. open problems in logic decomposition and approximate circuit synthesis