Architectural Considerations for a Self-Configuring Routing Scheme for Spontaneous Networks

Decoupling the permanent identifier of a node from the node's topology-dependent address is a promising approach toward completely scalable self-organizing networks. A group of proposals that have adopted such an approach use the same structure to: address nodes, perform routing, and implement location service. In this way, the consistency of the routing protocol relies on the coherent sharing of the addressing space among all nodes in the network. Such proposals use a logical tree-like structure where routes in this space correspond to routes in the physical level. The advantage of tree-like spaces is that it allows for simple address assignment and management. Nevertheless, it has low route selection flexibility, which results in low routing performance and poor resilience to failures. In this paper, we propose to increase the number of paths using incomplete hypercubes. The design of more complex structures, like multi-dimensional Cartesian spaces, improves the resilience and routing performance due to the flexibility in route selection. We present a framework for using hypercubes to implement indirect routing. This framework allows to give a solution adapted to the dynamics of the network, providing a proactive and reactive routing protocols, our major contributions. We show that, contrary to traditional approaches, our proposal supports more dynamic networks and is more robust to node failures

On Graph Theoretical Properties of Extended Double Star Interconnection Network Topology

  The Extended Double star (EDS) parallel interconnection network with a network controller (NC) is a two-level hybrid structure. It is a large-scale network with the Double star as its basic building block. EDS network has degree (n!+n+1) and diameter ⌊

DHT-based functionalities using hypercubes

Decoupling the permanent identifi er of a node from the node's topology-dependent address is a promising approach toward completely scalable self-organizing networks. Existing solutions use a logical tree-like structure that, although allowing for simple address assignment and management, lead to low route selection flexibility. This clearly results in low routing performance and poor resilience to failures. In this paper, we propose to increase the number of candidate paths by using incomplete hypercubes. We will see that this solution can cover a wide range of applications by adapting to the dynamics of the network1st IFIP International Conference on Ad-Hoc NetWorkingRed de Universidades con Carreras en Informática (RedUNCI

Investigation of the robustness of star graph networks

The star interconnection network has been known as an attractive alternative to n-cube for interconnecting a large number of processors. It possesses many nice properties, such as vertex/edge symmetry, recursiveness, sublogarithmic degree and diameter, and maximal fault tolerance, which are all desirable when building an interconnection topology for a parallel and distributed system. Investigation of the robustness of the star network architecture is essential since the star network has the potential of use in critical applications. In this study, three different reliability measures are proposed to investigate the robustness of the star network. First, a constrained two-terminal reliability measure referred to as Distance Reliability (DR) between the source node u and the destination node I with the shortest distance, in an n-dimensional star network, Sn, is introduced to assess the robustness of the star network. A combinatorial analysis on DR especially for u having a single cycle is performed under different failure models (node, link, combined node/link failure). Lower bounds on the special case of the DR: antipode reliability, are derived, compared with n-cube, and shown to be more fault-tolerant than n-cube. The degradation of a container in a Sn having at least one operational optimal path between u and I is also examined to measure the system effectiveness in the presence of failures under different failure models. The values of MTTF to each transition state are calculated and compared with similar size containers in n-cube. Meanwhile, an upper bound under the probability fault model and an approximation under the fixed partitioning approach on the ( n-1)-star reliability are derived, and proved to be similarly accurate and close to the simulations results. Conservative comparisons between similar size star networks and n-cubes show that the star network is more robust than n-cube in terms of ( n-1)-network reliability

Design of gracefully degradable hypercube-connected systems

We address the problem of modifying a hypercube computer by the addition of spare nodes and links to improve its fault tolerance, while maintaining a specified level of performance. The hypercube is modeled by a graph in which nodes represent processors and edges represent communication links. A new graph-based measure of performance degradation is introduced. This characterizes a fault-tolerant hypercube as k-fault-tolerant (k-FT) g-step-degradable (g-SD) if the removal of any k nodes reduces the dimension of the largest fault-free subcube by at most g. We show how to construct k-FT g-SD hypercubes for values of k up to 16 and g = 0, 1, or 2. Many of these designs are shown to be link- or degree-optimal. We also propose a construction method that uses small k-FT g-SD designs as seeds to construct k-FT g-SD designs of larger sizes. This results in fault-tolerant hypercubes in which reconfiguration can be first done locally and then easily extended to the entire system. The small number of added links and nodes is shown to be useful not only in increasing the fault tolerance of the underlying hypercube, but also in reducing the average internode distance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30347/1/0000749.pd

DHT-based functionalities using hypercubes

Decoupling the permanent identifi er of a node from the node's topology-dependent address is a promising approach toward completely scalable self-organizing networks. Existing solutions use a logical tree-like structure that, although allowing for simple address assignment and management, lead to low route selection flexibility. This clearly results in low routing performance and poor resilience to failures. In this paper, we propose to increase the number of candidate paths by using incomplete hypercubes. We will see that this solution can cover a wide range of applications by adapting to the dynamics of the network1st IFIP International Conference on Ad-Hoc NetWorkingRed de Universidades con Carreras en Informática (RedUNCI

Improving Scalability and Usability of Parallel Runtime Environments for High Availability and High Performance Systems

The number of processors embedded in high performance computing platforms is growing daily to solve larger and more complex problems. Hence, parallel runtime environments have to support and adapt to the underlying platforms that require scalability and fault management in more and more dynamic environments. This dissertation aims to analyze, understand and improve the state of the art mechanisms for managing highly dynamic, large scale applications. This dissertation demonstrates that the use of new scalable and fault-tolerant topologies, combined with rerouting techniques, builds parallel runtime environments, which are able to efficiently and reliably deliver sets of information to a large number of processes. Several important graph properties are provided to illustrate the theoretical capability of these topologies in terms of both scalability and fault-tolerance, such as reasonable degree, regular graph, low diameter, symmetric graph, low cost factor, low message traffic density, optimal connectivity, low fault-diameter and strongly resilient. The dissertation builds a communication framework based on these topologies to support parallel runtime environments. Such a framework can handle multiple types of messages, e.g., unicast, multicast, broadcast and all-gather. Additionally, the communication framework has been formally verified to work in both normal and failure circumstances without creating any of the common problems such as broadcast storm, deadlock and non-progress cycle

High Performance Software Reconfiguration in the Context of Distributed Systems and Interconnection Networks.

Designed algorithms that are useful for developing protocols and supporting tools for fault tolerance, dynamic load balancing, and distributing monitoring in loosely coupled multi-processor systems. Four efficient algorithms are developed to learn network topology and reconfigure distributed application programs in execution using the available tools for replication and process migration. The first algorithm provides techniques for transparent software reconfiguration based on process migration in the context of quadtree embeddings in Hypercubes. Our novel approach provides efficient reconfiguration for some classes of faults that may be identified easily. We provide a theoretical characterization to use graph matching, quadratic assignment, and a variety of branch and bound techniques to recover from general faults at run-time and maintain load balance. The second algorithm provides distributed recognition of articulation points, biconnected components, and bridges. Since the removal of an articulation point disconnects the network, knowledge about it may be used for selective replication. We have obtained the most efficient distributed algorithms with linear message complexity for the recognition of these properties. The third algorithm is an optimal linear message complexity distributed solution for recognizing graph planarity which is one of the most celebrated problems in graph theory and algorithm design. Recently, efficient shortest path algorithms are developed for planar graphs whose efficient recognition itself was left open. Our algorithm also leads to designing efficient distributed algorithm to recognize outer-planar graphs with applications in Hamiltonian path, shortest path routing and graph coloring. It is shown that efficient routing of information and distributing the stack needed for for planarity testing permit local computations leading to an efficient distributed algorithm. The fourth algorithm provides software redundancy techniques to provide fault tolerance to program structures. We consider the problem of mapping replicated program structures to provide efficient communication between modules in multiple replicas. We have obtained an optimal mapping of 2-replicated binary trees into hypercubes. For replication numbers greater than two, we provide efficient heuristic simulation results to provide efficient support for both \u27N-version programming\u27 and \u27Recovery block\u27 approaches for software replication