Symmetric Interconnection Networks from Cubic Crystal Lattices

Torus networks of moderate degree have been widely used in the supercomputer industry. Tori are superb when used for executing applications that require near-neighbor communications. Nevertheless, they are not so good when dealing with global communications. Hence, typical 3D implementations have evolved to 5D networks, among other reasons, to reduce network distances. Most of these big systems are mixed-radix tori which are not the best option for minimizing distances and efficiently using network resources. This paper is focused on improving the topological properties of these networks. By using integral matrices to deal with Cayley graphs over Abelian groups, we have been able to propose and analyze a family of high-dimensional grid-based interconnection networks. As they are built over $n$-dimensional grids that induce a regular tiling of the space, these topologies have been denoted \textsl{lattice graphs}. We will focus on cubic crystal lattices for modeling symmetric 3D networks. Other higher dimensional networks can be composed over these graphs, as illustrated in this research. Easy network partitioning can also take advantage of this network composition operation. Minimal routing algorithms are also provided for these new topologies. Finally, some practical issues such as implementability and preliminary performance evaluations have been addressed

A class of hierarchical graphs as topologies for interconnection networks

We study some topological and algorithmic properties of a recently defined hierarchical interconnection network, the hierarchical crossed cube HCC(k,n), which draws upon constructions used within the well-known hypercube and also the crossed cube. In particular, we study: the construction of shortest paths between arbitrary vertices in HCC(k,n); the connectivity of HCC(k,n); and one-to-all broadcasts in parallel machines whose underlying topology is HCC(k,n) (with both one-port and multi-port store-and-forward models of communication). Moreover, (some of) our proofs are applicable not just to hierarchical crossed cubes but to hierarchical interconnection networks formed by replacing crossed cubes with other families of interconnection networks. As such, we provide a generic construction with accompanying generic results relating to some topological and algorithmic properties of a wide range of hierarchical interconnection networks

Multiswapped networks and their topological and algorithmic properties

We generalise the biswapped network Bsw(G)Bsw(G) to obtain a multiswapped network Msw(H;G)Msw(H;G), built around two graphs G and H. We show that the network Msw(H;G)Msw(H;G) lends itself to optoelectronic implementation and examine its topological and algorithmic. We derive the length of a shortest path joining any two vertices in Msw(H;G)Msw(H;G) and consequently a formula for the diameter. We show that if G has connectivity κ⩾1κ⩾1 and H has connectivity λ⩾1λ⩾1 where λ⩽κλ⩽κ then Msw(H;G)Msw(H;G) has connectivity at least κ+λκ+λ, and we derive upper bounds on the (κ+λ)(κ+λ)-diameter of Msw(H;G)Msw(H;G). Our analysis yields distributed routing algorithms for a distributed-memory multiprocessor whose underlying topology is Msw(H;G)Msw(H;G). We also prove that if G and H are Cayley graphs then Msw(H;G)Msw(H;G) need not be a Cayley graph, but when H is a bipartite Cayley graph then Msw(H;G)Msw(H;G) is necessarily a Cayley graph

A reliable and resource aware framework for data dissemination in wireless sensor networks

Distinctive from traditional wireless ad hoc networks, wireless sensor networks (WSN) comprise a large number of low-cost miniaturized nodes each acting autonomously and equipped with short-range wireless communication mechanism, limited memory, processing power, and a physical sensing capability. Since sensor networks are resource constrained in terms of power, bandwidth and computational capability, an optimal system design radically changes the performance of the sensor network. Here, a comprehensive information dissemination scheme for wireless sensor networks is performed. Two main research issues are considered: (1) a collaborative flow of information packet/s from the source to sink and (2) energy efficiency of the sensor nodes and the entire system. For the first issue, we designed and evaluated a reactive and on-demand routing paradigm for distributed sensing applications. We name this scheme as IDLF-Information Dissemination via Label ForwarDing IDLF incorporates point to point data transmission where the source initiates the routing scheme and disseminates the information toward the sink (destination) node. Prior to transmission of actual data packet/s, a data tunnel is formed followed by the source node issuing small label information to its neighbors locally. These labels are in turn disseminated in the network. By using small size labels, IDLF avoids generation of unnecessary network traffic and transmission of duplicate packets to nodes. To study the impact of node failures and to improve the reliability of the network, we developed another scheme which is an extension to IDLF. This new scheme, RM-IDLF - Reliable Multipath Information dissemination by Label Forwarding, employ an alternate disjoint path. This alternate path scheme (RM-IDLF) may have a higher path cost in terms of energy consumption, but is more reliable in terms of data packet delivery to sink than the single path scheme (IDLF). In the latter scheme, the protocol establishes multiple (alternate) disjoint path/s from source to destination with negligible control overhead to balance load due to heavy data traffic among intermediate nodes from source to the destination. Another point of interest in this framework is the study of trade-offs between the achieved routing reliability using multiple disjoint path routing and extra energy consumption due to the use of additional path/s. Also, the effect of the failed nodes on the network performance is evaluated within the sensor system; Performance of the label dissemination scheme is evaluated and compared with the classic flooding and SPIN. (Abstract shortened by UMI.)

Joint optimization for wireless sensor networks in critical infrastructures

Energy optimization represents one of the main goals in wireless sensor network design where a typical sensor node has usually operated by making use of the battery with limited-capacity. In this thesis, the following main problems are addressed: first, the joint optimization of the energy consumption and the delay for conventional wireless sensor networks is presented. Second, the joint optimization of the information quality and energy consumption of the wireless sensor networks based structural health monitoring is outlined. Finally, the multi-objectives optimization of the former problem under several constraints is shown. In the first main problem, the following points are presented: we introduce a joint multi-objective optimization formulation for both energy and delay for most sensor nodes in various applications. Then, we present the Karush-Kuhn-Tucker analysis to demonstrate the optimal solution for each formulation. We introduce a method of determining the knee on the Pareto front curve, which meets the network designer interest for focusing on more practical solutions. The sensor node placement optimization has a significant role in wireless sensor networks, especially in structural health monitoring. In the second main problem of this work, the existing work optimizes the node placement and routing separately (by performing routing after carrying out the node placement). However, this approach does not guarantee the optimality of the overall solution. A joint optimization of sensor placement, routing, and flow assignment is introduced and is solved using mixed-integer programming modelling. In the third main problem of this study, we revisit the placement problem in wireless sensor networks of structural health monitoring by using multi-objective optimization. Furthermore, we take into consideration more constraints that were not taken into account before. This includes the maximum capacity per link and the node-disjoint routing. Since maximum capacity constraint is essential to study the data delivery over limited-capacity wireless links, node-disjoint routing is necessary to achieve load balancing and longer wireless sensor networks lifetime. We list the results of the previous problems, and then we evaluate the corresponding results

PReaCH: A Fast Lightweight Reachability Index using Pruning and Contraction Hierarchies

We develop the data structure PReaCH (for Pruned Reachability Contraction Hierarchies) which supports reachability queries in a directed graph, i.e., it supports queries that ask whether two nodes in the graph are connected by a directed path. PReaCH adapts the contraction hierarchy speedup techniques for shortest path queries to the reachability setting. The resulting approach is surprisingly simple and guarantees linear space and near linear preprocessing time. Orthogonally to that, we improve existing pruning techniques for the search by gathering more information from a single DFS-traversal of the graph. PReaCH-indices significantly outperform previous data structures with comparable preprocessing cost. Methods with faster queries need significantly more preprocessing time in particular for the most difficult instances