Gaussian interconnection networks have been introduced as a useful alternative to the classical toroidal networks, and in this paper this concept is generalized to higher dimensions. We also explore many important properties of this new topology, including distance distribution and the decomposition of higher dimensional Gaussian networks into edge-disjoint tori and Hamiltonian cycles. In addition, an optimal shortest path routing algorithm and a one-to-all broadcast algorithm for higher dimensional Gaussian networks are given. Simulation results show that the routing algorithm proposed for higher dimensional Gaussian networks outperforms the routing algorithm of the corresponding torus network of the same node-degree and the same number of nodes.

In a multiprocessor system, a limited number of resources need to be uniformly distributed so that all processor nodes can have equal access to these resources. This is referred to as the resource placement problem. In a perfect t--placement each nonresource node is at a distance of t or less from exactly one resource node. Here, we first find all perfect t-placements in the infinite square and triangular grids. That information is then used to show that translates of earlier sets are the only perfect t-placements in Gaussian and EJ interconnection networks.

In this paper, we show that the hexagonal mesh networks developed in the early 1990s are a special case of the EJ networks that have been considered more recently. Using a node addressing scheme based on the EJ number system, we give a shortest path routing algorithm for hexagonal mesh networks. We also extend the known efficient one-to-all broadcasting algorithm on hexagonal mesh networks to algorithms for one-to-one personalized broadcasting, all-to-all broadcasting, and all-to-all personalized broadcasting algorithms. Their time complexity and optimality are analyzed.

Earlier authors have used quotient rings of Gaussian and Eisenstein-Jacobi integers to construct interconnection networks with good topological properties. In this paper, we present a unified study of these two types of networks. Our results include decomposing the edges into disjoint Hamiltonian cycles, a simplification of the calculation of the Eisenstein-Jacobi distance, a distribution of the distances between Eisenstein-Jacobi nodes, and shortest path routing algorithms. In particular, the known Gaussian routing algorithm is simplified.