Optimal flow control allocation policies in communication networkswith multiple message classes

Flow control is considered for M(⩾2) transmitting stations sending packets to a single receiver over a slotted time-multiplexed link. The optimal allocation problem is generalized to the case of nonidentical holding costs at the M transmitters. Qualitative properties of optimal discounted and time-average policies that reduce the computational complexity of the M-dimensional optimal flow control algorithm are derived. For M=2, a simple relationship between optimal allocations for states x and x +e_i (i=1,2) that leads to significant computational savings in the optimal algorithm is established     

Convolution on mesh connected multicomputers

An efficient parallel algorithm is presented for convolution on a mesh-connected computer with wraparound. The algorithm does not require a broadcast feature for data values, as assumed by previously proposed algorithms. As a result, the algorithm is applicable to both SIMD and MIMD meshes. For an N×N image and a M×M template, the previous algorithms take O (M²q) time on an N×N mesh-connected multicomputer (q is the number of bits in each entry of the convolution matrix). The algorithms have complexity O(M²r), where r=max {number of bits in an image entry, number of bits in a template entry}. In addition to not requiring a broadcast capability, these algorithms are faster for binary images     

Clustering on a hypercube multicomputer

Squared error clustering algorithms for single-instruction multiple-data (SIMD) hypercubes are presented. The algorithms are shown to be asymptotically faster than previously known algorithms and require less memory per processing element (PE). For a clustering problem with N patterns, M features per pattern, and K clusters, the algorithms complete in O(k+log NM ) steps on NM processor hypercubes. This is optimal up to a constant factor. These results are extended to the case in which NMK processors are available. Experimental results from a multiple-instruction, multiple-data (MIMD) medium-grain hypercube are also presented     

Comments on `Parallel algorithms for hierarchical clustering andcluster validity'

In the above-titled paper (ibid., vol.12, no.11, p.1088-92, Nov. 1990), parallel implementations of hierarchical clustering algorithms that achieve O(n²) computational time complexity and thereby improve on the baseline of sequential implementations are described. The latter are stated to be O( n³), with the exception of the single-link method. The commenter points out that state-of-the-art hierarchical clustering algorithms have O(n²) time complexity and should be referred to in preference to the O(n³ ) algorithms, which were described in many texts in the 1970s. Some further references in the parallelizing of hierarchic clustering algorithms are provided     

Optimal algorithms on the pipelined hypercube and related networks

Parallel algorithms for several important combinatorial problems such as the all nearest smaller values problem, triangulating a monotone polygon, and line packing are presented. These algorithms achieve linear speedups on the pipelined hypercube, and provably optimal speedups on the shuffle-exchange and the cube-connected-cycles for any number p of processors satisfying 1⩽p⩽n/((log³n)(loglog n)²), where n is the input size. The lower bound results are established under no restriction on how the input is mapped into the local memories of the different processors     

An efficient distributed knot detection algorithm

A distributed knot detection algorithm for general graphs is presented. The knot detection algorithm uses at most O(n log n+m) messages and O(m+n log n) bits of memory to detect all knots' nodes in the network (where n is the number of nodes and m is the number of links). This is compared to O(n²) messages needed in the best algorithm previously published. The knot detection algorithm makes use of efficient cycle detection and clustering techniques. Various applications for the knot detection algorithms are presented. In particular, its importance to deadlock detection in store and forward communication networks and in transaction systems is demonstrated     

Serial and parallel algorithms for the medial axis transform

An O(n²) time serial algorithm is developed for obtaining the medial axis transform (MAT) of an n×n image. An O(log n) time CREW PRAM algorithm and an O(log² n) time SIMD hypercube parallel algorithm for the MAT are also developed. Both of these use O(n²) processors. Two problems associated with the MAT, the area and perimeter reporting problem, are studied. An O(log n) time hypercube algorithm is developed for both of them, where n is the number of squares in the MAT, and the algorithms use O(n²) processors     

Constant time algorithms for the transitive closure and somerelated graph problems on processor arrays with reconfigurable bussystems

The transitive closure problem in O(1) time is solved by a new method that is far different from the conventional solution method. On processor arrays with reconfigurable bus systems, two O (1) time algorithms are proposed for computing the transitive closure of an undirected graph. One is designed on a three-dimensional n×n×n processor array with a reconfigurable bus system, and the other is designed on a two-dimensional n²×n² processor array with a reconfigurable bus system, where n is the number of vertices in the graph. Using the O(1) time transitive closure algorithms, many other graph problems are solved in O(1) time. These problems include recognizing bipartite graphs and finding connected components, articulation points, biconnected components, bridges, and minimum spanning trees in undirected graphs     

Designing efficient parallel algorithms on mech-connected computerswith multiple broadcasting

Semigroup and prefix computations on two-dimensional mesh-connected computers with multiple broadcasting (2-MCCMBs) are studied. Previously, only square 2-MCCMBs with N processing elements were considered for semigroup computations of N data items, and O(N^1/6) time was required. It is found that square machines are not the best form for semigroup computations, and an O(N^1/8)-time algorithm is derived on an N^5/8×N^3/8 rectangular 2-MCCMB. This time complexity can be further reduced to O(N^1/9) if fewer processing elements are used. Parallel algorithms for prefix computations with the same time complexities are derived     

Efficient algorithms for list ranking and for solving graphproblems on the hypercube

A hypercube algorithm to solve the list ranking problem is presented. Let n be the length of the list, and let p be the number of processors of the hypercube. The algorithm described runs in time O(n/p) when n=Ω(p ^1+ε) for any constant ε>0, and in time O(n log n/p+log³ p) otherwise. This clearly attains a linear speedup when n=Ω(p ^1+ε). Efficient balancing and routing schemes had to be used to achieve the linear speedup. The authors use these techniques to obtain efficient hypercube algorithms for many basic graph problems such as tree expression evaluation, connected and biconnected components, ear decomposition, and st-numbering. These problems are also addressed in the restricted model of one-port communication     

Parallel algorithms for hierarchical clustering and clustervalidity

Parallel algorithms on SIMD (single-instruction stream multiple-data stream) machines for hierarchical clustering and cluster validity computation are proposed. The machine model uses a parallel memory system and an alignment network to facilitate parallel access to both pattern matrix and proximity matrix. For a problem with N patterns, the number of memory accesses is reduced from O(N ³) on a sequential machine to O(N²) on an SIMD machine with N PEs     

On time mapping of uniform dependence algorithms into lowerdimensional processor arrays

Most existing methods of mapping algorithms into processor arrays are restricted to the case where n-dimensional algorithms, or algorithms with n nested loops, are mapped into (n-1)-dimensional arrays. However, in practice, it is interesting to map n-dimensional algorithms into (k-1)-dimensional arrays where k<n. A computational conflict occurs if two or more computations of an algorithm are mapped into the same execution time. Based on the Hermite normal form of the mapping matrix, necessary and sufficient conditions are derived to identify mapping without computational conflicts. These conditions are used to find time mappings of n-dimensional algorithms into (k-1)-dimensional arrays, k<n , without computational conflicts. For some applications, the mapping is time-optimal     

Properties and performance of folded hypercubes

A new hypercube-type structure, the folded hypercube (FHC), which is basically a standard hypercube with some extra links established between its nodes, is proposed and analyzed. The hardware overhead is almost 1/n, n being the dimensionality of the hypercube, which is negligible for large n. For this new design, optimal routing algorithms are developed and proven to be remarkably more efficient than those of the conventional n-cube. For one-to-one communication, each node can reach any other node in the network in at most [n/2] hops (each hop corresponds to the traversal of a single link), as opposed to n hops in the standard hypercube. One-to-all communication (broadcasting) can also be performed in only [n/2] steps, yielding a 50% improvement in broadcasting time over that of the standard hypercube. All routing algorithms are simple and easy to implement. Correctness proofs for the algorithms are given. For the proposed architecture, communication parameters such as average distance, message traffic density, and communication time delay are derived. In addition, some fault tolerance capabilities of this architecture are quantified and compared to those of the standard cube. It is shown that this structure offers substantial improvement over existing hypercube-type networks in terms of the above-mentioned network parameters     

Linear systems with state and control constraints: the theory andapplication of maximal output admissible sets

The initial state of an unforced linear system is output admissible with respect to a constraint set Y if the resulting output function satisfies the pointwise-in-time condition y(t)∈Y, t⩾0. The set of all possible such initial conditions is the maximal output admissible set O_∞. The properties of O_∞ and its characterization are investigated. In the discrete-time case, it is generally possible to represent O_∞ or a close approximation of it, by a finite number of functional inequalities. Practical algorithms for generating the functions are described. In the continuous-time case simple representations of the maximal output admissible set are not available, however, it is shown that the discrete-time results may be used to obtain approximate representations     

An efficient algorithm for mutual exclusion using queue migrationin computer networks

A nonsymmetric deadlock-free mutual exclusion algorithm for computer networks is presented. The algorithm requires O(m ) messages to synchronize m modes in a lightly loaded system, and the performance approaches a constant k dependent on m as the workload increases. In a medium to heavily loaded system, it outperforms other proposed algorithms and its performance is independent of network topology     

A frame approach to the H∞ superoptimal solution

A frame approach to the H_∞ superoptimal solution which offers computational improvements over existing algorithms is given. The approach is based on interpreting s numbers as the largest gains between appropriately defined spaces. Some useful bounds on Hankel singular values and s numbers are derived     

Convexity of the largest singular value of eDMe-D: a convexity lemma

A rigorous proof is given for a convexity lemma used by C.C. Chu and J.C. Doyle (1986) to prove the convexity of the largest singular value of e^DMe^-D with respect to D on a commuting convex subset of matrices     

A linear programming approach for the weighted graph matchingproblem

A linear programming (LP) approach is proposed for the weighted graph matching problem. A linear program is obtained by formulating the graph matching problem in L₁ norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a simplex-based algorithm. Then, approximate 0-1 integer solutions are obtained by applying the Hungarian method on the real solutions of the linear program. The complexity of the proposed algorithm is polynomial time, and it is O(n ⁶L) for matching graphs of size n. The developed algorithm is compared to two other algorithms. One is based on an eigendecomposition approach and the other on a symmetric polynomial transform. Experimental results showed that the LP approach is superior in matching graphs than both other methods     

Consensus with dual failure modes

The problem of achieving consensus in a distributed system is discussed. Systems are treated in which either or both of two types of faults may occur: dormant (essentially omission and timing faults) and arbitrary (exhibiting arbitrary behavior, commonly referred to as Byzantine). Previous results showed that are number of dormant faults may be tolerated when there are no arbitrary faults and that, at most, [n-1/3] arbitrary faults may be tolerated when there are no dormant faults (n is the number of processors). A continuum is established between the previous results: an algorithm exists iff n >f_max+2m_max and c >f_max+m_max (where c is the system connectivity), when faults are constrained so that there are at most f_max and at most m_max of these that are arbitrary. An algorithm is given and compared to known algorithms. A method is given to establish virtual links so that the communications graph appears completely connected     

Geometric structure and feedback in singular systems

The output-nulling (A, E, R(B))-invariant subspaces are defined for singular systems, rigorously justifying the name and demonstrating that special cases of these geometric objects are the familiar subspace of admissible conditions and the supremal (A, E, R(B ))-invariant subspace. A novel singular-system-structure algorithm is used to compute them by numerically efficient means. Their importance for describing the possible closed-loop geometric structure in terms of the open-loop geometric structure is shown. An approach to spectrum assignment in singular systems that is based on a generalized Lyapunov equation is introduced. The equation is used to compute feedback gains to place poles and assign various closed-loop invariant subspaces while guaranteeing closed-loop regularity