ppxscal/embedding_network huggingface dataset:
Preliminary thoughts on problem-oriented shared memory: a decentralized approach to distributed systems
Authors: David R. Cheriton
Venue: ACM SIGOPS Operating Systems Review (1985)

Much of the work to date on distributed systems has focused on the correct choice of communication paradigm, stressing (for example) message primitives, remote procedure call, problem- oriented protocols and so on. A distributed system service is then implemented as a module executing on particular server machine that is accessed using these communication facilities. In contrast, the shared memory paradigm has been used on multiprocessor and uniprocessor systems. In the shared memory paradigm, the state of a service is stored in shared memory and implemented in a decentralization fashion across multiple processors using this shared memory.This paper describes some preliminary thoughts on applying the shared memory paradigm to distributed systems. For efficiency reasons, shared memory is not provided in its full generality, but only with the semantics required for the applications of interest. This type of application-specific memory is called a problem-oriented shared memory. The use of problem- oriented shared memory is illustrated by describing several applications we are exploring in the V distributed system. We also discuss basic requirements on a communication system to support this approach.
Proof Rules for Fault-Tolerant Distributed Programs
Authors: Mathai Joseph, Abha Moitra, Neelam Soundararajan
Venue:  (1984)

Proving properties of fault tolerant distributed programs is a complex task as such proofs must take into account failures at all possible points in the execution of individual processes. The difficulty in accomplishing this is compounded by the need also to cater for simultaneous failures of two or more processes. In this paper, we consider programs written in a version of Hoare''s CSP and define a set of axioms and inference rules by which proofs can be constructed in three steps: proving the properties of each process when its communicants are prone to failure, establishing the effects of failure of each process, and combining these proofs to determine the fault tolerant properties of the whole program.
Nested Dissection on a M x M x K Grid
Authors: Paul Lanzkron, J D Rose
Venue:  (1991)

\indent In this note we will consider the cost of nested dissection for sparse linear systems arising from $M \times M \times K$ grids. For the purpose of this note we will consider two origins for the grids. One origin is from a single differential equation on a 3D $M \times M \times K$ grid. The second is from $K$ coupled differential equations on a $M \times M$ grid, for example the drift diffusion equations for seimconductor device simulation (where $K$ = 3) [1, 2]. We present analyses for two nested dissection algorithms which we call the {\em Minimum Separator Algorithm} and {\em Supernode Algorithm} respectively.
Geometric Probing and Testing - A Survey
Authors: Kathleen Romanik
Venue:  (1995)

Geometric probing is the area of computational geometry that studies how to identify, verify, or determine some property of an unknown geometric object using a measuring device known as a probe. It has applications in the areas of robotics, automated manufacturing, computer vision, optical character recognition and tomography. Geometric testing is the subarea of geometric probing that studies the verification problem - given a target object from a class of objects, it looks at how to find a set of probes that distinguishes the target object from all other objects in the class. In this paper we survey results in the field of geometric testing.
Adoption of systems development methods and techniques: experiences of Bruneian organizations
Authors: M. Rahim, A. H. Seyal, M. N. A. Rahman, S. V. Abdullah
Venue: Proceedings of the 1996 Information Systems Conference of New Zealand (ISCNZ '96) (1996)

Summary form only given, as follows. A wide spectrum of methods and techniques are currently available to aid the information systems (IS) development process. The benefits offered by these methods and techniques are also widely documented in the IS literature. Despite their publicity, several studies reported slow adoption of IS development methods and techniques within US and European organizations. However, little information is known about how these methods and techniques are being practiced within Bruneian organizations, and how successful they have been. A study was thus initiated that employed a survey approach and gathered the perceptions of Bruneian IS personnel towards a set of popular methods and techniques. Thirty six organizations out of sixty participated in the survey. Two thirds (67%) of the participating organizations reported adoption of at least one method to develop their information systems. Even though it appears satisfactory for a newly established small country like Brunei, the use of individual methods, particularly the well known ones like SSADM, and information engineering method is lower than expected. Another startling finding is the very low usage of structured methods. The use of emerging object oriented design is also limited. Surprisingly a substantial proportion of the organizations was found to use in-house methods. The implications of these findings are discussed. These findings are also compared with those of other studies and several suggestions are offered.
Temporal Logic and Semidirect Products: An Effective Characterization of the Until Hierarchy
Authors: Denis Therien, Thomas Wilke
Venue:  (1996)

We reveal an intimate connection between semidirect products of finite semigroups and substitution of formulas in linear temporal logic. We use this connection to obtain an algebraic characterization of the `until'' hierarchy of linear temporal logic; the k-th level of that hierarchy is comprised of all temporal properties that are expressible by a formula of nesting depth k in the `until'' operator. Applying deep results from finite semigroup theory we are able to prove that each level of the `until'' hierarchy is decidable.
Setup-Trail-Avoidance Routing Algorithm
Authors: Matthew T. Busche, Christopher J. Olszewski
Venue: Proceedings of the 1996 International Conference on Network Protocols (ICNP '96) (1996)

The setup-trail-avoidance routing (STAR) algorithm is a new simple distributed routing algorithm for connection- oriented mesh networks. In this algorithm, signaling messages used to set up a service (or end-to-end connection) contain a list of nodes, called the setup trail, that have participated in routing the service to its destination. A node receiving such a signaling message will then calculate a shortest-path route to the service's destination using a network topology specific to the type of service, after first removing from the topology other nodes in the service's setup trail. STAR adapts to changing network conditions, choosing efficient routes for services (e.g., asynchronous transfer mode [ATM] virtual paths) while at the same time quickly terminating service setup requests that have little or no chance of being successfully completed. Simulated restoration studies show STAR has the best performance characteristics among many distributed restoration algorithms.
Overcoming the Christmas Tree Syndrome
Authors: Eric Gregoire
Venue: Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence (1999)

We propose a new computational approach to logic-based systems that should reason in a fast but logically sound and complete manner about large-scale complex critical devices and systems that can exhibit unexpected faulty behaviors. The approach is original from at least two points of view. First, it makes use of local search techniques while preserving logical deductive completeness. Second, it proves experimentally efficient for very large knowledge bases thanks to new heuristics in the use of local search techniques.
A New Upper Bound on the Reliability Function of the Gaussian Channel
Authors: Ashikhmin A., Barg A., Litsyn S.
Venue:  (1999)

We derive a new upper bound on the exponent of error probability of decoding for the best possible codes in the Gaussian channel. This bound is tighter than the known upper bounds (the sphere-packing and minimum-distance bounds proved in Shannon''s classical 1959 paper and their low-rate improvement by Kabatiansky and Levenshtein). The proof is accomplished by studying asymptotic properties of codes on the Euclidean $n$-dimensional sphere. First we prove that the distance distribution of codes of large size necessarily contains a large component. A general theorem establishing this estimate is proved simultaneously for codes on the Euclidean sphere and in real and complex projective spaces. To derive specific estimates of the distance distribution, we study the asymptotic behavior of Jacobi polynomials $P_k^{\alpha,\beta}$ as $k\to \infty$ and at least one of the upper indices grows linearly in $k$. This group of results provides the exact behavior of the exponent of Jacobi polynomials in the entire orthogonality segment. Since on the average there are many code vectors in the vicinity of the transmitted vector $\bfx$, one can show that the probability of confusing $\bfx$ and one of these vectors cannot be too small. This proves a lower bound on the error probability of decoding and the upper bound announced in the title.
On Some Central Problems in Computational Complexity
Authors: Janos Simon
Venue:  (1975)

In this thesis we examine some of the central problems in the theory of computational complexity, like the trade-offs between time and memory, the power of nondeterminism and parallelism, and the speed gained by adding new operations to random access machines. Our main result is the cahracterization of the power of multiplication in random access acceptors: we show, in Chapter 3, that for such models nondeterministic and deterministic computations are polynomially related and that there is a polynomial relationship between the amount of time required for acceptance by random access machines with multiplication, and the amount of tape required by Turing machines. Thus, the additional power gained by using multiplication is the same as that of memory over time (if any). We derive similar results for some other interesting instruction sets. We also have some results for probabilistic and nondeterministic computations: we define threshold machines and show how probabilistic Turing machines may simulate them, and exhibit a set of complete problems for threshold machines. For nondeterministic computations, we present a hierarchy of the elementary recursive languages obtained by polynomially bounded quantification over objects of higher and higher type, which represent nondeterministic time bounded computations with larger and larger bounds. Finally, we discuss some deterministic computations, and conclude with a look at some open problems.
Modeling Multicomputer Task Allocation as a Vector Packing Problem
Authors: James Beck, Daniel Siewiorek
Venue: Proceedings of the 9th international symposium on System synthesis (1996)

This paper considers the problem of task allocation for embedded, bus-based multicomputers. The problem is shown to be isomorphic to a generalization of vector packing, and heuristic solution techniques are investigated. A total of 256 packing algorithms are considered, using a divide-and-conquer experimentation strategy on a set of sixteen real and synthetic test cases. Performance is compared based on the number of processors, the utilization level of the broadcast bus and run time. This research differs from other approaches in that task allocation is formulated as a multi-dimensional problem, and general purpose solution techniques are developed that can accommodate arbitrary models for the schedulable resources.
A study on the average case error of composite Newton-Cotes quadratures
Authors: Sung Hee Choi, Jung Ho Park, Yoon-Young Park
Venue: The Korean Journal of Computational Applied Mathematics (2003)

We study the integration problem in which one wants to compute the approximation to the definite integral in the average case setting. We choose the composite Newton-Cotes quadratures as our algorithm and the function values at equally spaced sample points on the given interval [0,1] as information. We compute the average case error of composite Newton-Cotes quadratures and show that it is minimal (modulo a multiplicative constant).
A Newton Acceleration of the Weiszfeld Algorithm for Minimizing the Sum of Euclidean Distances
Authors: Yuying Li
Venue:  (1995)

The Weiszfeld algorithm for continuous location problems can be considered as an iteratively reweighted least squares method. It exhibits linear convergence. In this paper, a Newton type algorithm with similar simplicity is proposed to solve a continuous multifacility location problem with Euclidean distance measure. Similar to the Weiszfeld algorithm, at each iteration the main computation can be solving a weighted least squares problem. A Cholesky factorization of a symmetric positive definite band matrix, typically with a relatively small band width (e.g., a band width of two for a Euclidean location problem on a plane) is required. This new algorithm can be regarded as a Newton acceleration to the Weiszfeld algorithm with fast global and local convergence. The simplicity and efficiency of the proposed algorithm makes it particularly suitable for large-scale Euclidean location problems and parallel implementation. Computational experience also suggests that the proposed algorithm performs remarkably well in the presence of degeneracy and near degeneracy. In addition, it is proven to be globally convergent. Although the local convergence analysis is still under investigation, computation results suggest that it is typically superlinearly convergent.
Newton: Constraint Programming over Nonlinear Real Constraints
Authors: Pascal Van Hentenryck, Laurent Michel
Venue:  (1995)

This paper is an introduction to Newton, a constraint programming language over nonlinear real constraints. Newton originates from an effort to reconcile the declarative nature of constraint logic programming languages over intervals with advanced interval techniques developed in numerical analysis, such as the interval Newton method. Its key conceptual idea is to introduce the notion of box-consistency, which approximates arc-consistency, a notion well-known in artificial intelligence. Box-consistency achieves an effective pruning at a reasonable computation cost and generalizes some traditional interval operators. Newton has been applied to numerous applications in science and engineering, including nonlinear equation-solving, unconstrained optimization, and constrained optimization. It is competitive with continuation methods on their equation-solving benchmarks and outperforms the interval-based methods we are aware of on optimization problems.
A FIFO worst case analysis for a hard real-time distributed problem with consistency constraints
Authors: L. George, P. Minet
Venue: Proceedings of the 17th International Conference on Distributed Computing Systems (ICDCS '97) (1997)

A solution for a hard real-time scheduling problem in a distributed system is designed and proved. The constraints of our problem are first to preserve consistency even in presence of concurrency and second to preserve the releases order of tasks, provided that tasks release times differ more than clock precision. That is achieved by a FIFO based scheduling. The feasibility conditions resulting from the worst-case response time analysis of each task set are given. The solution complexity is shown to be pseudo-polynomial.
A Data Structure for Bicategories with Application to Speeding Up an Approximation Algorithm
Authors: Philip N. Klein
Venue:  (1993)

We introduce a data-structure problem on graphs we call the bicategory problem, and a data structure that solves it in $O(\sqrt m \log m)$ time, where m is the number of edges. We show how this data structure can be used in quickly computing approximately minimum-cost networks. The resulting time bound for the approximation algorithm is $O(n \sqrt m \log m)$ where n and m are the number of nodes and edges in the input graph, an improvement over the previously known bound of $O(n^2 \sqrt{\log \log n})$ when the input graph is sparse.
On Multiplayer Non-Cooperative Games of Incomplete Information: Part 1 - Decision Algorithms
Authors: Salman Azhar, Gary Peterson, John Reif
Venue:  (1991)

\indent This paper presents algorithms for deciding the {\em outcome} for various classes of multiplayer games of incomplete information. A companion paper shows that these algorithms are indeed asymptotically optimal by providing matching lower bounds [APR91b]. The classes of games to which our algorithms are applicable include games which were not previously known to be decidable. We apply our algorithms to provide alternative upper bounds, and new time-space trade-offs on complexity of multiperson alternating Turing machines [PR79]. We analyze the algorithms to characterize the space complexity $S(n)$ of multiplayer games in terms of the complexity of deterministic Turing machines. In hierarchical multiplayer games each additional {\em clique} (subset of players with same information) increases the complexity of the outcome problem by a further exponential. We show that an $S (n)$ space bounded {\em k}-player game of incomplete information has a deterministic time upper bound of $k$ + 1 repeated expotentials of $S (n)$. Furthermore, $S (n)$ space bounded {\em k}-player blindfold games have deterministic space upper bound of $k$ repeated exponentials of $S (n)$. This paper proves that this exponential blow-up can occur. We also show that time bounded games do not exhibit such hierarchy. In fact, a $T (n)$ time bounded blindfold multiplayer game, as well as a $T (n)$ time bounded multiplayer game of incomplete information, has a deterministic space bound of $T (n)$.
A Storage Efficient WY Representation for Products of Householder Transformations
Authors: Robert S. Schreiber, Charles Van Loan
Venue:  (1987)

A product $Q = P_{1} \cdots P_{r}$ of m-by-m Householder matrices can be written in the form $Q = I + WY^{T}$ where W and Y are each m-by-r. This is called the WY representation of Q. It is of interest when implementing Householder techniques in high-performance computing environments that ``like'''' matrix-matrix multiplication. In this note we describe a storage efficient way to implement the WY representation. In particular, we show how the matrix Q can be expressed in the form $Q = I + YTY^{T}$ where $Y \epsilon R^{mxr}$ and $T \epsilon R^{rxr}$ with T upper triangular. Usually r >> m and so this ``compact'''' WY representation requires less storage. When compared with the recent block-reflector strategy proposed by Schreiber and Parlett the new technique still has a storage advantage and involves a comparable amount of work.
On Markov Reward Modeling with FSPNs
Authors: Katinka Wolter, Andrea Zisowsky
Venue: Proceedings of the 4th International Computer Performance and Dependability Symposium (2000)

In this paper fluid stochastic Petri nets (FSPNs) will be used for modeling reward in a performability model. Two variations of a known performability model are presented in order to demonstrate the ability of FSPNs in modeling accumulated rate reward as well as accumulated impulse reward. In the first model two fluid places are used, one of which represents the profit (reward) obtained by operating the system and the other one the buffer that is approximated continuously.In the second model only one fluid place is used, representing the costs (negative reward) arising due to repair of system components. The costs increase continuously at deterministic rate while the system is in state of repair (which is a rate reward in the model). Additional costs incur each time the buffer fails (which is an impulse reward in the model). With a numerical solution algorithm the distribution of the reward and its mean are computed.
An Optimization Model for Routing in Low Earth Orbit Satellite Constellations
Authors: A. Ferreira, J. Galtier, P. Mahey, G. Mateus, A. Oliveira, M. Pichereau
Venue: Proceedings of the 2000 International Symposium on Parallel Architectures, Algorithms and Networks (2000)

In the recent years, a large set of satellite constellations has been proposed to addresscommunication services with worldwide coverage and once data is in the sky, a major issue consists of redistributing it on Earth in a proper way.This work addresses. the routing problem in satellite networks. An optimization model is presented. In our model, the communication flow is not divided in several routes, the topology is Considered fixed in each state the satellite goes through and the ISL'S capacities arepredefined.
Using the genetic algorithm to build optimal neural networks for fault-prone module detection
Authors: R. Hochman, T. M. Khoshgoftaar, E. B. Allen, J. P. Hudepohl
Venue: Proceedings of the The Seventh International Symposium on Software Reliability Engineering (1996)

The genetic algorithm is applied to developing optimal or near optimal backpropagation neural networks for fault-prone/not-fault-prone classification of software modules. The algorithm considers each network in a population of neural networks as a potential solution to the optimal classification problem. Variables governing the learning and other parameters and network architecture are represented as substrings (genes) in a machine-level bit string (chromosome). When the population undergoes simulated evolution using genetic operators-selection based on a fitness function, crossover, and mutation-the average performance increases in successive generations. We found that, on the same data, compared with the best manually developed networks, evolved networks produced improved classifications in considerably less time, with no human effort, and with greater confidence in their optimality or near optimality. Strategies for devising a fitness function specific to the problem are explored and discussed.
Refinement and Verification of Concurrent Systems Specified in Object-Z and CSP
Authors: Graeme Smith, John Derrick
Venue: Proceedings of the 1st International Conference on Formal Engineering Methods (1997)

The formal development of large or complex systems can often be facilitated by the use of more than one formal specification language. Such a combination of languages is particularly suited to the specification of concurrent or distributed systems, where both the modelling of processes and state is necessary. This paper presents an approach to refinement and verification of specifications written using a combination of Object-Z and CSP. A common semantic basis for the two languages enables a unified method of refinement to be used, based upon CSP refinement. To enable state-based techniques to be used for the Object-Z components of a specification we develop state-based refinement relations which are sound and complete with respect to CSP refinement. In addition, a verification method for static and dynamic properties is presented. The method allows us to verify properties of the CSP system specification in terms of its component Object-Z classes by using the laws of the CSP operators together with the logic for Object-Z.