Optimality of systems of identically distributed competing processes

This paper considers the problem of optimal distribution of computational resources of multiprocessor systems based on the principles of parallelization and conveyorization. The necessary conditions and criteria of efficiency and optimality of systems of identically distributed competing processes are obtained that take into account the overheads required in the context of their run time. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 3–10, November–December 2005.     

Optimal grouping of components in a distributed system

Traditionally the performance of a distributed system or a telecommunications network is taken into account only in the last steps of its design and it is seen as a final improvement. Recent attempts to incorporate performance considerations in the mainstream design rely on the development of a functional model consisting of entities that must be optimally distributed over a network of physical nodes. The optimal allocation is environment sensitive and probable different environments must be taken into account. Functional entities that are likely to be grouped together in different environments compose the so-called network entities. In this paper the problem of optimally composing network entities is examined. Different variations of the problem have been studied.     

Optimal control of distributed bilinear systems

The optimal control problem for a bilinear distributed parameter system subject to a quadratic cost functional is solved. It is shown that the optimal control is given by a convergent power series in the state with tensor coefficients.     

Optimal control of distributed parameter systems

A method for determining the optimum control for distributed parameter systems is presented. The method is based upon mathematical programming and is restricted to systems which can be represented by discrete time models having coefficients which are functions of the spatial variables. The control function is assumed to be spatially concentrated. A closed form Bolutton is given which is valid when no constraints exist. An illustrative example is provided.     

Optimal semijoins for distributed database systems

A Bloom-filter-based semijoin algorithm for distributed database systems is presented. This algorithm reduces communications costs to process a distributed natural join as much as possible with a filter approach. An optimal filter is developed in pieces. Filter information is used both to recognize when the semijoin will cease to be effective and to optimally process the semijoin. An ineffective semijoin will be quickly and cheaply recognized. An effective semijoin will use all of the transmitted bits optimally     

Estimation of the parameter of identically distributed exponential quantities

A sequence of Independent random exponential variables with identical distribution is considered. The conditions of strong consistency for the parameter of the sequence under certain conditions are presented. Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 130–134, November–December, 1999.     

Optimal measurement trajectories for distributed parameter systems

The paper deals with the optimal sensor location problem associated with minimax filtering for linear distributed parameter systems under the moving sensors. The problem of optimal choice of a measurement trajectory is treated here as an H^∞-optimal control one under phase constraints with the objective to minimize a given ‘weak’ performance index under ‘worst’ possible disturbances. Existence of a solution to such a problem is established for the case of quadratic constraints on the disturbances and necessary conditions for optimally are derived on the basis of constructing a sequence of suboptimal solutions associated, in turn, with a sequence of finite-dimensional maximum principles.     

Optimal control of a class of distributed systems

A procedure consisting of two iterative schemes is developed for the optimal control of quasi-static distributed systems. The procedure, which is based on singular perturbation techniques and calculus of variations, is illustrated for a diffusive system.     

Parallel Algorithm Design on Some Distributed Systems

Some testing results on DAWINING-1000,Paragon and workstation cluster are described in this paper.On the home-made parallel system DAWNING-1000 with 32 computational processors,the practical performance of 1.1777 Gflops and 1.58 Gflops has been measured in solving a dense linear system and doing matrix multiplication,respectively .The scalability is also investigated.The importance of designing efficient parallel algorithms for evaluating parallel systems is emphasized.     

Efficient task migration algorithm for distributed systems

The objective of the study was to achieve balanced load among processors, reduce the communication overhead of the load balancing algorithm, and improve respource utilization, which results in better average resonse time. A communication protocol and a fully distributed algorithm for dynamic load balancing through task migration in a connected N-processor network are presented. Each processor communicates its load directly with only a subset (of the size √ N) of processors, reducing communication traffic and average response time. It is proved that the given algorithm will perform task migration even if there is only one light load processor and one heavy load processor in the system. Simulation results show that the proposed scheme can save up to 60% of the protocol messages used by the broadcast algorithms and can reduce the average response time     

分布式系统下的启发式任务调度算法

为了提升异构分布式环境下处理具有依赖关系的任务的性能,提出一种基于关键任务和处理器选择参数的启发式任务调度算法（HCNPSV）。该算法结合表调度和任务复制调度的思想,改进了关键任务的计算方法,并按照是否为关键任务、上行权重值递减、关联任务数递增的顺序获得调度序列,资源选择阶段综合考虑了任务的最早完成时间和到出口节点的最短距离,最后将任务调度到处理器选择参数最小的资源上执行。实验结果表明,HCNPSV有效地提高了系统的调度性能。     

Optimal placement of distributed generation units in distribution systems via an enhanced multi-objective particle swarm optimization algorithm

This paper deals with the optimal placement of distributed generation （DG） units in distribution systems via an enhanced multi-objective particle swarm optimization （EMOPSO） algorithm. To pursue a better simulation of the reality and provide the designer with diverse alternative options, a multi-objective optimization model with technical and operational con- straints is constructed to minimize the total power loss and the voltage fluctuation of the power system simultaneously. To enhance the convergence of MOPSO, special techniques including a dynamic inertia weight and acceleration coefficients have been inte- grated as well as a mutation operator. Besides, to promote the diversity of Pareto-optimal solutions, an improved non-dominated crowding distance sorting technique has been introduced and applied to the selection of particles for the next iteration. After verifying its effectiveness and competitiveness with a set of well-known benchmark functions, the EMOPSO algorithm is em- ployed to achieve the optimal placement of DG units in the IEEE 33-bus system. Simulation results indicate that the EMOPSO algorithm enables the identification of a set of Pareto-optimal solutions with good tradeoff between power loss and voltage sta- bility. Compared with other representative methods, the present results reveal the advantages of optimizing capacities and loca- tions of DG units simultaneously, and exemplify the validity of the EMOPSO algorithm applied for optimally placing DG units.     

Optimal control of distributed hyperbolic systems with deviating arguments

In this paper optimal control problems for hyperbolic systems in which deviating arguments appear in the integral form both in the state equations and in the boundary conditions are considered. Making use of Lion's scheme, necessary and sufficient conditions of optimality for the Neumann problem are derived. A simple example of application is also provided.     

A partitioning algorithm for distributed software systems design

One complication in using distributed computer systems is the increased complexity of developing distributed software systems. These software systems are composed of asynchronously executing components which communicate via message passing. Current software design techniques are not adequate for use in the design of distributed software systems. New design methods which explicitly address the problem of system partitioning are needed. An overall distributed software design approach is presented. The key to the design approach is the presentation of a distributed processing component (DPC) partitioning algorithm for clustering functional modules in order to derive a set of distributed processing components. The design approach is oriented towards producing a software system which is hierarchical, which exploits potential concurrency that exists between functional modules, and which avoids nonprofitable message traffic.     

An efficient partitioning algorithm for distributed virtualenvironment systems

Distributed virtual environment (DVE) systems model and simulate the activities of thousands of entities interacting in a virtual world over a wide area network. Possible applications for DVE systems are multiplayer video games, military and industrial trainings, and collaborative engineering. In general, a DVE system is composed of many servers and each server is responsible to manage multiple clients who want to participate in the virtual world. Each server receives updates from different clients (such as the current position and orientation of each client) and then delivers this information to other clients in the virtual world. The server also needs to perform other tasks, such as object collision detection and synchronization control. A large scale DVE system needs to support many clients and this imposes a heavy requirement on networking resources and computational resources. Therefore, how to meet the growing requirement of bandwidth and computational resources is one of the major challenges in designing a scalable and cost-effective DVE system. In this paper, we propose an efficient partitioning algorithm that addresses the scalability issue of designing a large scale DVE system. The main idea is to dynamically divide the virtual world into different partitions and then efficiently assign these partitions to different servers. This way, each server will process approximately the same amount of workload. Another objective of the partitioning algorithm is to reduce the server-to-server communication overhead. The theoretical foundation of our dynamic partitioning algorithm is based on the linear optimization principle. We also illustrate how one can parallelize the proposed partitioning algorithm so that it can efficiently partition a very large scale DVE system. Lastly, experiments are carried out to illustrate the effectiveness of the proposed partitioning algorithm under various settings of the virtual world     

支持构件迁移的分布式系统容错算法

随着分布式应用技术的发展,构件的静态性限制了分布式系统在运行期间适应其可用资源变化的要求.为了动态适应系统可用资源,提高系统性能,支持构件可迁移的分布式应用研究受到广泛关注.针对提高构件可迁移分布式应用的可靠性,提出一种分布式系统容错算法.在准同步检查点算法的基础上,通过引入shadow-chain和通讯录机制,实现了构件间通信的可靠性和构件重定位的透明性,从而使得系统能够在较低代价下设置检查点,并能将出错后的系统回卷到一致性状态.     

Optimal control of distributed multiagent systems with finite-time group flocking

The flocking of multiple intelligent agents, inspired by the swarm behavior of natural phenomena, has been widely used in the engineering fields such as in unmanned aerial vehicle (UAV) and robots system. However, the performance of the system (such as response time, network throughput, and resource utilization) may be greatly affected while the intelligent agents are engaged in cooperative work. Therefore, it is concerned to accomplish the distributed cooperation while ensuring the optimal performance of the intelligent system. In this paper, we investigated the optimal control problem of distributed multiagent systems (MASs) with finite-time group flocking movement. Specifically, we propose two optimal group flocking algorithms of MASs with single-integrator model and double-integrator model. Then, we study the group consensus of distributed MASs by using modern control theory and finite-time convergence theory, where the proposed optimal control algorithms can drive MASs to achieve the group convergence in finite-time while minimizing the performance index of the intelligence system. Finally, experimental simulation shows that MASs can keep the minimum energy function under the effect of optimal control algorithm, while the intelligent agents can follow the optimal trajectory to achieve group flocking in finite time.     

Optimal cost design of replicated data in distributed database systems

Replicated data are a common strategy for achieving ultra-availability in fault-tolerant distributed database systems. Replication, however, requires additional resources, for example additional costs in terms of maintenance effort, software complexity, hardware requirements and time needed for testing consistency. Various replication control protocols have been developed to ensure data consistency. In this paper, we develop analytical methods for the quorum-consensus replication protocol that minimizes the total system cost by determining the optimal read quorum, the optimal number of system sites, or the optimal site availability assuming that (1) the cost of an individual site is an increasing function of the availability of the site and (2) the two system unavailable modes (i.e. read and write) can have different penalty costs. Several numerical examples and applications are provided to illustrate the results.     

A new dynamic voting algorithm for distributed database systems

We consider the problem of keeping a distributed database system that has been partitioned because of site or communication link failures partially operable while ensuring data consistency. A dynamic-voting-consistency algorithm is proposed, and its correctness is demonstrated. The proposed algorithm results in improved efficiency in executing read requests by not requiring a read quorum. This algorithm is effective in environments where the majority of user requests are “read” types of requests. Furthermore, the proposed algorithm results in efficient recovery by avoiding updating those data objects that are still current. Under the proposed algorithm, the majority partition would be available even if changes in the network topology take place at a higher rate than the update rate, as long as only simple partitioning takes place     

Optimal observation strategies for model-based fault detection in distributed systems

In model oriented diagnostics of real-world systems, the problems of structural identification and parameter estimation are of crucial importance. They require a properly designed schedule of measurements in such a way as to obtain possibly the most informative observational data. The aim of this work is to develop a novel approach to fault detection in distributed systems based on the maximization of the power of parametric hypothesis test, which verifies the nominal state of the considered system. The optimal locations of sensors are determined using the performance index operating on the Fisher Information Matrix. A general scheme is then proposed and tested on a computer example regarding an advection-diffusion problem.