Distributed computing of all-to-all comparison problems in heterogeneous systems

The requirement of distributed computing of all-to-all comparison (ATAC) problems in heterogeneous systems is increasingly important in various domains. Though Hadoop-based solutions are widely used, they are inefficient for the ATAC pattern, which is fundamentally different from the MapReduce pattern for which Hadoop is designed. They exhibit poor data locality and unbalanced allocation of comparison tasks, particularly in heterogeneous systems. The results in massive data movement at runtime and ineffective utilization of computing resources, affecting the overall computing performance significantly. To address these problems, a scalable and efficient data and task distribution strategy is presented in this paper for processing large-scale ATAC problems in heterogeneous systems. It not only saves storage space but also achieves load balancing and good data locality for all comparison tasks. Experiments of bioinformatics examples show that about 89\% of the ideal performance capacity of the multiple machines have be achieved through using the approach presented in this paper.

Performance evaluation of a distributed concurrency control algorithm

Concurrency control (CC) algorithms are important in distributed database systems to ensure consistency of the database. A number of such algorithms are available in the literature. The issue of performance evaluation of these algorithms has been recognized to be important. However, only a few studies have been carried out towards this. This paper deals with the performance evaluation of a CC algorithm proposed by Rosenkrantz et al. through a detailed simulation study. In doing so, the algorithm has been modified so that it can, within itself, take care of the redundancy in the database. The influences of various system parameters and the transaction profile on the response time and on the degree of conflict are considered. The entire study has been carried out using the programming language SIMULA on a DEC-1090 system.

An account of chronological developments in control of distributed parameter systems

Control systems arising in many engineering fields are often of distributed parameter type, which are modeled by partial differential equations. Decades of research have lead to a great deal of literature on distributed parameter systems scattered in a wide spectrum.Extensions of popular finite-dimensional techniques to infinite-dimensional systems as well as innovative infinite-dimensional specific control design approaches have been proposed. A comprehensive account of all the developments would probably require several volumes and is perhaps a very difficult task. In this paper, however, an attempt has been made to give a brief yet reasonably representative account of many of these developments in a chronological order. To make it accessible to a wide audience, mathematical descriptions have been completely avoided with the assumption that an interested reader can always find the mathematical details in the relevant references.

Performance Study of a Centralized Concurrency Control Algorithm for Distributed Database Systems using SIMULA

The stimulation technique has gained much importance in the performance studies of Concurrency Control (CC) algorithms for distributed database systems. However, details regarding the simulation methodology and implementation are seldom mentioned in the literature. One objective of this paper is to elaborate the simulation methodology using SIMULA. Detailed studies have been carried out on a centralised CC algorithm and its modified version. The results compare well with a previously reported study on these algorithms. Here, additional results concerning the update intensiveness of transactions and the degree of conflict are obtained. The degree of conflict is quantitatively measured and it is seen to be a useful performance index. Regression analysis has been carried out on the results, and an optimisation study using the regression model has been performed to minimise the response time. Such a study may prove useful for the design of distributed database systems.

Improved chemical control of Conyza bonariensis in wheat limits problems in the following fallow

Conyza bonariensis is a major weed infesting zero-tilled cropping systems in subtropical Australia, particularly in wheat and winter fallows. Uncontrolled C.bonariensis survives to become a problem weed in the following crops or fallows. As no herbicide has been registered for C.bonariensis in wheat, the effectiveness of 11 herbicides, currently registered for other broad-leaved weeds in wheat, was evaluated in two pot and two field experiments. As previous research showed that the age of C.bonariensis, and to a lesser extent, the soil moisture at spraying affected herbicide efficacy, these factors also were investigated. The efficacy of the majority of herbicide treatments was reduced when large rosettes (5-15cm diameter) were treated, compared with small rosettes (<5cm diameter). However, for the majority of herbicide treatments, the soil moisture did not affect the herbicide efficacy in the pot experiments. In the field, a delay in herbicide treatment of 2 weeks reduced the herbicide efficacy consistently across herbicide treatments, which was related to weed age but not to soil moisture differences. Across all the experiments, four herbicides controlled C.bonariensis in wheat consistently (83-100%): 2,4-D; aminopyralid + fluroxypyr; picloram + MCPA + metsulfuron; and picloram + high rates of 2,4-D. Thus, this problem weed can be effectively and consistently controlled in wheat, particularly when small rosettes are treated, and therefore C.bonariensis will have a less adverse impact on the following fallow or crop.

Data distribution and task scheduling for distributed computing of all-to-all comparison problems

This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

A Floor Control Server in a Distributed Conference Service

The conferencing systems in IP Multimedia (IM) networks are going through restructuring, accomplished in the near future. One of the changes introduced is the concept of floors and floor control in its current form with matching entity roles. The Binary Floor Control Protocol (BFCP) is a novelty to be exploited in distributed tightly coupled conferencing services. The protocol defines the floor control server (FCS), which implements floor control giving access to shared resources. As the newest tendency is to distribute the conferencing services, the locations of different functionality units play an important role in developing the standards. The floor control server location is not yet single-mindedly fixed in different standardization bodies, and the debate goes on where to place it within the media server, providing the conferencing service. The thesis main objective is to evaluate two distinctive alternatives in respect the Mp interface protocol between the respective nodes, as the interface in relation to floor control is under standardization work at the moment. The thesis gives a straightforward preamble in IMS network, nodes of interest including floor control server and conferencing. Knowledge on several protocols – BFCP, SDP, SIP and H.248 provides an important background for understanding the functionality changes introduced in the Mp interface and therefore introductions on those protocols and how they are connected to the full picture is given. The actual analysis on the impact of the floor control server into the Mp reference point is concluded in relation to the locations, giving basic flows, requirements analysis including a limited implementation proposal on supporting protocol parameters. The overall conclusion of the thesis is that even if both choices are seemingly useful, not one of the locations is clearly the most suitable in the light of this work. The thesis suggests a solution having both possibilities available to be chosen from in separate circumstances, realized with consistent standardization. It is evident, that if the preliminary assumption for the analysis is kept regarding to only one right place for the floor control server, more work is to be done in connected areas to discover the one most appropriate location.

Data-aware task scheduling for all-to-all comparison problems in heterogeneous distributed systems

Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.

Adaptive load control of the central processor in a distributed system with a star topology

The author presents adaptive control techniques for controlling the flow of real-time jobs from the peripheral processors (PPs) to the central processor (CP) of a distributed system with a star topology. He considers two classes of flow control mechanisms: (1) proportional control, where a certain proportion of the load offered to each PP is sent to the CP, and (2) threshold control, where there is a maximum rate at which each PP can send jobs to the CP. The problem is to obtain good algorithms for dynamically adjusting the control level at each PP in order to prevent overload of the CP, when the load offered by the PPs is unknown and varying. The author formulates the problem approximately as a standard system control problem in which the system has unknown parameters that are subject to change. Using well-known techniques (e.g., naive-feedback-controller and stochastic approximation techniques), he derives adaptive controls for the system control problem. He demonstrates the efficacy of these controls in the original problem by using the control algorithms in simulations of a queuing model of the CP and the load controls.

Ordered Ports – a Language Concept for High-level Distributed Programming

A new language concept for high-level distributed programming is proposed. Programs are organised as a collection of concurrently executing processes. Some of these processes, referred to as liaison processes, have a monitor-like structure and contain ports which may be invoked by other processes for the purposes of synchronisation and communication. Synchronisation is achieved by conditional activation of ports and also through port control constructs which may directly specify the execution ordering of ports. These constructs implement a path-expression-like mechanism for synchronisation and are also equipped with options to provide conditional, non-deterministic and priority ordering of ports. The usefulness and expressive power of the proposed concepts are illustrated through solutions of several representative programming problems. Some implementation issues are also considered.

Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems

In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

Reduced Order Suboptimal Control Design for a Class of Nonlinear Distributed Parameter Systems Using POD and /spl thetas/-D Techniques

A new computational tool is presented in this paper for suboptimal control design of a class of nonlinear distributed parameter systems. First proper orthogonal decomposition based problem-oriented basis functions are designed, which are then used in a Galerkin projection to come up with a low-order lumped parameter approximation. Next, a suboptimal controller is designed using the emerging /spl thetas/-D technique for lumped parameter systems. This time domain sub-optimal control solution is then mapped back to the distributed domain using the same basis functions, which essentially leads to a closed form solution for the controller in a state feedback form. Numerical results for a real-life nonlinear temperature control problem indicate that the proposed method holds promise as a good suboptimal control design technique for distributed parameter systems.

Convergence problems in a class of model reference adaptive control systems

A class of model reference adaptive control system which make use of an augmented error signal has been introduced by Monopoli. Convergence problems in this attractive class of systems have been investigated in this paper using concepts from hyperstability theory. It is shown that the condition on the linear part of the system has to be stronger than the one given earlier. A boundedness condition on the input to the linear part of the system has been taken into account in the analysis - this condition appears to have been missed in the previous applications of hyperstability theory. Sufficient conditions for the convergence of the adaptive gain to the desired value are also given.