A simulated annealing algorithm for energy efficient virtual machine placement

Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

Sampling environmental acoustic recordings to determine species richness : I

Acoustic sensors provide an effective means of monitoring biodiversity at large spatial and temporal scales. They can continuously and passively record large volumes of data over extended periods, however these data must be analysed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced users can produce accurate results, however the time and effort required to process even small volumes of data can make manual analysis prohibitive. Our research examined the use of sampling methods to reduce the cost of analysing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilising five days of manually analysed acoustic sensor data from four sites, we examined a range of sampling rates and methods including random, stratified and biologically informed. Our findings indicate that randomly selecting 120, one-minute samples from the three hours immediately following dawn provided the most effective sampling method. This method detected, on average 62% of total species after 120 one-minute samples were analysed, compared to 34% of total species from traditional point counts. Our results demonstrate that targeted sampling methods can provide an effective means for analysing large volumes of acoustic sensor data efficiently and accurately.

Performance evaluation of onsite wastewater treatment : field sampling and preliminary evaluation of results

Background The onsite treatment of sewage and effluent disposal within the premises is widely prevalent in rural and urban fringe areas due to the general unavailability of reticulated wastewater collection systems. Despite the seemingly low technology of the systems, failure is common and in many cases leading to adverse public health and environmental consequences. Therefore it is important that careful consideration is given to the design and location of onsite sewage treatment systems. It requires an understanding of the factors that influence treatment performance. The use of subsurface effluent absorption systems is the most common form of effluent disposal for onsite sewage treatment and particularly for septic tanks. Additionally in the case of septic tanks, a subsurface disposal system is generally an integral component of the sewage treatment process. Therefore location specific factors will play a key role in this context. The project The primary aims of the research project are: • to relate treatment performance of onsite sewage treatment systems to soil conditions at site; • to identify important areas where there is currently a lack of relevant research knowledge and is in need of further investigation. These tasks were undertaken with the objective of facilitating the development of performance based planning and management strategies for onsite sewage treatment. The primary focus of the research project has been on septic tanks. Therefore by implication the investigation has been confined to subsurface soil absorption systems. The design and treatment processes taking place within the septic tank chamber itself did not form a part of the investigation. In the evaluation to be undertaken, the treatment performance of soil absorption systems will be related to the physico-chemical characteristics of the soil. Five broad categories of soil types have been considered for this purpose. The number of systems investigated was based on the proportionate area of urban development within the Brisbane region located on each soil types. In the initial phase of the investigation, though the majority of the systems evaluated were septic tanks, a small number of aerobic wastewater treatment systems (AWTS) were also included. This was primarily to compare the effluent quality of systems employing different generic treatment processes. It is important to note that the number of different types of systems investigated was relatively small. As such this does not permit a statistical analysis to be undertaken of the results obtained. This is an important issue considering the large number of parameters that can influence treatment performance and their wide variability. The report This report is the second in a series of three reports focussing on the performance evaluation of onsite treatment of sewage. The research project was initiated at the request of the Brisbane City Council. The work undertaken included site investigation and testing of sewage effluent and soil samples taken at distances of 1 and 3 m from the effluent disposal area. The project component discussed in the current report formed the basis for the more detailed investigation undertaken subsequently. The outcomes from the initial studies have been discussed, which enabled the identification of factors to be investigated further. Primarily, this report contains the results of the field monitoring program, the initial analysis undertaken and preliminary conclusions. Field study and outcomes Initially commencing with a list of 252 locations in 17 different suburbs, a total of 22 sites in 21 different locations were monitored. These sites were selected based on predetermined criteria. To obtain house owner agreement to participate in the monitoring study was not an easy task. Six of these sites had to be abandoned subsequently due to various reasons. The remaining sites included eight septic systems with subsurface effluent disposal and treating blackwater or combined black and greywater, two sites treating greywater only and six sites with AWTS. In addition to collecting effluent and soil samples from each site, a detailed field investigation including a series of house owner interviews were also undertaken. Significant observations were made during the field investigations. In addition to site specific observations, the general observations include the following: • Most house owners are unaware of the need for regular maintenance. Sludge removal has not been undertaken in any of the septic tanks monitored. Even in the case of aerated wastewater treatment systems, the regular inspections by the supplier is confined only to the treatment system and does not include the effluent disposal system. This is not a satisfactory situation as the investigations revealed. • In the case of separate greywater systems, only one site had a suitably functioning disposal arrangement. The general practice is to employ a garden hose to siphon the greywater for use in surface irrigation of the garden. • In most sites, the soil profile showed significant lateral percolation of effluent. As such, the flow of effluent to surface water bodies is a distinct possibility. • The need to investigate the subsurface condition to a depth greater than what is required for the standard percolation test was clearly evident. On occasion, seemingly permeable soil was found to have an underlying impermeable soil layer or vice versa. The important outcomes from the testing program include the following: • Though effluent treatment is influenced by the physico-chemical characteristics of the soil, it was not possible to distinguish between the treatment performance of different soil types. This leads to the hypothesis that effluent renovation is significantly influenced by the combination of various physico-chemical parameters rather than single parameters. This would make the processes involved strongly site specific. • Generally the improvement in effluent quality appears to take place only within the initial 1 m of travel and without any appreciable improvement thereafter. This relates only to the degree of improvement obtained and does not imply that this quality is satisfactory. This calls into question the value of adopting setback distances from sensitive water bodies. • Use of AWTS for sewage treatment may provide effluent of higher quality suitable for surface disposal. However on the whole, after a 1-3 m of travel through the subsurface, it was not possible to distinguish any significant differences in quality between those originating from septic tanks and AWTS. • In comparison with effluent quality from a conventional wastewater treatment plant, most systems were found to perform satisfactorily with regards to Total Nitrogen. The success rate was much lower in the case of faecal coliforms. However it is important to note that five of the systems exhibited problems with regards to effluent disposal, resulting in surface flow. This could lead to possible contamination of surface water courses. • The ratio of TDS to EC is about 0.42 whilst the optimum recommended value for use of treated effluent for irrigation should be about 0.64. This would mean a higher salt content in the effluent than what is advisable for use in irrigation. A consequence of this would be the accumulation of salts to a concentration harmful to crops or the landscape unless adequate leaching is present. These relatively high EC values are present even in the case of AWTS where surface irrigation of effluent is being undertaken. However it is important to note that this is not an artefact of the treatment process but rather an indication of the quality of the wastewater generated in the household. This clearly indicates the need for further research to evaluate the suitability of various soil types for the surface irrigation of effluent where the TDS/EC ratio is less than 0.64. • Effluent percolating through the subsurface absorption field may travel in the form of dilute pulses. As such the effluent will move through the soil profile forming fronts of elevated parameter levels. • The downward flow of effluent and leaching of the soil profile is evident in the case of podsolic, lithosol and kransozem soils. Lateral flow of effluent is evident in the case of prairie soils. Gleyed podsolic soils indicate poor drainage and ponding of effluent. In the current phase of the research project, a number of chemical indicators such as EC, pH and chloride concentration were employed as indicators to investigate the extent of effluent flow and to understand how soil renovates effluent. The soil profile, especially texture, structure and moisture regime was examined more in an engineering sense to determine the effect of movement of water into and through the soil. However it is not only the physical characteristics, but the chemical characteristics of the soil also play a key role in the effluent renovation process. Therefore in order to understand the complex processes taking place in a subsurface effluent disposal area, it is important that the identified influential parameters are evaluated using soil chemical concepts. Consequently the primary focus of the next phase of the research project will be to identify linkages between various important parameters. The research thus envisaged will help to develop robust criteria for evaluating the performance of subsurface disposal systems.

An accurate and reliable stereo matching algorithm incorporating the rank constraint

A fundamental problem faced by stereo vision algorithms is that of determining correspondences between two images which comprise a stereo pair. This paper presents work towards the development of a new matching algorithm, based on the rank transform. This algorithm makes use of both area-based and edge-based information, and is therefore referred to as a hybrid algorithm. In addition, this algorithm uses a number of matching constraints,including the novel rank constraint. Results obtained using a number of test pairs show that the matching algorithm is capable of removing a significant proportion of invalid matches. The accuracy of matching in the vicinity of edges is also improved.

A hybrid stereo matching algorithm incorporating the rank constraint

A fundamental problem faced by stereo vision algorithms is that of determining correspondences between two images which comprise a stereo pair. This paper presents work towards the development of a new matching algorithm, based on the rank transform. This algorithm makes use of both area-based and edge-based information, and is therefore referred to as a hybrid algorithm. In addition, this algorithm uses a number of matching constraints, including the novel rank constraint. Results obtained using a number of test pairs show that the matching algorithm is capable of removing most invalid matches. The accuracy of matching in the vicinity of edges is also improved.

Towards Bayesian experimental design for nonlinear models that require a large number of sampling times

The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.

Hybrid game evolutionary algorithm for mission path planning of aerial survey tasks

The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Pareto-optimal solutions.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

Glider path-planning for optimal sampling of mesocale eddies

Ocean gliders constitute an important advance in the highly demanding ocean monitoring scenario. Their effciency, endurance and increasing robustness make these vehicles an ideal observing platform for many long term oceanographic applications. However, they have proved to be also useful in the opportunis-tic short term characterization of dynamic structures. Among these, mesoscale eddies are of particular interest due to the relevance they have in many oceano-graphic processes.

Fourier Lucas-Kanade Algorithm

In this paper we propose a framework for both gradient descent image and object alignment in the Fourier domain. Our method centers upon the classical Lucas & Kanade (LK) algorithm where we represent the source and template/model in the complex 2D Fourier domain rather than in the spatial 2D domain. We refer to our approach as the Fourier LK (FLK) algorithm. The FLK formulation is advantageous when one pre-processes the source image and template/model with a bank of filters (e.g. oriented edges, Gabor, etc.) as: (i) it can handle substantial illumination variations, (ii) the inefficient pre-processing filter bank step can be subsumed within the FLK algorithm as a sparse diagonal weighting matrix, (iii) unlike traditional LK the computational cost is invariant to the number of filters and as a result far more efficient, and (iv) this approach can be extended to the inverse compositional form of the LK algorithm where nearly all steps (including Fourier transform and filter bank pre-processing) can be pre-computed leading to an extremely efficient and robust approach to gradient descent image matching. Further, these computational savings translate to non-rigid object alignment tasks that are considered extensions of the LK algorithm such as those found in Active Appearance Models (AAMs).

Collective sampling and analysis of high order tensors for chatroom communications

This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

Cause of Death, Trend and Disease Burden in Shandong Province, China : the Third Retrospective Sampling Survey of Cause of Death Report

This book describes the mortality for all causes of death and the trend in major causes of death since 1970s in Shandong Province, China.