To lock, or not to lock: That is the question

Mechanisms to control concurrent access over project artefacts are needed to execute the software development process in an organized way. These mechanisms are implemented by concurrency control policies in version control systems that may inhibit (i.e. ‘to lock’) or allow (i.e., ‘not to lock’) parallel development. This work presents a novel approach named Orion that analyzes the project's historical changes and suggests the most appropriate concurrency control policy for each software element. This suggestion aims at minimizing conflict situations and thus improving the productivity of the development team. In addition, it identifies critical elements that do not work well with any of these policies and are candidates to refactoring. We evaluated Orion through two experimental studies and the results, which indicated it was effective, led us to a prototype implementation. Apart from the Orion approach this paper also presents the planning, execution, and analysis stages of the evaluation, and details of prototype internals.     

Reducing congestion in bulk-service finite-buffer queueing system using batch-size-dependent service

In the design and analysis of any queueing system, one of the main objectives is to reduce congestion which can be achieved by controlling either arrival-rates or service-rates. This paper adopts the latter approach and analyzes a single-server finite-buffer queue where customers arrive according to the Poisson process and are served in batches of minimum size a with a maximum threshold limit b. The service times of the batches are arbitrarily distributed and depends on the size of the batches undergoing service. We obtain the joint distribution of the number of customers in the queue and the number with the server, and distributions of the number of customers in the queue, in the system, and the number with the server. Various performance measures such as the average number of customers in the queue (system) and with the server etc. are obtained. Several numerical results are presented in the form of tables and graphs and it is observed that batch-size-dependent service rule is more effective in reducing the congestion as compared to the one when service rates of the batches remain same irrespective of the size of the batch. This model has potential application in manufacturing, computer-communication network, telecommunication systems and group testing.     

Cost-benefit analysis of an SLA mapping approach for defining standardized Cloud computing goods

Due to the large variety in computing resources and, consequently, the large number of different types of service level agreements (SLAs), computing resource markets face the problem of a low market liquidity. Restricting the number of different resource types to a small set of standardized computing resources seems to be the appropriate solution to counteract this problem. Standardized computing resources are defined through an SLA template. An SLA template defines the structure of an SLA, the service attributes, the names of the service attributes, and the service attribute values. However, since existing research results have only introduced static SLA templates so far, the SLA templates cannot reflect changes in user needs and market structures. To address this shortcoming, we present a novel approach of adaptive SLA matching. This approach adapts SLA templates based on SLA mappings of users. It allows Cloud users to define mappings between a public SLA template, which is available in the Cloud market, and their private SLA templates, which are used for various in-house business processes of the Cloud user. Besides showing how public SLA templates are adapted to the demand of Cloud users, we also analyze the costs and benefits of this approach. Costs are incurred every time a user has to define a new SLA mapping to a public SLA template due to its adaptation. In particular, we investigate how the costs differ with respect to the public SLA template adaptation method. The simulation results show that the use of heuristics within adaptation methods allows balancing the costs and benefits of the SLA mapping approach.     

Cyberphysical systems security applied to telesurgical robotics

Researchers in telesurgical robotics and security collaborated to develop the Secure ITP, a security enhancement to the Interoperable Telesurgery Protocol (ITP). The ITP defines the structure for communication between telesurgery robots and controllers and has been adopted and tested by fourteen research groups in telesurgical robotics. The Secure ITP uses open source software tools and follows guidelines in Federal Information Processing Standards (FIPS) documents published by the National Institute of Standards and Technology (NIST) to create asecurity enhancement prototype for demonstration purposes and tofacilitate the development of new security technologies which addressthe stringent requirements of telesurgery.     

Study of the influence of nickel ions substitutes in barium stannates used as humidity resistive sensors

In the present work, we report the results of the influence of the Ni ions which partly substitute the Ba ions in the barium stannate (Ba_1−xNi_xSnO₃, where x = 0; 0.1; 0.2; 0.5), on the structural and electronic properties, as well as on the sensitivity to humidity. With the view to obtain a porous and finer structure, thus providing a high specific surface, these materials were obtained through the precursor method of self-combustion (co-precipitation in a colloidal environment and self-combustion), followed by heat treatments. The phase composition and morphology were studied by XRD and SEM. The pure sample, as well as that with the substitution x = 0.1, are single phased after 40 min sintering at 1000 °C. For substitutions with x > 0.1 secondary phases appear, which favorably influence the humidity sensitivity. All the samples show a significant sensitivity to humidity within 22% RH and 75% RH for the substitution with x = 0 and 0.1, and 22% RH - 98% RH for the substitution with x = 0.5. For this interval, the material resistivity logarithmically decreases by over four orders. The sample with the substitution x = 0.5 is characterized by a very fine structure (∼250 nm) and a high effective porosity (47%). This sample presents a shorter absorption response time than the other samples. Its high sensitivity, its sensitivity range, linearity of the sensitivity characteristic and the quick response time recommend the material with the composition Ba_0.5Ni_0.5SnO₃ for the realization of a very good resistive humidity sensor.     

Sensitivity optimization of surface plasmon sensors for detection of intermediate layers

A sensitivity optimization method for the detection of an intermediate layer using a surface plasmon sensor is presented. The dependence of detection sensitivity on distance from the metal surface and the average refractive index over the sensing region are considered. Based on the calculated results, the sensitivity for detecting an intermediate layer in a multilayered sample is determined by varying the refractive index and thickness of each layer. It is shown that, in particular cases, controlling the refractive index and thickness increases the detection sensitivity. The proposed method is useful for designing multilayered samples.     

Polynomial based scheme (PBS) for establishing Authentic Associations in Wireless Mesh Networks

The varying degree of mobility of Mesh Clients has provided much more flexibility in Wireless Mesh Networks, and establishing an Authentic Association among entities is a non-trivial problem. In this paper, we introduce a Polynomial Based scheme which provides pair-wise connectivity, low communication, marginal storage overhead and high scalability while making on the fly Authentic Association feasible. The proposed scheme is also observed to be resilient against both traffic analysis and node capture attacks.     

Modeling discrete event scalable network systems

Scalability in simulation tools is one of the most important traits to measure performance of software. The reason is that today’s Internet is the main instance of a large-scale and highly complex system. Simulation of Internet-scale network systems has to be supported by any simulation tool. Despite this fact, many network simulators lacks support for building large models. In this work, in order to propose a new approach for scalability issue in network simulation tools, a network simulator is developed based on behavior of honeybees and high performance DEVS, modular and hierarchical system theoretic approach. A biologically-inspired discrete event modeling approach is described for studying networks’ scalability and performance traits. Since natural systems can offer important concepts for modeling network systems, key adaptive and emergent attributes of honeybees and their societal properties are incorporated into a set of simulation models that are developed using the discrete event system specification approach. Large-scale network models are simulated and evaluated to show the benefits of nature-inspired network models.     

Supervised principal component analysis: Visualization, classification and regression on subspaces and submanifolds

We propose “supervised principal component analysis (supervised PCA)”, a generalization of PCA that is uniquely effective for regression and classification problems with high-dimensional input data. It works by estimating a sequence of principal components that have maximal dependence on the response variable. The proposed supervised PCA is solvable in closed-form, and has a dual formulation that significantly reduces the computational complexity of problems in which the number of predictors greatly exceeds the number of observations (such as DNA microarray experiments). Furthermore, we show how the algorithm can be kernelized, which makes it applicable to non-linear dimensionality reduction tasks. Experimental results on various visualization, classification and regression problems show significant improvement over other supervised approaches both in accuracy and computational efficiency.     

From classifiers to discriminators: A nearest neighbor rule induced discriminant analysis

The current discriminant analysis method design is generally independent of classifiers, thus the connection between discriminant analysis methods and classifiers is loose. This paper provides a way to design discriminant analysis methods that are bound with classifiers. We begin with a local mean based nearest neighbor (LM-NN) classifier and use its decision rule to supervise the design of a discriminator. Therefore, the derived discriminator, called local mean based nearest neighbor discriminant analysis (LM-NNDA), matches the LM-NN classifier optimally in theory. In contrast to that LM-NNDA is a NN classifier induced discriminant analysis method, we further show that the classical Fisher linear discriminant analysis (FLDA) is a minimum distance classifier (i.e. nearest Class-mean classifier) induced discriminant analysis method. The proposed LM-NNDA method is evaluated using the CENPARMI handwritten numeral database, the NUST603 handwritten Chinese character database, the ETH80 object category database and the FERET face image database. The experimental results demonstrate the performance advantage of LM-NNDA over other feature extraction methods with respect to the LM-NN (or NN) classifier.