Distributed algorithms for barrier coverage using relocatable sensors

We study the barrier coverage problem using relocatable sensor nodes. We assume each sensor can sense an intruder or event inside its sensing range. Sensors are initially located at arbitrary positions on the barrier and can move along the barrier. The goal is to find final positions for sensors so that the entire barrier is covered. In recent years, the problem has been studied extensively in the centralized setting. In this paper, we study a barrier coverage problem in the distributed and discrete setting. We assume that we have n identical sensors located at grid positions on the barrier, and that each sensor repeatedly executes a Look-Compute-Move cycle: based on what it sees in its vicinity, it makes a decision on where to move, and moves to its next position. We make two strong but realistic restrictions on the capabilities of sensors: they have a constant visibility range and can move only a constant distance in every cycle. In this model, we give the first two distributed algorithms that achieve barrier coverage for a line segment barrier when there are enough nodes in the network to cover the entire barrier. Our algorithms are synchronous, and local in the sense that sensors make their decisions independently based only on what they see within their constant visibility range. One of our algorithms is oblivious whereas the other uses two bits of memory at each sensor to store the type of move made in the previous step. We show that our oblivious algorithm terminates within \(\varTheta (n^2)\) steps with the barrier fully covered, while the constant-memory algorithm is shown to take \(\varTheta (n)\) steps to terminate in the worst case. Since any algorithm in which a sensor can only move a constant distance in one step requires \(\varOmega (n)\) steps on some inputs, our second algorithm is asymptotically optimal.     

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.     

Stability of Local On‐Ramp Metering Control Laws

A framework for stability analysis of local on‐ramp metering control strategies based on the cell transmission model is presented. Within this framework, it is possible to formulate Lyapunov and input‐state stability results for on‐ramp metering control strategies in an open section of highway with on‐ramps. Using this analysis, recommendations for the design of on‐ramp metering control laws set points are derived. Two examples on the use of such analysis are presented. One deals with the stability analysis of a local on‐ramp metering control law and the other with the design of a disturbance observer that, used in combination with the local on‐ramp metering control law, provides a more robust response to traffic regulation. Simulation results are included that confirm the possibility of using this framework to test the impact of local on‐ramp metering control strategies.     

Visualization of level-of-detail meshes on the GPU

Extensive research has been carried out in multiresolution models for many decades. The tendency in recent years has been to harness the potential of GPUs to perform the level-of-detail extraction on graphics hardware. The aim of this work is to present a new level-of-detail scheme based on triangles which is both simple and efficient. In this approach, the extraction process updates vertices instead of indices, thus providing a perfect framework for adapting the algorithms to work completely on GPU shaders. One of the key aspects of our proposal is the need for just a single rendering pass in order to obtain the desired geometry. Moreover, coherence among the different approximations is maximized by means of a symmetric extraction algorithm, which performs the same process when refining and coarsening the mesh. Lastly, we also introduce different uses of the scheme to offer continuous and view-dependent resolution.     

DynaMICs: Comprehensive Support for Run-Time Monitoring

Software engineering strives to enable the economic construction of software systems that behave reliably, predictably, and safely. In other engineering disciplines, safety is assured in part by detailed monitoring of processes. In software, we may achieve some level of confidence in the operation of programs by monitoring their execution. DynaMICs is a software tool that facilitates the collection and use of constraints for software systems. In addition, it supports traceability by mapping constraints to system artifacts. Constraint specifications are stored separately from code; constraint-monitoring code is automatically generated from the specifications and inserted into the program at appropriate places; and constraints are verified at execution time. These constraint checks are triggered by changes made to variable values. We describe the architecture of DynaMICs, discuss alternative verification techniques, and outline research directions for the DynaMICs project.     

2‐D/3‐D displays based on switchable lenticulars

Abstract— An attractive concept for 3‐D displays is the one based on LCDs equipped with lenticular lenses. This enables autostereoscopic multiview 3‐D displays without a loss in brightness. A general issue in multiview 3‐D displays is their relatively low spatial resolution because the pixels are divided among the different views. To overcome this problem, we have developed switchable displays, using liquid‐crystal (LC) filled switchable lenticulars. In this way, it is possible to have a high‐brightness 3‐D display capable of fully exploiting the native 2‐D resolution of the underlying LCD. The feasibility of LC‐filled switchable lenticulars was shown in several applications. For applications in which it is advantageous to be able to display 3‐D and 2‐D content simultaneously, a 42‐in. locally switchable prototype having a matrix electrode structure was developed. These displays were realized using cylindrically shaped lenticular lenses in contact with LC. An alternative for these are lenticulars based on gradient‐index (GRIN) LC lenses. Preliminary results for such switchable GRIN lenses are presented as well.     

On spiking neural P systems and partially blind counter machines

A k-output spiking neural P system (SNP) with output neurons, , generates a tuple of positive integers if, starting from the initial configuration, there is a sequence of steps such that during the computation, each O _i generates exactly two spikes aa (the times the pair aa are generated may be different for different output neurons) and the time interval between the first a and the second a is n _i . After the output neurons generate their pairs of spikes, the system eventually halts. We give characterizations of sets definable by partially blind multicounter machines in terms of k-output SNPs operating in a sequential mode. Slight variations of the models make them universal.     

Using OGRO and CertiVeR to improve OCSP validation for Grids

Authentication and authorization in many distributed systems rely on the use of cryptographic credentials that in most of the cases have a defined lifetime. This feature mandates the use of mechanisms able to determine whether a particular credential can be trusted at a given moment. This process is commonly named validation. Among available validation mechanisms, the Online Certificate Status Protocol (OCSP) stands out due to its ability to carry near real time certificate status information. Despite its importance for security, OCSP faces considerable challenges in the computational Grid (i.e. Proxy Certificate’s validation) that are being studied at the Global Grid Forum’s CA Operations Work Group (CAOPS-WG). As members of this group, we have implemented an OCSP validation infrastructure for the Globus Toolkit 4, composed of the CertiVeR Validation Service and our Open GRid Ocsp (OGRO) client library, which introduced the Grid Validation Policy. This paper summarizes our experiences on that work and the results obtained up to now. Furthermore we introduce the prevalidation concept, a mechanism analogous to the Authorization Push-Model, capable of improving OCSP validation performance in Grids. This paper also reports the results obtained with OGRO’s prevalidation rules for Grid Services as a proof of concept.

Distance preserving flattening of surface sections

Curved cross-sections extracted from medical volume images are useful for analyzing nonplanar anatomic structures such as the aorta arch or the pelvis. For visualization and for performing distance measurements, extracted surface sections need to be adequately flattened. We present two different distance preserving surface flattening methods which preserve distances according to a user-specified center of interest and according to user-specified orientations. The first method flattens surface sections by preserving distances along surface curves located within planes having a user specified constant orientation. The second method flattens surfaces along curves located within radial planes crossing the center of interest. We study and compare the properties of the two flattening methods by analyzing their distortion maps. Thanks to a multiresolution approach, we provide surface flattening at interactive rates, allowing users to displace their focus point while visualizing the resulting flattened surface. These distance preserving flattening methods provide new means of inspecting curved cross-sections extracted from medical images.