Towards an Iterative Algorithm for the Optimal Boundary Coverage of a 3D Environment

This paper presents a new optimal algorithm for locating a set of sensors in 3D able to see the boundaries of a polyhedral environment. Our approach is iterative and is based on a lower bound on the sensors' number and on a restriction of the original problem requiring each face to be observed in its entirety by at least one sensor. The lower bound allows evaluating the quality of the solution obtained at each step, and halting the algorithm if the solution is satisfactory. The algorithm asymptotically converges to the optimal solution of the unrestricted problem if the faces are subdivided into smaller part

Minimum Cost Design of Cellular Networks in Rural Areas with UAVs, Optical Rings, Solar Panels and Batteries

Bringing the cellular connectivity in rural zones is a big challenge, due to the large installation costs that are incurred when a legacy cellular network based on fixed Base Stations (BSs) is deployed. To tackle this aspect, we consider an alternative architecture composed of UAV-based BSs to provide cellular coverage, ground sites to connect the UAVs with the rest of the network, Solar Panels (SPs) and batteries to recharge the UAVs and to power the ground sites, and a ring of optical fiber links to connect the installed sites. We then target the minimization of the installation costs for the considered UAV-based cellular architecture, by taking into account the constraints of UAVs coverage, SPs energy consumption, levels of the batteries and the deployment of the optical ring. After providing the problem formulation, we derive an innovative methodology to ensure that a single ring of installed optical fibers is deployed. Moreover, we propose a new algorithm, called DIARIZE, to practically tackle the problem. Our results, obtained over a set of representative rural scenarios, show that DIARIZE performs very close to the optimal solution, and in general outperforms a reference design based on fixed BSs

Fractionated solar power satellite for regional coverage

This paper presents a preliminary analysis of a fractionated solar power satellite system for regional coverage. The fractionated system is composed of a cluster of satellites, in different possible configurations, that concurrently beam energy to the ground through medium power lasers. The paper presents an analysis of the possible orbit solutions that can be adopted to provide power during the night time to local users in different regions of the world. The system is intended to serve mobile stations or local stations that can be hardly accessed by normal power lines or are cut off during disasters. A preliminary system analysis shows that with a limited number of small size satellite local users can be provided with a few kWh of energy every day

Search algorithms for regression test case prioritization

Regression testing is an expensive, but important, process. Unfortunately, there may be insufficient resources to allow for the re-execution of all test cases during regression testing. In this situation, test case prioritisation techniques aim to improve the effectiveness of regression testing, by ordering the test cases so that the most beneficial are executed first. Previous work on regression test case prioritisation has focused on Greedy Algorithms. However, it is known that these algorithms may produce sub-optimal results, because they may construct results that denote only local minima within the search space. By contrast, meta-heuristic and evolutionary search algorithms aim to avoid such problems. This paper presents results from an empirical study of the application of several greedy, meta-heuristic and evolutionary search algorithms to six programs, ranging from 374 to 11,148 lines of code for 3 choices of fitness metric. The paper addresses the problems of choice of fitness metric, characterisation of landscape modality and determination of the most suitable search technique to apply. The empirical results replicate previous results concerning Greedy Algorithms. They shed light on the nature of the regression testing search space, indicating that it is multi-modal. The results also show that Genetic Algorithms perform well, although Greedy approaches are surprisingly effective, given the multi-modal nature of the landscape

Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics

The accurate and efficient solution of Maxwell's equation is the problem addressed by the scientific discipline called Computational ElectroMagnetics (CEM). Many macroscopic phenomena in a great number of fields are governed by this set of differential equations: electronic, geophysics, medical and biomedical technologies, virtual EM prototyping, besides the traditional antenna and propagation applications. Therefore, many efforts are focussed on the development of new and more efficient approach to solve Maxwell's equation. The interest in CEM applications is growing on. Several problems, hard to figure out few years ago, can now be easily addressed thanks to the reliability and flexibility of new technologies, together with the increased computational power. This technology evolution opens the possibility to address large and complex tasks. Many of these applications aim to simulate the electromagnetic behavior, for example in terms of input impedance and radiation pattern in antenna problems, or Radar Cross Section for scattering applications. Instead, problems, which solution requires high accuracy, need to implement full wave analysis techniques, e.g., virtual prototyping context, where the objective is to obtain reliable simulations in order to minimize measurement number, and as consequence their cost. Besides, other tasks require the analysis of complete structures (that include an high number of details) by directly simulating a CAD Model. This approach allows to relieve researcher of the burden of removing useless details, while maintaining the original complexity and taking into account all details. Unfortunately, this reduction implies: (a) high computational effort, due to the increased number of degrees of freedom, and (b) worsening of spectral properties of the linear system during complex analysis. The above considerations underline the needs to identify appropriate information technologies that ease solution achievement and fasten required elaborations. The authors analysis and expertise infer that Grid Computing techniques can be very useful to these purposes. Grids appear mainly in high performance computing environments. In this context, hundreds of off-the-shelf nodes are linked together and work in parallel to solve problems, that, previously, could be addressed sequentially or by using supercomputers. Grid Computing is a technique developed to elaborate enormous amounts of data and enables large-scale resource sharing to solve problem by exploiting distributed scenarios. The main advantage of Grid is due to parallel computing, indeed if a problem can be split in smaller tasks, that can be executed independently, its solution calculation fasten up considerably. To exploit this advantage, it is necessary to identify a technique able to split original electromagnetic task into a set of smaller subproblems. The Domain Decomposition (DD) technique, based on the block generation algorithm introduced in Matekovits et al. (2007) and Francavilla et al. (2011), perfectly addresses our requirements (see Section 3.4 for details). In this chapter, a Grid Computing infrastructure is presented. This architecture allows parallel block execution by distributing tasks to nodes that belong to the Grid. The set of nodes is composed by physical machines and virtualized ones. This feature enables great flexibility and increase available computational power. Furthermore, the presence of virtual nodes allows a full and efficient Grid usage, indeed the presented architecture can be used by different users that run different applications

Planning UAV Activities for Efficient User Coverage in Disaster Areas

Climate changes brought about by global warming as well as man-made environmental changes are often the cause of sever natural disasters. ICT, which is itself responsible for global warming due to its high carbon footprint, can play a role in alleviating the consequences of such hazards by providing reliable, resilient means of communication during a disaster crisis. In this paper, we explore the provision of wireless coverage through UAVs (Unmanned Aerial Vehicles) to complement, or replace, the traditional communication infrastructure. The use of UAVs is indeed crucial in emergency scenarios, as they allow for the quick and easy deployment of micro and pico cellular base stations where needed. We characterize the movements of UAVs and define an optimization problem to determine the best UAV coverage that maximizes the user throughput, while maintaining fairness across the different parts of the geographical area that has been affected by the disaster. To evaluate our strategy, we simulate a flooding in San Francisco and the car traffic resulting from people seeking safety on higher ground

Feasibility, Architecture and Cost Considerations of Using TVWS for Rural Internet Access in 5G

The cellular technology is mostly an urban technology that has been unable to serve rural areas well. This is because the traditional cellular models are not economical for areas with low user density and lesser revenues. In 5G cellular networks, the coverage dilemma is likely to remain the same, thus widening the rural-urban digital divide further. It is about time to identify the root cause that has hindered the rural technology growth and analyse the possible options in 5G architecture to address this issue. We advocate that it can only be accomplished in two phases by sequentially addressing economic viability followed by performance progression. We deliberate how various works in literature focus on the later stage of this ‘two-phase’ problem and are not feasible to implement in the first place. We propose the concept of TV band white space (TVWS) dovetailed with 5G infrastructure for rural coverage and show that it can yield cost-effectiveness from a service provider’s perspective

Telling Stories That Explain: Comparing Media and Organizational Discourse on Adolescent Substance Use

What's missing from the public conversation on adolescent substance use? For one thing, it's lacking crucial information about what makes adolescence a sensitive period for brain development. That's the conclusion of "Telling Stories that Explain," a new study from the FrameWorks Institute. Researchers analyzed the communications content in media coverage and nonprofit materials, and found that the narratives the public encounters don't tell the whole story

Compressed sensing of monostatic and multistatic SAR

In this paper we study the impact of sparse aperture data collection of a SAR sensor on reconstruction quality of a scene of interest. Different mono and multi-static SAR measurement configurations produce different Fourier sampling patterns. These patterns reflect different spectral and spatial diversity trade-offs that must be made during task planning. Compressed sensing theory argues that the mutual coherence of the measurement probes is related to the reconstruction performance of sparse domains. With this motivation we compare the mutual coherence and corresponding reconstruction behavior of various mono-static and ultra-narrow band multi-static configurations, which trade-off frequency for geometric diversity. We investigate if such simple metrics are related to SAR reconstruction quality in an obvious way

A Review of the Enviro-Net Project

Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis.Comment: v2: 29 pages, 5 figures, reflects changes addressing reviewers' comments v1: 38 pages, 8 figure