Service-Oriented Architecture for Space Exploration Robotic Rover Systems

Currently, industrial sectors are transforming their business processes into e-services and component-based architectures to build flexible, robust, and scalable systems, and reduce integration-related maintenance and development costs. Robotics is yet another promising and fast-growing industry that deals with the creation of machines that operate in an autonomous fashion and serve for various applications including space exploration, weaponry, laboratory research, and manufacturing. It is in space exploration that the most common type of robots is the planetary rover which moves across the surface of a planet and conducts a thorough geological study of the celestial surface. This type of rover system is still ad-hoc in that it incorporates its software into its core hardware making the whole system cohesive, tightly-coupled, more susceptible to shortcomings, less flexible, hard to be scaled and maintained, and impossible to be adapted to other purposes. This paper proposes a service-oriented architecture for space exploration robotic rover systems made out of loosely-coupled and distributed web services. The proposed architecture consists of three elementary tiers: the client tier that corresponds to the actual rover; the server tier that corresponds to the web services; and the middleware tier that corresponds to an Enterprise Service Bus which promotes interoperability between the interconnected entities. The niche of this architecture is that rover's software components are decoupled and isolated from the rover's body and possibly deployed at a distant location. A service-oriented architecture promotes integrate-ability, scalability, reusability, maintainability, and interoperability for client-to-server communication.Comment: LACSC - Lebanese Association for Computational Sciences, http://www.lacsc.org/; International Journal of Science & Emerging Technologies (IJSET), Vol. 3, No. 2, February 201

Towards formal models and languages for verifiable Multi-Robot Systems

Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation. We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.Comment: Changed formattin

Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

Income Distributional Effects of Using Market-Based Instruments for Managing Common Property Resources

In the face of growing management problems and conflicts over increasing demands and dwindling or increasingly variable supplies of surface and groundwater, the need for revising the conventional water resource allocation methods has been increasingly felt among natural resource managers and policy makers. For the past 30 years economists have advocated for the application of various types of market-based instruments (MBIs) as an efficient means of effecting the re-allocation water resources among competing uses. While MBIs have been implemented in several countries, they have continued to encounter strong socio-political opposition, due to the impacts imposed on third-parties during transfers and re-allocations, as well as the distributional effects across different types of water users. Despite the demonstrable efficiency gains of MBIs, the resulting equity or distributional effects of MBI-driven re-allocations can be of equal or greater importance to policy-makers and the constituents that they serve. At the same time, the realized gains in economic efficiency from the application of MBIs depend heavily on the heterogeneity of the agents they are targeted towards, as well as the degree of information asymmetry that the regulator faces. In this paper, we use a simple theoretical framework to show the trade-offs between efficiency and equity that might arise from the application of MBIs to a heterogenous population of agents drawing non-cooperatively from a natural resource pool. Using the idealized centralized planner as a benchmark of dynamic, allocative efficiency, we compare the realized efficiency gains that can be realized by alternative policy instruments and the resulting impacts on distributional equity, in terms of the cumulative net benefits over time. Using the specific example of groundwater and the empirical setting of Southern California, we are able to highlight the trade-offs between efficiency and equity that might exist among alternative policy instruments, and how MBIs perform with respect to those dual criteria. We find that under agent heterogeneity, there are asymmetric gains in efficiency when the centralized planner allocations are constrained by equity considerations. Through such results, this paper demonstrates the importance of considering both efficiency gains and the minimization of disparities in distributional inequity, when designing policy instruments that create winners and losers with potentially serious socio-political ramifications.Resource /Energy Economics and Policy,

A Review on Modern Distributed Computing Paradigms: Cloud Computing, Jungle Computing and Fog Computing

The distributed computing attempts to improve performance in large-scale computing problems by resource sharing. Moreover, rising low-cost computing power coupled with advances in communications/networking and the advent of big data, now enables new distributed computing paradigms such as Cloud, Jungle and Fog computing.Cloud computing brings a number of advantages to consumers in terms of accessibility and elasticity. It is based on centralization of resources that possess huge processing power and storage capacities. Fog computing, in contrast, is pushing the frontier of computing away from centralized nodes to the edge of a network, to enable computing at the source of the data. On the other hand, Jungle computing includes a simultaneous combination of clusters, grids, clouds, and so on, in order to gain maximum potential computing power.To understand these new buzzwords, reviewing these paradigms together can be useful. Therefore, this paper describes the advent of new forms of distributed computing. It provides a definition for Cloud, Jungle and Fog computing, and the key characteristics of them are determined. In addition, their architectures are illustrated and, finally, several main use cases are introduced

Leveraging cloudlets for immersive collaborative applications

To enable immersive applications on mobile devices, the authors propose a component-based cyber foraging framework that optimizes application-specific metrics by not only offloading but also configuring application components at runtime. It also enables collaborative scenarios by sharing components between multiple devices