An iconic programming language for sensor-based robots

In this paper we describe an iconic programming language called Onika for sensor-based robotic systems. Onika is both modular and reconfigurable and can be used with any system architecture and real-time operating system. Onika is also a multi-level programming environment wherein tasks are built by connecting a series of icons which, in turn, can be defined in terms of other icons at the lower levels. Expert users are also allowed to use control block form to define servo tasks. The icons in Onika are both shape and color coded, like the pieces of a jigsaw puzzle, thus providing a form of error control in the development of high level applications

Reconfigurable Security: Edge Computing-based Framework for IoT

In various scenarios, achieving security between IoT devices is challenging since the devices may have different dedicated communication standards, resource constraints as well as various applications. In this article, we first provide requirements and existing solutions for IoT security. We then introduce a new reconfigurable security framework based on edge computing, which utilizes a near-user edge device, i.e., security agent, to simplify key management and offload the computational costs of security algorithms at IoT devices. This framework is designed to overcome the challenges including high computation costs, low flexibility in key management, and low compatibility in deploying new security algorithms in IoT, especially when adopting advanced cryptographic primitives. We also provide the design principles of the reconfigurable security framework, the exemplary security protocols for anonymous authentication and secure data access control, and the performance analysis in terms of feasibility and usability. The reconfigurable security framework paves a new way to strength IoT security by edge computing.Comment: under submission to possible journal publication

Development of a software application for machine tool reconfiguration using a knowledge-based engineering system approach

The automation processes industry has become increasingly expensive, which is why some small and medium sized enterprises are incapable of buying machine tools with automatic systems. This means that their processes are manual in many cases, and as a result they often have to rework their developed products due to the lack of precision and efficiency in their production processes. Considering that current manufacturing systems with variable machining and turning centers are gradually replacing dedicated systems for medium lot size production, the production systems' basic element, the machine tool, must be capable of working at high speeds with precision, and it must be reconfigurable. These systems must also be compatible and convertible in order to create economic benefits for customers. This article describes a specific software architecture designed to record all the data, information and knowledge concerning manufacturing systems. The software allows for the creation of a new knowledge database and works with it in the reconfiguration of machine tools depending on the rules, requirements and parameters needed to effectively modify production processes or products.Hincapie, M.; Guemes, D.; Contero González, MR.; Ramirez, M.; Diaz, C. (2016). Development of a software application for machine tool reconfiguration using a knowledge-based engineering system approach. International Journal of Knowledge-Based and Intelligent Engineering Systems. 20(1):49-63. doi:10.3233/KES-160334S496320

High Performance Biological Pairwise Sequence Alignment: FPGA versus GPU versus Cell BE versus GPP

This paper explores the pros and cons of reconfigurable computing in the form of FPGAs for high performance efficient computing. In particular, the paper presents the results of a comparative study between three different acceleration technologies, namely, Field Programmable Gate Arrays (FPGAs), Graphics Processor Units (GPUs), and IBM’s Cell Broadband Engine (Cell BE), in the design and implementation of the widely-used Smith-Waterman pairwise sequence alignment algorithm, with general purpose processors as a base reference implementation. Comparison criteria include speed, energy consumption, and purchase and development costs. The study shows that FPGAs largely outperform all other implementation platforms on performance per watt criterion and perform better than all other platforms on performance per dollar criterion, although by a much smaller margin. Cell BE and GPU come second and third, respectively, on both performance per watt and performance per dollar criteria. In general, in order to outperform other technologies on performance per dollar criterion (using currently available hardware and development tools), FPGAs need to achieve at least two orders of magnitude speed-up compared to general-purpose processors and one order of magnitude speed-up compared to domain-specific technologies such as GPUs