In this work we present a distributed event-based awareness approach for P2P groupware systems. One important domain is that of mobile applications supporting collaborative work, such as, eLearning and eHealth. Mobile computing has many application domains. The simulation results show that the proposed system makes a proper selection decision of IoT-devices in opportunistic networks. We evaluate the performance of the proposed system by simulations. The output parameter is IoT device selection decision. We propose a delay-aware fuzzy-based system consisting of three input parameters. In this work, we consider the IoT device selection problem in opportunistic networks. Therefore, nodes need to communicate with each other via opportunistic contacts through store-carry-forward operation. When there is no path existing between the source and the destination, the network partition occurs.
These events result in intermittent connectivity. In an opportunistic network, when nodes move away or turn off their power to conserve energy, links may be disrupted or shut down periodically. These networks can be useful for routing in places where there are few base stations and connected routes for long distances. The opportunistic networks are the variants of Delay Tolerant Networks (DTNs).
PRINT DESIRED SIGNALS IN AWS FPGA SIMULATION SOFTWARE
The aim of the volume “Complex, Intelligent and Software Intensive Systems” is to provide a platform of scientific interaction between the three interwoven and challenging areas of research and development of future Information and Communications Technology (ICT)-enabled applications: Software Intensive Systems, Complex systems and Intelligent Systems. Recent research in the fields of intelligent systems, robotics, neuroscience, artificial intelligence, and cognitive sciences is essential to the future development of and innovations in software intensive and complex systems. The development of Intelligent Systems and agents, which invariably involves the use of ontologies and their logical foundations, offers a fruitful impulse for both Software Intensive Systems and Complex Systems. They evolve and adapt through internal and external dynamic interactions. Complex Systems are very much shaped by the changing environments in which they operate, and by their multiple internal and external interactions. Moreover, the outcome of web services delivers a new platform for enabling software intensive systems.Ĭomplex Systems research is focused on the understanding of a system as a whole rather than its components. the automotive sector, telecommunication systems, embedded systems in general, industrial automation systems and business applications. Further, they are now being used in more and more domains, e.g. Software Intensive Systems are characterized by their intensive interaction with other systems, sensors, actuators, devices, and users. Once this is done, I implement it using Verilog (behavioural style) and write a test bench to simulate it with the same arbitrary inputs and compare both the output signals.This book gathers the proceedings of the 11th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2017), held on June 28–Jin Torino, Italy. What I have done here is, designing a LPF butterworth filter using Python and simulate to see how it works using some arbitrary inputs. If, this filter is to be implemented on hardware such as FPGA, one should go about writing the made design, using a Hardware Description Language such as VHDL or Verilog. Once the calculations are done, the frequecy response, as well as simulations can be done in the same language to know how the calculated coefficients perform.
Thanks to latest tools like MATLAB and Python (Scipy), It has become easy as the strenuous calculations are done by the computers. Running a simulation and cross-checking the result with the one simulated in Python.ĭesiging a IIR filter is a lengthy and Time consuming process. Designing, Implementing and Verifying IIR Filter ¶ĭesiging an IIR LOWPASS Butterworth filter, at any desired $\omega$ and implementing it using a Verilog program.
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