#Fuzzy Logic Software Software Has Been

Fuzzy Logic Software Software Has Been

The software has been prepared as a collection of M-files for Matlab (a registered trademark of The MathWorks, Inc.). It is in six sections: general type-2 fuzzy logic systems, interval type-2 fuzzy logic systems, type-1 fuzzy logic systems, type-reduction, interval approach to fuzzistics, and novel weighted averages.Traditional load balancing hardware is expensive and lacks scalability and flexibility. We propose a load balancing strategy based on fuzzy logic (LBSFL), which exploits the control and forwarding separation architecture characteristics of software-defined networking (SDN).

It can be implemented in systems with various sizes and capabilities ranging from small micro-controllers to large, networked, workstation-based control systems. Based on this, the load state of the virtual server is evaluated through fuzzy logic. Then the centralized control capability of SDNвЂ™s controllers for the whole network is utilized to monitor virtual server information in real time and to schedule virtual server tasks. Individual servers can be hibernated or restarted, to save power or to increase performance as necessary.

R.An Application of Fuzzy Logic for Hardware/Software Partitioning in Embedded SystemsAplicaciГіn de lГіgica difusa para el particionado hardware/software en sistemas embebidosHumberto DГaz Pando 1, Sergio Cuenca Asensi 2, Roberto SepГєlveda Lima 1, Jenny Fajardo CalderГn 1 and Alejandro Rosete SuГЎrez 11 School of Informatics Engineering, CUJAE, Havana Cuba.2 University of Alicante, Spain received on Hardware/Software partitioning (HSP) is a key task for embedded system co-design. Figure 1: Fuzzy Model for Prioritization After the fuzzification process, there is a fuzzy set for eachApplication of Fuzzy Logic Approach to Software. This will use MamdaniвЂ™s fuzzy inference method which is most commonly seen fuzzy methodology as shown in Figure 2. Fuzzy Inference System (FIS) is the process of formulating the mapping from a given input to an output using fuzzy logic.

This article presents the results of applying a fuzzy approach to the HSP problem. However, due to diversity of models and metrics used, the choice of the best suited algorithm is an open problem yet. In last years, several approaches have been proposed for solving the HSP problem, directed by metaheuristic algorithms.

En los Гєltimos anos, se han propuesto diferentes estrategias para resolver el problema PHS, las cuales utilizan en su mayorГa algoritmos metaheurГsticos. El objetivo principal de esta etapa es decidir que componentes de la aplicaciГіn serГan ejecutados en un procesador de propГіsito general (software) y cuales en un hardware especГfico, teniendo en cuenta las restricciones. The obtained results show that Restart Hill Climbing is the best performing algorithm in most cases.Keywords:В Hardware/software co-design, hardware/software partitioning, metaheuristic algorithms.El Particionado Hardware/Software (PHS) es una etapa fundamental en el co-diseГ±o de sistemas embebidos. The presented model is aimed to simultaneously minimize the hardware area and the execution time. In this work we compare six metaheuristic algorithms: Random Search, Tabu Search, Simulated Annealing, Hill Climbing, Genetic Algorithm and Evolutionary Strategy.

El modelo que se presenta estГЎ dirigido a minimizar de forma simultГЎnea el ГЎrea de hardware y el tiempo de ejecuciГіn del sistema. AdemГЎs en este trabajo se comparan seis algoritmos metaheurГsticos: BГєsqueda aleatoria, BГєsqueda tabГє, Recocido simulado, Escalador de colinas, Algoritmo genГ©tico y Estrategia evolutiva. Esta estrategia es mГЎs flexible que muchas de las otras propuestas, ya que es posible aceptar soluciones bastante buenas o rechazar otras que no parezcan buenas. Este artГculo presenta los resultados de aplicar lГіgica difusa en el problema PHS.

On the hardware-software partitioning problem: System modeling and partitioning techniques. ACM Transactions on Design Automation of Electronic Systems (TODAES), 10(1), 136-156. Algorithmic aspects of hardware/software partitioning. Arato, P., Mann, Z.A., & Orban, A. A decade of hardware/software codesign.

Jigang, W., Srikanthan, T., & Jiao, T. Information Processing Letters, 98(2), 41-46. Low-complex dynamic programming algorithm for hardware/software partitioning.

Hardware software partitioning problem in embedded system design using particle swarm optimization algorithm. Bhattacharya, A., Konar, A., Das, S., Grosan, C., & Abraham, A. Journal of Computer Science and Technology, 23(4), 644-651. New model and algorithm for hardware/software partitioning. Wu, J.G., Srikanthan, T., & Zou, G.W. Design Automation for Embedded Systems, 12(4), 345-375.

Partitioning algorithms for hardware/software co-design. 17th ACM Great Lakes symposium on VLSI (GLSVLSI '07), Stresa-Lago Maggiore, Italy, 359-364. HW/SW partitioning using discrete particle swarm. Farmahini-Farahani, A., Kamal, M., Fakhraie, S.M., & Safari, S.

Verdegay, J.L., Yager, R.R., & Bonissone, P.P. International Conference on Information Technology: Coding and Computing (ITCC 2004), Las Vegas, Nevada, USA, 2, 508-512. Efficient cryptographic hardware using the co-design methodology.

An approach to automated hardware/software partitioning using a flexible granularity that is driven by high-level estimation techniques. Master's thesis, Faculty of the Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA. Model based approach to hardware/software partitioning of SOC designs. Fuzzy Sets Systems, 159(7), 846-855.

A survey on hardware/software codesign representation models. Cortes, L.A., Eles, P., & Peng, Z. Lecture Notes in Electrical Engineering, 60, 201-213. Electronic Engineering and Computing Technology. Models of computation for heterogeneous embedded systems in Electronic Engineering and Computing Technology. Shaout, A., El-Mousa, A.H., & Mattar, K.

Gohringer, D., Hubner, M., Benz, M., & Becker, J. IEEE Design & Test of Computers, 10(3), 29-41. Hardware-software cosynthesis for digital systems.

IEEE Design & Test of computers, 10(4), 64-75. Hardware-softwareВ cosynthesis for microcontrollers. Ernst, R., Henkel, J., & Benner, T. 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), Charlotte, NC, USA, 259-262.

System level hardware/software partitioning based on simulated annealing and tabu search. Eles, P., Peng, Z., Kuchcinski, K., & Doboli, A. Design Automation for Embedded Systems, 6(4), 425-449.

Madsen, J., Grode, J., Knudsen, P.V., Petersen, M.E., & Haxthausen, A. Journal of Systems Architecture: the EUROMICRO Journal, 53(7), 339-354. Genetic algorithms for hardware-software partitioning and optimal resource allocation. Purnaprajna, M., Reformat, M., & Pedrycz, W.

Design, automation & test in Europe, Paris, France, 914-915. A knowledge-based system for hardware-software partitioning. LГіpez, M.L., Iglesias, C.A., & LГіpez, J.C. Design Automation for Embedded Systems, 2(2), 195-235.

A hardware/software partitioning algorithm based on artificial immune principles. Zhang, Y., Luo, W., Zhang, Z., Li, B., & Wang, X. 4 th International Conference on Modeling Decisions for Artificial Intelligence (MDAI '07), Kitakyushu, Japan, 307-317.

Genetic and Evolutionary Computation Conference, Orlando, Florida, USA, 2, 1699-1706. Automatic graph drawing and stochastic hill climbing. Rosete-SuГЎrez, A., Ochoa-RodrГguez, A., & Sebag, M. Revista Iberoamericana de Inteligencia Artificial, 3(8), 18-26. Hacia un enfoque general del trazado de grafos. Rosete-SuГЎrez, A., Nogueira-Keeling, A., Ochoa-RodrГguez, A., & Sebag, M.

Revista Internacional de InvestigaciГіn de Operaciones (RIIO), 1.