**4. Grid technology for embedded system and application**

Grid computing is another way of distributed computing. Distributed computing is a science which solves a large problem by giving small parts of the problem to many computers to solve and then combining the solutions for the parts into a solution for the problem. Grid Computing finds many potential opportunities and advantages in the fields of education, research, engineering, bio-medicine, pharmaceuticals, financial sector and government organizations(Mark,el.,2002). In the embedded system design the gird computing technology is used for improving the developing cycle of the embedded system . for example, GridSim is a toolkit for modeling and simulation of Grid resources and application scheduling. It provides a comprehensive facility for the simulation of different classes of heterogeneous resources, users, applications, resource brokers, and schedulers. It has facilities for the modeling and simulation of resources and network connectivity with different capabilities, configurations, and domains. It supports primitives for application composition, information services for resource discovery, and interfaces for assigning application tasks to resources and managing their execution. These features can be used to simulate resource brokers or Grid schedulers to evaluate performance of scheduling algorithms or heuristics(Buyya R, el.,2002). May programs are built based on the gird technology one of this program is the MATLAB and SimuLink which is used in this study.

MATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. The MATLAB infrastructure design is based on the gird computing technology .MATLAB is used to solve problems in several application areas such as signal and image processing, communications, control design, test and measurement, financial modeling and analysis, and computational biology. Add-on toolboxes extend the MATLAB environment to solve particular classes of problems in different application areas.

Simulink is a companion product to MATLAB that offers an environment for multidomain simulation and Model-Based Design for dynamic and embedded systems. It provides an interactive graphical environment and a customizable set of block libraries that allows users to design, simulate, implement, and test a variety of time-varying systems.

In this chapter we used the Model Based Design method to eliminate some of the embedded system challenges. Model Based Design is a simulation based method so, if the embedded system becomes large and more complicated, its simulation time will be increased. To accelerate the simulation time of such embedded systems, some parallel and distributed systems (grid computing method) are necessary.
