ABSTRACT
Optimization by using heterogeneous com-
putings is one of the crucial methods for increasing performances. Embedded systems have many constraints, such as time, reliability, and energy consumption. Balancing these constraints is an efficient mechanism to increase the performance of an embedded system. Therefore, leveraging heterogeneous computing in mobile embedded systems is an optimization problem. Dynamic programming is an important approach for optimizing embedded systems, and this has been broadly used in multiple industries
and mobile domains. This chapter focuses on introducing the updated mechanism of adopting dynamic programming in embedded systems. The represented schema is named Heterogeneous Embedded Systems (HES) that can be used to enable embedded systems to accomplish works with the least resource costs under a specific timing constraint. Two models of heterogeneous embedded systems are introduced in this chapter. The main contents of this chapter include:
1. Dynamic programming
2. Heterogenous embedded systems
3. Fixed time model of heterogenous embedded systems
4. Probabilistic time model of heterogenous embedded systems
This chapter intends to instruct students to learn an important mechanism being used in the current mobile optimization domains, which is HES. This is an important mechanism for increasing the performance of the heterogeneous memory. The system is based on leveraging dynamic programming algorithm and the corresponding implementations will be covered in this chapter. A few examples and case studies will be given in this chapter to aid students to further understand the schemas of dynamic programming. Throughout this chapter, students should be able to answer the following questions:
1. What is the HES?
