This chapter presents the scheduling problem in large scale distributed systems. Most parts of the chapter are devoted to discussion of scheduling algorithms and models. The main challenges of scheduling problem are approached here. The implementation issues are also covered. The chapter has three parts. The first part covers basics like scheduling models, scheduling algorithms for independent tasks and DAG scheduling Algorithms for tasks with dependencies. The first part of the chapter presents a classification of scheduling problems, methods that are relevant for the solution procedures, and computational complexity. The scheduling models are presented based on systems architecture described in Resource Management chapter. This firs part also provides a critical analysis of most important algorithms from different points of view, such as static versus dynamic policies, objective functions, applications models, adaptation, QoS constraints and strategies dealing with dynamic behavior of resources. The second part covers new scheduling mechanism like resources co-allocation and advance reservation. Multi-criteria optimization mechanisms for users and systems constrain (e.g. load-balancing, minimization of execution time) are described and analyzed in this chapter. This part uses algorithm and methods to highlight the importance of these topics. The dynamic scheduling is also the subject of this part. It is also presented the implementation issues for scheduler tools. Since it is not possible to cover the whole area of scheduling in one chapter, some restrictions are imposed. Firstly, the chapter presents only Scheduling for Large Scale Distributed Systems (LSDS), without single system scheduling. Secondly, some interesting topics of fault tolerance (re-scheduling) are not analyzed in this chapter.
A new improved genetic algorithm approach and a competitive heuristic method for large-scale multiple resource-constrained project-scheduling problems