Multiprocessor scheduling and rescheduling with use of cellular automata and artificial immune system support

Scheduling in a dynamic heterogeneous distributed system using estimation error

“…Many scheduling algorithms (other than the most trivial) utilize knowledge of the available system resources and the tasks to be processed when deciding to allocate a task to a processor [3,8,10,28,33,36,37,42]. How to best generate this knowledge is an open problem [37], which is dealt with in different ways.…”

“…The accuracy of these estimations becomes particularly important in distributed systems, where users must pay for processing, where demand for computational resources outstrips supply, or where a problem must be processed as quickly as possible. The most common form of estimating task execution times is by benchmarking a task or set of tasks offline in advance [3,8,33,36,37]. The heterogeneous and non-dedicated nature of the resources in a loosely-coupled distributed system means that this type of estimation can introduce a large amount of error, between the actual execution time and the estimated execution time of a set of tasks.…”

“…Other algorithms require the user to define the length of time that a problem is expected to take [3,8,33,36,37]. Many require a directed acyclic graph with task and communication information, and precedence constraints given in advance [3,8,24,26,25,33,36,37].…”

“…Many require a directed acyclic graph with task and communication information, and precedence constraints given in advance [3,8,24,26,25,33,36,37]. Communication costs are also not properly considered by many algorithms, for example all communication links are assumed to be homogeneous [41], it is assumed communication and computation can take place simultaneously [8], or it is assumed that there is instantaneous message passing [43].…”

An Artificial Immune System for Heterogeneous Multiprocessor Scheduling with Task Duplication

“…Due to the self-organizing, cooperative and robust characteristics of the immune system its applicability to various areas, such as pattern recognition, network security and anomaly detection has been actively studied in the past decade [2,3,4]. However, only recently immune system based scheduling algorithms have been developed by researchers to target different instances of the problem [5,6,7,8].…”