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or the makespan of the task graph Another common objective is to distribute the tasks evenly among the processors; this is called load balancing This objective is necessary to make sure that all the processors are fully utilized, and to avoid the case of uneven job distribution, which causes some processors to be too busy while some others are idle It is also an objective in task scheduling to minimize the laxity rate in the processors A laxity in a processor is defined as the lax time between the completion of a task and the start of another task in the processor A high laxity rate reflects inefficiency in the scheduling system of the network, and this is intolerable as the running time for the system is expensive For a real-time system, it is important for a schedule to be designed so as to meet the deadline of executions.

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A soft deadline in the schedule indicates that compliance to it is not very critical to the overall functioning of the system The system may still function if there is some delay in the deadline although this may cause some discomfort or inconvenience In a system with a hard deadline, compliance to the deadline is very critical to system survival The system may lose some critical data or even crash if the deadline is not met For example, an aircraft due to land at an airport has a schedule with a tolerable soft deadline and intolerable hard deadline The aircraft has prepared itself to land before the soft deadline time of t1 but due to some unforeseen circumstances at the airport, it is unable to do so It can tolerate this delay by circling the airport a few times while waiting for clearance for landing.

The ultimate deadline, or hard deadline, for landing is then set at t2 A failure to land on or before t2 will result in a disaster as the aircraft may run out of fuel In reality, this problem has happened before; a South American aircraft crashed near an airport in New York, causing many deaths An optimum schedule in the mapping of tasks to processors helps to produce a healthy computing system in which the capability of the resources in the system is fully explored Some established methods for achieving this goal include methods based on list scheduling, clustering, mathematical programming, queueing theory, graph theoretic, and enumerated search There are also approaches using the latest tools in neural networks, simulated annealing, genetic algorithms, and other evolutionary algorithms There are two types of task scheduling.

The reader is in the text, and in a very similar way knowing in the face of mystery presumes a subject who is inside the knowledge production process and abandons him/herself to the centrifugal connections of meanings/actions The framework that I propose for analysis of the texture of a eld of practices is therefore indirect and metaphorical, since although texture can be shown or demonstrated it can never be de ned Explanation risks losing the very nature of what it seeks to elucidate Weaving, ie following the multivalent process that constitutes texture, is the analytical metaphor most appropriate for its understanding (Brogan, 1989) Nevertheless, this is not to imply that texture is a hidden object that cannot be grasped; rather, we should develop a style of thinking and doing research that enables us to show the relevance of connectedness in action and its continuing deferral.

In static scheduling, all the information about the tasks is known a priori, that is, before they are scheduled The information includes the length of the task, its precedence relationship with other tasks, and the related communication costs Very often, the task graph is known prior to scheduling, and this provides enough time to decide on the mapping Static task scheduling is often associated with offline scheduling in which its implementation is not critical and can be delayed On the other hand, if the state of the tasks is only known on the fly, that is, as the execution is in progress, then this is a case of dynamic scheduling Dynamic scheduling is more difficult to apply as it involves some extra overhead in determining the state of the arriving tasks and the processors at every time slot prior to scheduling the tasks.

Table 5.7: Project plan content Project Plan Content Resources Items Described in Content Availability of staff Techniques to Be Used Resource histogram Resource loading chart Required project phases Communication Risk Administration Contingency plans Various project phases needed Project communication Technical, financial Project support, meetings Backup, disaster & recovery Assessment Roles & responsibilities Risk modeling tools Organizational charts Assessment of solution

It is not always possible to get an optimum result in the form of minimum schedule length for this reason Therefore, the main objective in dynamic.

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