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Most large-scaled software systems are structured in distributed components to manage complexity and have to cope with concurrent executed threads.
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Second, along any concurrent execution, each processor executes the critical step infinitely often.
Loops that are suitable for concurrent execution are changed to execute on a set of concurrent server processes.
In this paper, we present a model for reasoning about energy consumed by concurrent computations executing on multicore processors, and mechanisms involved in creating schedules – of resource usage as well as frequencies at which processor cores should execute – for completing computation in an energy-efficient manner.
The key to maintaining database correctness is therefore to ensure that only complete transactions are applied to the data and that multiple concurrent transactions are executed (under a concurrency control mechanism) in such a way that a serial order can be defined that would produce the same results.
The key here is to ensure that only complete transactions are applied to the data and that multiple concurrent transactions are executed using locking so that serializing them would produce the same result.
Dependences constrain the program's concurrent execution because, in general, two conflicting statements cannot execute in a different order without affecting the program's result.
This allows the concurrent execution of successive tasks, i.e., a reducer can start executing as soon as it receives it's input from a mapper, without requiring all the mappers to finish first.
To ensure the optimal concurrent scheduling and the effective utilization of resources along with efficient delivery of information, some key factors such as time order, information, resources, lead-time and overlapping time of activities, which enable concurrent activities to be executed successfully, are taken into account.
In this paper, we have discussed the challenging problem that arises when multiple concurrent SON functions are executed by the same node, or different instances of the same or different SON functions are executed in neighboring cells.
A quasi-experimental study (a pre/post study with a concurrent control group) was executed (fig. 1).
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