Virtualization is the configuration of servers or clients which results in the division of resources into multiple and isolated execution environments, by applying one or more concepts or technologies to reduce costs and enhance flexibility associated with the acquisition, implementation, management, expansion, and recovery of critical business systems.
Virtualization is defined as a framework or methodology of dividing the resources of computer hardware into multiple execution environments, by applying one or more concepts or technologies such as hardware and software partitioning, time-sharing, partial or complete machine simulation, emulation, quality of service, and many others.
Figure 9 represents the execution cost by applying the proposed cost-based scheduling scheme and SAH-DB scheduling algorithm with 25 to 100 cloud containers respectively.
In this context, it seems that Big Data processing must profit from available computing resources by applying parallel execution models, thereby achieving results in "acceptable" times.
Performance-based indices measure the success of a grasp after its execution by lifting the object or by applying some small perturbation to it, which allows, for instance, the evaluation of the actual robustness of each grasp to store the results in a database that can be used in future grasp applications.
We also exploit work distribution locality through deferred load balancing: reducing the communication overhead and thrashing potential of load balancing algorithms by applying them across multiple execution instances of a loop.
But as each daily execution of the FTMM chain shares most of these data with the previous execution, there are significant efficiencies to be gained by applying Steps 1 to 5 only to the new data.
First, by applying a "Market risk - Execution risk" map to establish a firm's strategy, from incremental to breakthrough innovations.
This result was achieved by applying a dependable routing algorithm and dependable task execution.
By applying DTW, we gain robustness against variations in execution rates, which heavily affect HAR.
