Fig 8 - uploaded by Behnam Khaleghi
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Example of Markov chain for workload prediction.
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The continuous growth of big data applications with high computational and scalability demands has resulted in increasing popularity of cloud computing. Optimizing the performance and power consumption of cloud resources is therefore crucial to relieve the costs of data centers. In recent years, multi-FPGA platforms have gained traction in data cen...
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Context 1
... there are M × M edges between states where each edge has a probability learned during the training steps to predict the size of the incoming workload. Figure 8 represents a Markov chain model with 4 states, {S 0 , S 1 , S 2 , S 3 }, in which a directed edge with label P i,j shows the transition from S i to S j which happens with the probability of P i,j . Considering the The total probability of the outgoing edges of state S i has to be 1 as probability of selecting the next state is one. ...
Context 2
... there are M × M edges between states where each edge has a probability learned during the training steps to predict the size of the incoming workload. Figure 8 represents a Markov chain model with 4 states, {S 0 , S 1 , S 2 , S 3 }, in which a directed edge with label P i,j shows the transition from S i to S j which happens with the probability of P i,j . Considering the The total probability of the outgoing edges of state S i has to be 1 as probability of selecting the next state is one. ...
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