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Figure 10 Optimal scalable TLR scheme for the surface code.
Having set these definitions, we present the steps that we follow to find the optimal scalable TLR without doubled TLRs.
Following the above algorithm, we find the scalable optimal architectures presented in Table 6 and Figure 8. Figure 8 Pictorial representation of the optimal scalable solution of Table 6.
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This approach is an optimal and scalable parallelization of the well known two-list Horowitz and Sahni's algorithm, which is still the best complexity time bound for solving the Knapsack problem in a serial environment.
Solving the binary linear optimization problem with (m=5), we find the scalable optimal TLR scheme reported in Figure 10.
While solving such programs is a NP-hard problem, we propose a way to find scalable optimal architectures that require solving the linear program for a restricted number of qubits and couplers.
We evaluate the performance of the proposed cross-layer optimization solution for scalable video delivery in terms of an optimal network resource usage and QoE by exploiting a simulation environment developed in the FP7 ICT-OPTIMIX project.
The optimal MCS assignment for scalable video multicast can be mathematically stated as follows.
First, we focus on finding the optimal solution in non-scalable media distribution.
COPA is scalable and yields optimal solutions consuming less computational time.
The resulting optimal scheduler is amenable of scalable and distributed online implementation and its analytical characterization is in closed-form.
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