… Then, using stochastic optimization, we model the problem of minimizing power while …
framework for stochastic optimization problems and use it to solve our network slicing problem. We …

… We assume a network slices demand up to 32 network slice … to brute-force optimization
methods. Our work puts forth network slicing as a suitable approach for optimizing the radio …

… the learning-aided stochastic network optimization with dual … for the distributed stochastic
sensor network problem. The … In contrast, this paper highlights the stochastic combinatorial …

… , provisioning, dimensioning and deletion of network slices. The proposed algorithm is …
network slices of appropriate granularity. In addition, we also propose a stochastic optimization …

… networks operating under uncertainties (examples include [5]–[11]). We establish a stochastic
optimization … near-optimal solution of the stochastic optimization problem. We consider two …

… optimal joint slice recovery and reconfiguration algorithm for stochastic traffic demands by
exploiting robust optimization. To tackle the slow convergence issue in the robust optimization …

… slicing aided mobile systems is formulated considering both throughput and delay … network
operator’s perspective, whilst relying on stochastic geometry and Lyapunov optimization. …

… To solve the problem, we first transform the stochastic programming problem into a deterministic
optimization problem. We further apply semidefinite relaxation to transform the problem …

… stochastic environment without foreseeing the future network … network slicing technology in
stochastic vehicular networks to … networks, two types of network slicing, namely eMBB slicing …

… set (ie, it can only solve integer stochastic optimization problem). The discrete action space
not only brings quantization error for the continuous stochastic optimization problem, but also …