Efficient Mobile Computation Offloading over a Finite-State Markovian Channel using Spectral State Aggregation

This paper considers the problem of mobile computation offloading under stochastic wireless channels while task completion times are subject to deadline constraints. Our objective is to conserve energy for the mobile device by making an optimal decision to execute the task either locally or remotely. In the case of computation offloading, we dynamically vary the data transmission rate, in response to channel conditions. The wireless transmission channel is modelled using a Finite-State Markov Chain (FSMC). We formulate the problem of computation offloading as a constrained optimization problem, and develop an online algorithm to derive the optimal offloading policy. Moreover, to reduce the complexity, we estimate a suboptimal solution of the proposed online algorithm by reducing the size of the FSMC with the help of Markovian aggregation. The numerical results indicate that by applying Markovian aggregation, the running time of the algorithm can be significantly reduced without suffering unreasonable performance degradation.