Joint allocation of uplink and downlink resources for interactive mobile cloud applications

Cloud‐based mobile applications are interactive in nature. Due to the strong correlation between uplink request and downlink response, it is irrational to optimize the uplink and downlink resource allocation problem separately and independently. In this paper, the joint uplink and downlink resource allocation problem for interactive mobile cloud applications is considered. The data exchange characteristics between mobile terminal and cloud server is investigated and a novel traffic model including both uplink and downlink transmission queues is constructed. Based on the new traffic model, the resource allocation problem can be formulated as a constrained Markov Decision Process. The objective is to minimize the application response time, that is, the roundtrip delay of causally related packet group (PG) pairs, with a constraint on PG drop rate. The Q‐learning algorithm and Value Iteration Algorithm are employed to obtain a solution that converges to the optimal one. To combat the curse of dimensionality, a sub‐optimal solution is proposed to solve the problem with an acceptable complexity. Numerical results indicate that the reduced complexity solution can achieve a delay performance approximate to that of the optimal solution and outperform other allocation schemes.