The explosive growth of global mobile traffic has lead to a rapid growth inthe energy consumption in communication networks. In this paper, we focus onthe energy-aware design of the network selection, subchannel, and powerallocation in cellular and Wi-Fi networks, while taking into account thetraffic delay of mobile users. The problem is particularly challenging due tothe two-timescale operations for the network selection (large timescale) andsubchannel and power allocation (small timescale). Based on the two-timescaleLyapunov optimization technique, we first design an online Energy-Aware NetworkSelection and Resource Allocation (ENSRA) algorithm. The ENSRA algorithm yieldsa power consumption within O(1/V) bound of the optimal value, and guarantees anO(V) traffic delay for any positive control parameter V. Motivated by therecent advancement in the accurate estimation and prediction of user mobility,channel conditions, and traffic demands, we further develop a novel predictiveLyapunov optimization technique to utilize the predictive information, andpropose a Predictive Energy-Aware Network Selection and Resource Allocation(P-ENSRA) algorithm. We characterize the performance bounds of P-ENSRA in termsof the power-delay tradeoff theoretically. To reduce the computationalcomplexity, we finally propose a Greedy Predictive Energy-Aware NetworkSelection and Resource Allocation (GP-ENSRA) algorithm, where the operatorsolves the problem in P-ENSRA approximately and iteratively. Numerical resultsshow that GP-ENSRA significantly improves the power-delay performance overENSRA in the large delay regime. For a wide range of system parameters,GP-ENSRA reduces the traffic delay over ENSRA by 20~30% under the same powerconsumption.
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