Cloud offloading is considered a promising approach for both energy conservation and storage/computation enhancement for resource-limited mobile devices. In this paper, we present a Lyapunov optimization-based scheme for cloud offloading scheduling, as well as download scheduling for cloud execution output, for multiple applications running in a mobile device with a multi-core CPU. We derive an online algorithm and prove performance bounds for the proposed algorithm with respect to average power consumption and average queue length, which is indicative of delay, and reveal the fundamental tradeoff between the two optimization goals. The performance of the proposed online scheduling scheme is validated with trace-driven simulations.

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This paper studies how to maximize the per-user-based throughput in an M-tier heterogeneous wireless network (HetNet) by optimally managing traffic flows among the access points (APs) in the HetNet. The APs in the first M − 1 tiers can use the licensed spectrum at the same time whereas they share the unlicensed spectrum with the APs in the M th tier by the proposed opportunistic CSMA/CA protocol. We characterize the statistical property of the cell load and channel access probability of each AP using a general AP association scheme. For an AP in each tier, the tight bounds on its mean spectrum efficiencies in the licensed and unlicensed spectra are derived in a low-complexity form for general random channel gain and AP association weight models and they can give some insights on how channel gains, AP association weights and void AP probabilities affect the mean spectrum efficiencies. We define the per-user link throughput and per-user network throughput based on the derived the mean spectrum efficiencies and maximize them by proposing the decentralized and centralized traffic management schemes for the APs in the first M − 1 tiers under the constraint that the per-user link throughput of the tier-M APs must be above some minimum required value. Finally, a numerical example of coexisting LTE and WiFi networks is provided to validate our derived results and findings.

Femtocells are small, low‐power cellular base stations with high potential for coverage extension and offloading voice and wireless data. In this paper, we study the problem of joint access control and spectrum resource allocation in a 2‐tier femtocell network with 1 macro base station and multiple Femto access points (FAPs). The objective is to maximize the overall network capacity, while guaranteeing the quality of service requirement of all user equipments. We develop an access scheme for macro user equipments and a spectrum allocation mechanism for the FAPs. Spectrum allocation is used as an incentive mechanism to encourage FAPs to serve more macro user equipments. We also derive an upper bound of the network‐wide capacity through a reformulation of the problem. The proposed algorithms are validated, and the upper bound is shown to be quite accurate in the simulation study.

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