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Energy-optimized bandwidth allocation strategy for mobile cloud computing in LTE networks

机译：LTE网络中用于移动云计算的能源优化带宽分配策略

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This paper presents a mobile cloud computing application model and addresses how to minimize the energy consumption for uploading L size of data load within the T delay constraint. We propose a bandwidth allocation strategy for a LTE network with homogeneous sub-channel condition. Our objective is to allocate more bandwidth to each UE when its relative channel condition becomes better. We formulate the UE's objective function as the sum of two penalty functions: channel condition penalty function which incentivizes base stations to minimize the energy consumption for every UE and Service Level Agreement (SLA) demand penalty function which guarantees L size of data load that can be uploaded in time. In the network scenario, we formulate the EnerGy Optimized (EGO) bandwidth allocation strategy as a linear programming model and solve it by the Simplex Method. Simulation results show that EGO can save energy of up to 60% for each UE and decrease the SLA violation rate in the network of up to 30% in comparison with the existing bandwidth allocation strategy in the uplink of the LTE network.
机译：本文提出了一种移动云计算应用模型，并探讨了如何在T延迟约束内最小化上传L大小的数据负载的能耗。我们提出了具有同质子信道条件的LTE网络的带宽分配策略。我们的目标是在每个UE的相对信道状况变得更好时为其分配更多的带宽。我们将UE的目标函数表述为两个惩罚函数的总和：激励基站以使每个UE的能耗最小化的信道条件惩罚函数和服务水平协议（SLA）需求惩罚函数，该函数保证L个数据负载的大小为及时上传。在网络方案中，我们将EnerGy优化（EGO）带宽分配策略表述为线性规划模型，并通过单纯形法对其进行求解。仿真结果表明，与现有的LTE网络上行带宽分配策略相比，EGO可以为每个UE节省多达60％的能量，并降低网络中的SLA违规率高达30％。

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