Cost- and Energy-Aware Multi-Flow Mobile Data Offloading Using Markov Decision Process
Cost- and Energy-Aware Multi-Flow Mobile Data Offloading Using Markov Decision Process
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DOI：
10.1587/transcom.2017nrp0014
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发表时间：
2017-09
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影响因子：
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通讯作者：
Cheng Zhang;Bo Gu;Zhi Liu;K. Yamori;Y. Tanaka
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文献类型：
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作者：
Cheng Zhang;Bo Gu;Zhi Liu;K. Yamori;Y. Tanaka
随着对移动的数据的需求的快速增长，移动的网络运营商正试图通过部署无线局域网（LAN）热点来扩展无线网络容量，在所述LAN热点上他们可以卸载他们的移动的业务。然而，这些以网络为中心的方法通常不能满足移动的用户（MU）的利益。考虑到许多问题，MU应该能够决定是否将其流量卸载到互补的无线LAN。我们以前的工作研究了单流无线局域网卸载从MU的角度考虑延迟容忍的流量，货币成本和能源消耗。在本文中，我们研究了多流移动的数据卸载问题从MU的角度来看，MU有多个应用程序同时从远程服务器下载数据，不同的应用程序的数据有不同的截止日期。我们制定了无线局域网卸载问题作为一个有限时域离散时间马尔可夫决策过程（MDP），并建立了一个基于动态规划算法的最优策略。针对基于动态规划的卸载算法时间复杂度仍然较高的问题，提出了一种以性能为代价的低时间复杂度启发式卸载算法。大量的模拟进行验证我们提出的卸载算法。
With the rapid increase in demand for mobile data, mobile network operators are trying to expand wireless network capacity by deploying wireless local area network (LAN) hotspots on which they can offload their mobile traffic. However, these network-centric methods usually do not fulfill the interests of mobile users (MUs). Taking into consideration many issues, MUs should be able to decide whether to offload their traffic to a complementary wireless LAN. Our previous work studied single-flow wireless LAN offloading from a MU's perspective by considering delay-tolerance of traffic, monetary cost and energy consumption. In this paper, we study the multi-flow mobile data offloading problem from a MU's perspective in which a MU has multiple applications to download data simultaneously from remote servers, and different applications' data have different deadlines. We formulate the wireless LAN offloading problem as a finite-horizon discrete-time Markov decision process (MDP) and establish an optimal policy by a dynamic programming based algorithm. Since the time complexity of the dynamic programming based offloading algorithm is still high, we propose a low time complexity heuristic offloading algorithm with performance sacrifice. Extensive simulations are conducted to validate our proposed offloading algorithms.