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首页> 外文期刊>Vehicular Technology, IEEE Transactions on >Energy-Efficient Scheduling in Green Vehicular Infrastructure With Multiple Roadside Units
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Energy-Efficient Scheduling in Green Vehicular Infrastructure With Multiple Roadside Units

机译：具有多个路边单元的绿色车辆基础设施中的节能调度

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In this paper, we propose low-complexity algorithms for downlink traffic scheduling in green vehicular roadside infrastructure. In multiple roadside unit (RSU) deployments, the energy provisioning of the RSUs may differ, and it is therefore desirable to balance RSU usage from a normalized min-max energy viewpoint. This paper considers both splittable RSU assignment (SRA) and unsplittable RSU asssignment (URA) scheduling. An offline integer linear programming bound is first derived for normalized min-max RSU energy usage. We then show that in the SRA case, there is a polynomial complexity 2-approximation bound for the normalized min-max energy schedule. This paper then proposes several online scheduling algorithms. The first is a greedy online algorithm that makes simple RSU selections, followed by minimum-energy time slot assignments. A normalized min-max algorithm is then proposed [2-approximation online algorithm (TOAA)], which is an online version of the 2-approximation bound. Two algorithms are then introduced based on a potential function scheduling approach. The 1-objective algorithm uses an objective based on normalized min-max energy, and we show that it has an upper bounded worst-case competitive ratio performance. The 2-objective algorithm uses the same approach but incorporates a total-energy secondary objective as well. Results from a variety of experiments show that the proposed scheduling algorithms perform well. In particular, we find that in the SRA case, the TOAA algorithm performs very close to the lower bound but at the expense of having to reassign time slots whenever a new vehicle arrives. In the URA case, our low-complexity 1-objective algorithm performs better than the others over a wide range of traffic conditions.
机译：在本文中，我们提出了低复杂度的绿色路边基础设施下行链路流量调度算法。在多个路边单元（RSU）部署中，RSU的能量供应可能会有所不同，因此从标准化的最小-最大能量角度出发，希望平衡RSU的使用。本文同时考虑了可拆分RSU分配（SRA）和不可拆分RSU分配（URA）调度。首先导出离线整数线性规划界限，以用于标准化的最小-最大RSU能量使用。然后，我们表明在SRA情况下，对于归一化的最小-最大能量调度，存在多项式复杂度2-逼近。然后，本文提出了几种在线调度算法。第一个是贪婪的在线算法，可以简单地选择RSU，然后分配最小能量的时隙。然后提出归一化的最小-最大算法[2-逼近在线算法（TOAA）]，它是2-逼近边界的在线版本。然后基于潜在功能调度方法引入了两种算法。 1目标算法使用基于归一化最小-最大能量的目标，我们证明了它具有上限最坏情况下的竞争比率性能。 2目标算法使用相同的方法，但也包含了总能量的次级目标。各种实验的结果表明，提出的调度算法性能良好。尤其是，我们发现在SRA情况下，TOAA算法的性能非常接近下限，但代价是每当新车到来时都必须重新分配时隙。在URA的情况下，我们的低复杂度1目标算法在各种交通条件下的性能均优于其他算法。

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