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Energy efficient resource allocation in mobile ad hoc computational grids

机译:移动自组织计算网格中的节能资源分配

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This paper addresses the problem of energy efficient resource allocation to interdependent tasks in mobile ad hoc computational grids. The interdependent tasks may exchange large quantity of data and consume the energy proportional to amount of data exchanged among the tasks. If tasks wouldn't be allocated effectively, then there can be a significant increase in the energy consumption and communication cost. The increased energy consumption limit the life time of a node and may result in a power failure which not only affects the task executing on a node but also affects other tasks in various ways. In addition, the mobile nodes within a grid are battery driven and thus have a limited power that should be utilized effectively. In this paper, we propose a hybrid power-based resource allocation scheme to reduce the energy consumption and communication cost among the interdependent tasks. The basic idea is to exploit the dependency and task types and allocate interdependent tasks to nodes accessible at a minimum transmission power level. We also propose a power-based algorithm to find a group of closest nodes to allocate a set of interdependent tasks. Compared to the traditional algorithms, the complexity of proposed algorithm depends on the number of transmission power levels rather than the number of nodes within a grid.
机译:本文解决了在移动自组织计算网格中将能源高效的资源分配给相互依赖的任务的问题。相互依赖的任务可能交换大量数据,并消耗与任务之间交换的数据量成比例的能量。如果不能有效地分配任务,那么能耗和通信成本可能会大大增加。增加的能量消耗限制了节点的寿命,并且可能导致电源故障,该电源故障不仅影响节点上执行的任务,而且还以各种方式影响其他任务。另外,网格内的移动节点由电池驱动,因此具有应有效利用的有限功率。在本文中,我们提出了一种基于混合功率的资源分配方案,以减少相互依赖的任务之间的能耗和通信成本。基本思想是利用依存关系和任务类型,并将相互依存的任务分配给以最小传输功率级别可访问的节点。我们还提出了一种基于功率的算法,以找到一组最接近的节点来分配一组相互依赖的任务。与传统算法相比,所提出算法的复杂度取决于传输功率电平的数量,而不是网格内节点的数量。

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