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Energy-efficient dispatching policy for virus scanning as a service under N-version protection

机译:在N-Version Protection下,病毒扫描的节能调度策略

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We investigate energy-efficient dispatching policy for virus scanning as service (VSaaS) under N-version protection. Under N-version protection, one would dispatch a file-scan request to multiple service engines, in order to reduce the missed detection error cost. However, this also increases the energy consumption of service engines and the queueing delay. To manage this tradeoff, we aim to reduce the energy consumption of service engines and the missed detection error cost, while achieving low delay for VSaaS. We first define a penalty function as the combination of the energy consumption and the missed detection error cost. We then formulate the file-scan dispatching policy as a constrained optimization problem under the framework of Lyapunov optimization. Using the Lyapunov-drift-penalty function, we propose an online algorithm, which achieves the penalty function arbitrarily close to the minimum by increasing the control variable but at the cost of increasing the queue length. Simulation results indicate that the proposed algorithm is flexible to provide N-version protection. Using the algorithm, the cloud operator can dynamically tune the control variable in order to reduce the energy consumption and the missed detection error cost, while maintaining the queue stability.
机译:我们调查在N-Version Protection下作为服务(VSAAS)的病毒扫描的节能调度策略。在N-Version Protection下,可以将文件扫描请求分配给多个服务引擎,以减少错过的检测错误成本。然而,这也增加了服务发动机的能量消耗和排队延迟。为了管理这个权衡,我们的目标是降低服务发动机的能耗和错过的检测误差成本,同时为VSAAS实现低延迟。我们首先将惩罚功能定义为能量消耗的组合和错过的检测误差成本。然后,我们将文件扫描调度策略作为Lyapunov优化框架下的约束优化问题。使用Lyapunov-Drive-Dency函数,我们提出了一种在线算法,通过增加控制变量但以增加队列长度的成本,通过增加控制变量来任意接近最小的刑罚函数。仿真结果表明,所提出的算法提供了N-Version保护的灵活性。使用算法,云运算符可以动态调整控制变量,以降低能量消耗和未错过的检测误差成本,同时保持队列稳定性。

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