A Constraint-based Approach to Edge Resource Allocation for Complex Event Processing
A Constraint-based Approach to Edge Resource Allocation for Complex Event Processing
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DOI：
10.1109/wiiat50758.2020.00079
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发表时间：
2020-12
期刊：
影响因子：
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通讯作者：
Bowen Wei;Donghui Lin;Shiyao Ding
中科院分区：
文献类型：
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作者：
Bowen Wei;Donghui Lin;Shiyao Ding
随着物联网(IoT)的发展，对事件驱动的服务调用的需求不断增加，从流传感器数据中识别物理世界中的事件模式的复杂事件处理(CEP)技术引起了人们的兴趣。为了以较低的延迟处理数据，边缘计算在物联网中得到了广泛的应用，但在这样的分布式计算系统上实现事件识别面临着许多挑战。本文研究了复杂事件处理中的边缘资源分配问题，得到了一种能够在最短时间内检测到流数据中包含的所有复杂事件的分配方案。由于事件模式的复杂组合和问题的规模庞大，使得寻找最优解成为一个困难的问题，我们将问题描述为利用资源和事件的特征的基于约束的优化问题(COP)。然后，我们提出了一种CEP-Efficient启发式算法(CEED)来有效地确定解。实验结果表明，与基线方法相比，该算法可以大大减少问题求解所需的时间，同时获得了较好的逼近性能。
With the development of Internet of Things (IoT), the demand for event-driven service invocation continues to increase, which is attracting interest in the techniques of complex event processing (CEP) for recognizing event patterns in the physical world from stream sensor data. To process data with lower delay, edge computing is widely used in IoT, but there are many challenges in implementing event recognition on such distributed computing systems. This paper studies an edge resource allocation problem for complex event processing; the result is an allocation scheme that allows all complex events contained in stream data to be detected in minimal time. As the intricate composition of event patterns and the large scale of the problem makes finding an optimal solution a hard problem, we formulate the problem as a constraint-based optimization problem (COP) using features of resources and events. We then propose a CEP-efficient heuristic algorithm (CEED) for efficient solution determination. Experiments conform that our algorithm can greatly reduce the time needed for problem solving while yielding good approximation performance relative to the baseline approach.