Redefining Node Centrality for Task Allocation in Mobile CrowdSensing Platforms
Redefining Node Centrality for Task Allocation in Mobile CrowdSensing Platforms
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DOI：
10.1109/smartcomp.2019.00069
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发表时间：
2019-06
期刊：
影响因子：
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通讯作者：
Christine Bassem
中科院分区：
文献类型：
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作者：
Christine Bassem
随着移动的CrowdSensing的最新发展，出现了一个有趣的时间图模型，其中节点权重随着时间的推移而演变，根据移动领域的时空任务的可用性。分析和理解这些类型的图，即权重演化时间（WET）图，是优化任务分配在这样的crowdsensing平台的关键。在本文中，我们正式定义了WET图和相应的路由问题，其中的路由的目标是最大化收集的回报访问的顶点之间的图遍历。通过将WET图建模为时间有序图，定义了高效的最优路由算法，并对其进行了理论分析。此外，我们提出了一种新的节点中心性的措施，即覆盖中心性，抓住了流行的WET图的各个节点，我们将在一个在线的众测任务分配机制，以增加任务覆盖。最后，我们评估了这种新的中心性措施在不同类型的图的功效，当与其他中心性措施相比，并评估其对在线移动的crowdsensing平台的任务覆盖的影响。
With the recent developments in Mobile CrowdSensing, an interesting model of temporal graphs has emerged, in which node weights evolve over time, according to the availability of spatio-temporal tasks on the mobility field. The analysis and understanding of these types of graphs, namely Weight Evolving Temporal (WET) graphs, is critical for optimizing task allocation in such crowdsensing platforms. In this paper, we formally define WET graphs and their corresponding routing problem, in which the objective of the routing is to maximize the reward collected from vertices visited amid the graph traversal. By modeling a WET graph as a time-ordered graph, we define efficient and optimal routing algorithms, and theoretically analyze them. Moreover, we present a novel node centrality measure, namely Coverage Centrality, that captures the popularity of various nodes of the WET graph, and which we incorporate in an online crowdsensing task allocation mechanism to increase task coverage. Finally, we evaluate the efficacy of this novel centrality measure on different types of graphs, when compared to other centrality measures, and evaluate its effect on task coverage in online mobile crowdsensing platforms.