Mobile Crowdsensing Systems (MCSs) present a flexible and economical alternative to traditional infrastructure based large-scale sensing through the recruitment of personal mobile devices as data sources. As this becomes a popular sensing approach it will impact the capacity of typical centralized cellular communication infrastructures widely adopted by MCS applications and any costs accrued. Following the trend towards edge processing, Mobile Edge Caching offloads data and services from the system core to reduce service latency and bandwidth occupation. However, in the MCS case the edge device is owned by the general public and are therefore more vulnerable to data or calculation manipulation by the user. We now better understand sensor data and user trustworthiness but have no way to determine which of devices could also be trusted, i.e. act as a credible caching device. In this article, we treat the quality of sensing data reported by each user as an indication of their possibility of providing credible caching services. Specifically, we conduct a comprehensive study of the data quality problem with regards to cache-enabled MCSs, and develop an incentivization method to encourage users to actively provide high quality data. That is, quality-aware behavior evaluation is core to the credible caching device selection process. Results of extensive simulations based on real-world data verify the effectiveness of our design. We also highlight several promising research directions that remain open for further elaborations.

In order to achieve optimization control of complex network topology connection and to identify the network topology which with the greatest network connection gain, this paper proposes the network topology connection optimization control algorithm based on network efficiency and average connectivity. The algorithm uses network efficiency to characterize network connectivity gains, uses average network connectivity to characterize network connection costs, and presents its calculational optimization algorithm. When a network has the small-world characteristics, and mn  , the time complexity of the algorithm can reach O (n2). Experimental results show that: the proposed algorithm can increase the connection gain and reduce connection costs.

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Igneous rocks have the characteristics of “diversification of eruption mode, diversification of lithologic origin and multiple changes of mineral assemblages ", so it is difficult to identify fine. This study is based on a real case study of igneous carboniferous reservoir in Jinlong 10 block at Junggar basin. The distinguish of the reservoir-developed rocks are catalyzed to basalt, andesite, dacite, granite, tuff and volcanic breccia rock, based on a combination of core and thin sheet analysis data. Based on the characteristics of log response of different lithology, the basic basalt, neutral andesite and acidic granite are quickly distinguished by N-DP intersection map method, and the idea of “step by step stripping” is adopted in the interval, and tuff and volcanic breccia are identified by intersection map method. The results of lithology identification and the conclusion of core sheet analysis have a high degree of anastomosis, which effectively improves the accuracy of lithology identification.

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