• An efficient indexing model for the fog layer of industrial Internet of Things.

      Miao, Dejun; Liu, Lu; Xu, Rongyan; Panneerselvam, John; Wu, Yan; Xu, Wei; Yangzhou University; University of Derby; Jiangsu University; Zhenjiang University (IEEE, 2018-01-30)
      Fog Computing is gaining popularity and is being increasingly deployed in various latency-sensitive application domains including industrial IoTs. However, efficient discovery of services is one of the prevailing issues in the fog nodes of indus-trial IoTs which restrain their efficiencies in availing appropriate services to the clients. To address this issue, this paper proposes a novel effi-cient multilevel index model based on equivalence relation, named the DM-index model, for service maintenance and retrieval in the fog layer of industrial IoTs to eliminate redundancy, narrow the search space, reduce both the traversed number of services and retrieval time, ultimately to improve the service discovery efficiency. The efficiency of the proposed index model has been verified theoretically and evaluated experimentally, which demonstrates that the proposed model is effective in achieving much better service discovery and retrieval performance than the sequential and inverted index models.