Abstract

Edge computing and caching of data in the Internet of Things (IoT) has several benefits such as reduced energy consumption by IoT end devices and increased availability of data and Quality of Service (QoS). In typical IoT scenarios, edge nodes (gateways) support several end devices, each of which may produce data in different patterns. In addition, data generated by different types of end devices varies in the application QoS requirements while also widely varying in the data access patterns by IoT services. Managing the data storage resources at edge nodes in such scenarios is a difficult task, especially since the edge nodes themselves may have limited computation capability and storage space. In this paper, we propose a dynamic, differentiated edge cache allocation strategy called NimbleCache that has low computational requirements and performs efficient cache allocation at edge nodes. Based on a Mixture Density Network (MDN), NimbleCache allocates varying portions of the edge cache to traffic of different IoT applications to achieve cache hit ratios very close to the target hit ratio. Simulation results show that NimbleCache achieves good average cache hit ratio with low cache space requirement and small computational overhead.

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