Content Caching Based on Popularity and Priority of Content Using seq2seq LSTM in ICN

Efficient content caching is essential to address the explosive growth of multimedia contents and most works on content cache placement have been proposed mainly based on the popularity of content. Since the priority of content is also an important attribute of content, we consider both popularity and priority of content together for content caching in information-centric networking (ICN). We define weighted delivery cost of content as content delivery cost multiplied by a weighted sum of popularity and priority of the content. Then, we formulate optimized content cache placement problem to minimize weighted content delivery cost for all content requests in a hierarchical network architecture with multi-access edge computing (MEC) and software-defined networking (SDN) controller. Average quality of experience (QoE), i.e., average content delivery cost, for contents with each priority is imposed as constraint. The number of content requests is predicted based on seq2seq long short-term memory (LSTM) model in MECs and this is delivered to SDN controller. Then, SDN controller obtains predicted popularity of contents and decides content placement in MECs and core routers by solving the content cache placement optimization problem based on binary particle swarm optimization (BPSO). Performance of the proposed content caching scheme is compared with conventional popularity-based, popularity prediction-based, and popularity prediction-based optimization schemes, from the aspect of QoE satisfaction ratio, average cost, weighted average cost, total cost, and weighted total cost. Numerical results show the effectiveness of the proposed scheme at caching content with high priority efficiently, at the expense of caching content with low priority.

Automated summary

Efficient content caching in information-centric networking (ICN) is studied by considering both popularity and priority of content. A weighted delivery cost is defined to measure the content delivery cost, and an optimized content cache placement problem is formulated to minimize the weighted content delivery cost. The proposed scheme utilizes a hierarchical network architecture with multi-access edge computing (MEC) and software-defined networking (SDN) controller, and predicts the content requests using a seq2seq long short-term memory (LSTM) model in MECs.