https://cis.temple.edu/~wu/research/publications/Publication_files/10_bare_jrnl_compsoc.pdf
6.1 Basic Setting at runs a Linux operating system with E5-2620 CPU, NVIDIA RTX5000 GPU, 128Gb memory, and a 2Tb hard disk. We choose the Social LSTM model to predict the future trajectories of users which can achieve an average accuracy of over 70%. We used
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Distributed_Deep_Multi-Agent_Reinforcement_Learning_for_Cooperative_Edge_Caching_in_Internet-of-Vehicles.pdf
2 Power of background noise -95 Bm Size of requested contents [0.5, 1.5] MB 2.4GHz Intel Xeon E5-2650 processor and 256GB RAM. The main parameters are listed in Table II. For performance comparison, the following four bench-mark caching methods are introduced:
https://cis.temple.edu/~wu/research/publications/Publication_files/Topology-Aware_Scheduling_Framework_for_Microservice_Applications_in_Cloud.pdf
Abstract—Loosely coupled and highly cohesived microservices running in containers are becoming the new paradigm for application development. Compared with monolithic applications, applications built on microservices architecture can be deployed and scaled independently, which promises to simplify software development and operation. However, the dramatic increase in the scale of microservices ...