Intelligent Fusion Technology, Inc.

Qi Zhao

Genshe Chen

Yi Li

Khanh D Pham

Xin Tian

Nichole Sullivan

Li Li

Huong Ngoc Dang

Mingjie Feng

An edge network computing system includes: a plurality of terminal devices; a plurality of edge servers connected to the terminal device through an access network; and a plurality of cloud servers connected to the plurality of edge servers through a core network. Each edge server is configured to: receive a plurality of computing tasks originated from one of the plurality of terminal devices; use a deep Q-learning neural network (DQN) with experience replay to select one of the plurality of could servers to offload a portion of the plurality of computing tasks; and send the portion of the plurality of computing tasks to the selected cloud server and forward results of the portion of the plurality of computing tasks received from the selected cloud server to the originating terminal device.

Edge network computing system with deep reinforcement learning based task scheduling

A system includes: a named data networking (NDN) based Spark distributed computing network including a Spark distributed computing network including a master computer node and a plurality of slave computer nodes, and a named data networking (NDN) protocol installed on the Spark distributed computing network, and a coded distributed computing (CDC) target recognition model deployed on the NDN-based Spark distributed computing network. The NDN-based Spark distributed computing network is configured to: receive one or more batches of input images; generate a parity image from each batch of the input images; predict a label for each image of the batch of the input images; process the generated parity image; upon a label prediction of one image of the batch of the input images being unavailable, reconstruct the unavailable label prediction; and classify labels for the input images.

Methods and systems of resilient mobile distributed computing

Various embodiments provide a method for transmission control protocol (TCP) packet transmission. The method includes receiving, by a receiver performance enhancing node (PEN), one or more TCP packets each with a timestamp and a sequence number from a sender PEN; evaluating a packet delivery time from the sender PEN to the receiver PEN; detecting whether any TCP packet is lost based on a packet sequence and determining a delay shaping time for each TCP packet based on a maximum number of retransmissions and an evaluated delivery time distribution; in response to a lost TCP packet being detected, determining whether the lost TCP packet needs to be retransmitted based on the maximum number of retransmissions; and in response to the determined delay shaping time, determining when a received TCP packet needs to be forwarded based on the determined delay shaping time and a timestamp associated with the received TCP packet.

Method, device, and system for TCP packet transmission over satellite communication network

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Germantown, MD, United States of America

Qi Zhao