A MPTCP Scheduler for Web Transfer

Multipath TCP(MPTCP)is the most significant extension of TCP that enables transmission via multiple paths concurrently to improve the resource usage and throughput of long flows.However,due to the concurrent multiple transfer(CMT)in short flow trans-mission,the congestion window(cwnd)of each MPTCP subflow is too small and it may lead to timeout when a single lost packet cannot be recovered through fast retransmission.As a result,MPTCP has even worse performance for short flows compared to regular TCP.In this paper,we take the first step to analyze the main reason why MPTCP has the diminished performance for short flows,and then we propose M PTCP-SF,which dynamically adjusts the number of subflows for each flow.In particular,MP TCP-SF firstly analyzes the distribution characteristics of the web objects to extract two thresholds to be used for classifying each flow.After eceiving each new ACK,M PTCP-SF periodically counts the data being sent based on per-flow and uses the threshold to classify the we blows.Finally,MPTCP-SF dynamically switches path scheduling model for different classification flows.We conduct extensive experiments in NS3 to evaluate its efficiency.Our evaluation proves that MPTCP-SF decreases the completion time of short flows by over 42.64% com-pared to MPTCP,and the throughput achieved by MPTCP-SF in transmitting long flows is about 11.11%higher than that of MPTCP in a WLAN/LTE wireless network.The results successfully validate the improved performance of MPTCP-SF.

Scheduling optimization for upstream dataflows in edge computing

Edge computing can alleviate the problem of insufficient computational resources for the user equipment,improve the network processing environment,and promote the user experience.Edge computing is well known as a prospective method for the development of the Internet of Things(IoT).However,with the development of smart terminals,much more time is required for scheduling the terminal high-intensity upstream dataflow in the edge server than for scheduling that in the downstream dataflow.In this paper,we study the scheduling strategy for upstream dataflows in edge computing networks and introduce a three-tier edge computing network architecture.We propose a Time-Slicing Self-Adaptive Scheduling(TSAS)algorithm based on the hierarchical queue,which can reduce the queuing delay of the dataflow,improve the timeliness of dataflow processing and achieve an efficient and reasonable performance of dataflow scheduling.The experimental results show that the TSAS algorithm can reduce latency,minimize energy consumption,and increase system throughput.