In multihop wireless networks, reliable data transfer is one of the most difficult tasks. When transmission control protocol (TCP) operates in multihop wireless networks, the performance of TCP reduces drastically. TCP retransmission timeouts (RTOs) related to non-congestion events such as spurious and random packet losses have been reported as one of the main problems in the performance degradation of TCP in multihop wireless networks. The RTOs triggered by random packet losses due to transmission errors lead to unnecessary reduction of TCP congestion window size, and the spurious RTOs due to sudden delay of packets on the network paths often cause unnecessary retransmissions as well as reduction of congestion window size. Existing solutions for detecting noncongestion RTOs have no mechanism to differentiate the spurious RTOs from RTOs caused by random packet loss. In this paper, we introduce an efficient algorithm called non-congestion retransmission timeouts (TCP NRT) which is capable of recovering packets after RTOs by reducing unnecessary retransmissions and needless reduction of congestion window size in order to improve the performance of TCP in multihop wireless networks. TCP NRT consists of three key components: NRT-detection, NRT-differentiation, and NRT-reaction. We implemented the algorithm in Qualnet network simulator and compared its performance to existing TCP versions. Results from the experiments show that our algorithm achieves significant performance improvement in terms of throughput and accuracy. Also, the results showed that our algorithm, TCP NRT, maintains a fair and friendly behavior compared to the most widely deployed TCP, NewReno.
In this article, we propose a unified solution called Transmission Control Protocol (TCP) for Non-Congestion Events (TCP NCE), to overcome the performance degradation of TCP due to non-congestion events over wireless networks. TCP NCE is capable to reduce the unnecessary reduction of congestion window size and retransmissions caused by non-congestion events such as random loss and packet reordering. TCP NCE consists of three schemes. Detection of non-congestion events (NCE-Detection), Differentiation of non-congestion events (NCE-Differentiation) and Reaction to non-congestion events (NCE-Reaction). For NCE-Detection, we compute the queue length of the bottleneck link using TCP timestamp and for NCE-Differentiation, we utilize the flightsize information of the network with a dynamic delay threshold value. We introduce a new retransmission algorithm called 'Retransmission Delay' for NCE-Reaction which guides the TCP sender to react to non-congestion events by properly triggering the congestion control mechanism. According to the extensive simulation results using qualnet network simulator, TCP NCE acheives more than 70% throughput gain over TCP CERL and more than 95% throughput improvement as compared to TCP NewReno, TCP PR, RR TCP, TCP Veno, and TCP DOOR when the network coexisted with congestion and non-congestion events. Also, we compared the accuracy and fairness of TCP NCE and the result shows significant improvement over existing algorithms in wireless networks.
SUMMARYWhen TCP operates in multi-hop wireless networks, it suffers from severe performance degradation. This is because TCP reacts to wireless packet losses by unnecessarily decreasing its sending rate. Although previous loss differentiation algorithms (LDAs) can identify some of the packet losses due to wireless transmission errors as wireless losses, their accuracy is not high as much as we expect, and these schemes cannot avoid sacrificing the accuracy of congestion loss discrimination by misclassifying congestion losses as wireless losses. In this paper, we suggest a new end-to-end loss differentiation scheme which has high accuracy in both wireless loss discrimination and congestion loss discrimination. Our scheme estimates the rate of queue usage using information available to TCP. If the estimated queue usage is larger than 50% when a packet is lost, our scheme diagnoses the packet loss as congestion losses. Otherwise, it diagnoses the packet loss as wireless losses. Because the estimated queue usage is highly correlated to congestion, our scheme has an advantage to more exactly identify packet losses related to congestion and those unrelated to congestion. Through extensive simulations, we compare and evaluate our scheme with previous LDAs in terms of correlation, accuracy, and stability. And the results show that our scheme has the highest accuracy as well as its accuracy is more reliable than the other LDAs. key words: end-to-end loss differentiation, multi-hop wireless networks, TCP
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