In this paper, we propose an adaptive Go-Back-N (GBN) ARQ protocol over two parallel channels with slow state transition. This proposed protocol sophisticatedly determines the order of priority of the channel usage for sending packets, by using the channel-state feedback information. We exactly analyze the throughput efficiency of the protocol and obtain its closed-form expression under the assumption that the time-varying channel is modeled by a two-state Markov chain, which is characterized by packet error rate and the decay factor. The analytical results and numerical examples show that, for a given round-trip time, the throughput efficiency depends on both the average packet-error rate and the decay factor. Furthermore, it is shown that the throughput efficiency of the proposed protocol is superior to that of the non-adaptive Go-Back-N protocol using the two channels in a fixed order in the case of slow state transition (i.e. the decay factor is positively large).

ECN, as a decisive approach for TCP congestion control, has been proposed for many years. However, its deployment on the Internet is much slower than expected. In this paper, we investigate the state of the deployment of ECN (Explicit Congestion Notification) on the Internet from a different viewpoint. We use the data set of web domains published by Alexa as the hosts to be tested. We negotiate an ECN-Capable and a Not ECN-Capable connections with each host and collect all packets belonging to the connections. By analyzing the header fields of the TCP/IP packets, we dig out the deployment rate, connectivity, variation of round-trip time and time to live between the Not ECN-Capable and ECN-Capable connections as well as the rate of IPv6-Capable web servers. Especially, it is clear that the connectivity is different from the domains (regions on the Internet). We hope that the findings acquired from this study would incentivize ISPs and administrators to enable ECN in their network systems.

In this paper, we investigate the throughput efficiency of the Go-Back-N ARQ protocol on parallel multiple channels with burst errors. We assume that packet errors occur according to a two-state Markov chain on each channel. The effect of the decay factor of the Markov chain on throughput efficiency is evaluated based on the results of numerical analysis.

Multi-hop wireless ad hoc networks suffer from temporary link error due to fading. In order to improve packet transmission reliability and achieve efficient transmission in fading environment, a new cognitive temporary bypassing scheme is proposed based on a cross-layer approach and cognitive behavior of local nodes. The proposed scheme enables neighboring nodes to prepare and create a temporary bypass for lost-packets. This is done by monitoring message packets that include information of the multi-hop route and link-acknowledgement. The scheme also includes an anti-collision function that is necessary to prevent contention among multiple bypassing nodes. Packet success probability with the proposed scheme is studied both by theoretical analysis and time-domain computer simulation for Rayleigh faded single- and multi-hop links. Network simulation using a modified QualNet simulator validate that packet success probability is remarkably improved with the scheme for maximum Doppler frequencies up to 30 Hz.

In this paper, we used the data set of domain names Global Top 1M provided by Alexa to analyze the effectiveness of Fallback in ECN. For the same test server, we first negotiate a connection with Not-ECN-Capable, and then negotiate a connection with ECN-Capable, if the sender does not receive the response to ECN-Capable negotiation from the receiver by the end of retransmission timeout, it will enter the Fallback state, and switch to negotiating a connection with Not-ECN-Capable. By extracting the header fields of the TCP/IP packets, we confirmed that in most regions, connectivity will be slightly improved after Fallback is enabled and Fallback has a positive effect on the total time of the whole access process. Meanwhile, we provided the updated information about the characteristics related to ECN with Fallback in different regions by considering the geographical region distribution of all targeted servers.