Analytical modeling of TCP flow in wireless LANs

Gupta, V. B.; Selvamuthu, Dharmaraja; Gong, Mingwei

doi:10.1016/j.mcm.2010.10.004

Cited by 11 publications

(7 citation statements)

References 16 publications

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“…This demonstrates the efficiency of TCP NewReno over TCP Reno. Gupta et al [20] and Chan and Ramjee [28] also explore the throughput and goodput of the protocol, and we observe that our results are in consistence with them. Next, we explore the TCT of TCP Reno and TCP NewReno and compare the relative goodput of the two protocols in Figure 3.…”

Section: Numerical Illustrationsupporting

confidence: 85%

“…Gupta et al . and Chan and Ramjee also explore the throughput and goodput of the protocol, and we observe that our results are in consistence with them.…”

Section: Numerical Illustrationsupporting

confidence: 78%

“…They integrate the essential features of concurrency, synchronization and a sequenced presentation of complex systems. The technique of GSPN has been successfully used to analyze the performance of TCP Reno [20], bidirectional multichannel IEEE 802.11 MAC protocol [21], and IEEE 802.11 distributed coordinated function of MAC protocol [22]. The GSPN proves to be one of the most appropriate tools to represent complex continuous time Markov chains in a concise way, thereby facilitating a graphical visualization of a multitasking scenario and a dynamic behavior of packet transmission.In this paper, the GSPN model depicting the packet flow following the slow-but-steady variant of TCP NewReno is developed.…”

mentioning

confidence: 99%

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Analytical modeling of Transmission Control Protocol NewReno using Generalized Stochastic Petri Nets

Vinayak

Krishnaswamy

Selvamuthu

2013

Int J Communication

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This paper presents a novel analytical model of Transmission Control Protocol (TCP) using a generalized stochastic Petri net (GSPN). Extensive simulation work has been done for the performance evaluation of TCP NewReno protocol. In view of the limitations of the simulation technique, we present an analytical approach using GSPN. A GSPN is a useful mathematical tool that solves continuous time Markov chains for complex systems and evaluates the stationary behavior. In this paper, we analyze the slow-but-steady variant of TCP NewReno. The model captures the behavioral aspects of the slow start and the congestion avoidance phase together with the fast retransmit and recovery capabilities of TCP NewReno. Performance metrics such as throughput, goodput, and task completion time of the system are obtained. The effect of variation in the model parameters on the performance is studied. The results are validated using the network simulator, and their accuracy is verified by evaluating the confidence interval. The performance of the proposed model is compared with that of TCP Reno. The performance of the proposed model is also compared with one of the previous models. The numerical illustrations and comparison of the proposed technique with simulation validates the accuracy, efficiency, and competence of the GSPN technique. While GSPN modeling for TCP is investigated in depth for the TCP NewReno and TCP Reno variant in this paper, other protocols could be also analyzed similarly. 4186 R. VINAYAK, D. KRISHNASWAMY AND S. DHARMARAJA with TCP Sack. Padhye et al. [8] analyzes the throughput of TCP alone and does not take into consideration the fast recovery mechanism. Padhye et al.[9] presents a model of the TCP Reno. The model captures the essence of TCP's congestion avoidance behavior. The paper analyzes the performance of the protocol in terms of rounds. A simulative approach is followed for the evaluation. However, the paper majorly ignores the effects of fast recovery and fast retransmits. Significantly, the paper concludes that time-outs have a prominent impact on the performance of the protocol. Parves et al.[10] also did the same for TCP NewReno, simulatively. In [11], the slow-but-steady variant of TCP NewReno is analyzed simulatively, using an approach similar to [9]. In [12], the authors develop a continuous time Markov chain model of TCP. However, they ignore the generation of partial acknowledgement (PartACK) and complete acknowledgement (CompACK). They only manipulate the congestion window size, cwnd, and the threshold value, thresh, when the system enters the fast retransmit and recovery (FRR) phase. They ignore the fact that more duplicate acknowledgements (ACKs) arrive, while a segment is in the process of retransmission, and with each incoming duplicate ACK, the window size is incremented by one. The scenario of delayed ACK has not been considered.[13] presents a discrete time Markov chain model for the window size of the TCP and evaluates the throughput and probability of loss for the corresponding window siz...

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Section: Numerical Illustrationsupporting

confidence: 85%

“…Gupta et al . and Chan and Ramjee also explore the throughput and goodput of the protocol, and we observe that our results are in consistence with them.…”

Section: Numerical Illustrationsupporting

confidence: 78%

mentioning

confidence: 99%

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Analytical modeling of Transmission Control Protocol NewReno using Generalized Stochastic Petri Nets

Vinayak

Krishnaswamy

Selvamuthu

2013

Int J Communication

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“…The main TCP standard (RFC 793 [36]) is mandated by ATN/IPS [2] for the reliable transport however no additional TCP variant is mandated or proposed. In our simulations, TCP Reno which is implemented by most operating systems [37], is considered as an example transport protocol with the settings shown in Table 5 in order to show the performance gain of HA-buffering method.…”

Section: Transport and Application Layer Considerationsmentioning

confidence: 99%

Performance Evaluation of Network Mobility Handover over Future Aeronautical Data Link

Ayaz

Hoffmann

Sommer

et al. 2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

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The aviation community is currently working on the standardization of data communication systems for the future air traffic management. In this context, International Civil Aviation Organization (ICAO) has initiated a work on standardization of an IPv6-based aeronautical telecommunications network and on future radio access technologies, respectively. In this paper, we integrate L-Band Digital Aeronautical Communications System Option 1 (L-DACS 1), which is one candidate for future radio access technologies, with realistic IPv6-based network layer functionality and analyze the effect of handover delay to the TCP performance. Realistic Frame Error Rate (FER) values obtained from an L-DACS 1 physical layer simulator, which uses a realistic aeronautical channel model, are used in the simulation experiments. In the first stage, we decreased layer 3 handover latency by removing the Duplicate Address Detection (DAD) procedure for address configuration. In the second stage, we introduced a Home Agent (HA)-buffering method, which is used to buffer the traffic (destined to the mobile node) during handover. Transmission completion time is the primary performance metric in our analysis. With the HA-buffering method, the transmission completion time is reduced by at least 10% for the transmission of 110 kB of information over a wireless link with 31.5 kbit s −1 data rate.

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“…Also, in the existing literature, SRN modeling technique has been used for the performance analysis of various protocols such as IEEE 802.11 DCF, IEEE 802.11 MAC, TCP, and its variant TCP new reno. () This motivated us to use SRN as a modeling tool. Although SRNs are opted as modeling technique in the paper, rewards are not considered in the model.…”

Section: Introductionmentioning

confidence: 99%

Analytical modeling of RLC protocol of LTE using stochastic reward nets

Gupta

2019

Int J Communication

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Summary RLC (radio link control) is a layer 2 protocol of LTE used for reliable transmission of data packets in communication networks. This protocol operates in three modes, namely, transparent mode (TM), unacknowledged mode (UM), and acknowledged mode (AM). In this paper, analytical models are developed to study the flow of data streams in all the three modes of the RLC protocol. Stochastic reward net (SRN) is adopted as a modeling technique as it easily captures various aspects of this protocol such as protocol data unit (PDU) transmission, assigning header with each PDU, requesting for status report, retransmission of PDU(s), management of PDU losses due to expiration of various timers (quick repeat timer, poll timer, status timer). Throughput, average delay and probability of PDU loss are evaluated as the performance measures using the SRN models. Based on these performance measures, a comparative study between the UM and AM is presented which depicts that the modes are performing their key functions decently. Analytical results are also validated via simulation.

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Analytical modeling of TCP flow in wireless LANs

Cited by 11 publications

References 16 publications

Analytical modeling of Transmission Control Protocol NewReno using Generalized Stochastic Petri Nets

Analytical modeling of Transmission Control Protocol NewReno using Generalized Stochastic Petri Nets

Performance Evaluation of Network Mobility Handover over Future Aeronautical Data Link

Analytical modeling of RLC protocol of LTE using stochastic reward nets

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