Faculty Publications
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Item Modified QUIC protocol for improved network performance and comparison with QUIC and TCP(Inderscience Publishers, 2019) Kharat, P.; Kulkarni, M.Congestion control mechanism is solely responsible for maintaining the performance of streaming data. However, when there is no congestion, a regular delivery window update is followed as a step by step process. The process can be improved by individual window update along with acknowledgement (ACK) as feedback to the server even in the absence of congestion. To achieve maximum throughput and minimum delay, we have suggested modification in the existing handshaking mechanism of quick UDP internet connections (QUIC) protocol. This paper presents an investigation of QUIC protocol performance and proposes a modified QUIC (ModQUIC): a modification in existing handshaking mechanism of QUIC to reduce control overhead. Chromium server-client model testbed setup results, show that the proposed technique gives stable output and improves performance in terms of overall throughput and delay over QUIC and transmission control protocol (TCP). Performance has been tested for limited (2 Mbps) and sufficient (10 Mbps) link bandwidth in presence of loss. The validation of results has been carried out with the help of linear regression model. The result show a throughput improvement of 35.66% and 51.93% over QUIC and TCP respectively and also the delay is reduced by 3% to 5% over QUIC and TCP. © © 2019 Inderscience Enterprises Ltd.Item CoCoA++: Delay gradient based congestion control for Internet of Things(Elsevier B.V., 2019) Rathod, V.; Jeppu, N.; Sastry, S.; Singala, S.; Tahiliani, M.P.In this paper, we propose a new congestion control algorithm called CoCoA++ to address the issue of network congestion in Internet of Things (IoT). Unlike the existing congestion control mechanisms that operate on instantaneous Round Trip Time (RTT) measurements in IoT, we use delay gradients to get a better measure of network congestion, and implement a probabilistic backoff to deal with congestion. We integrate the delay gradients and the probability backoff factor with Constrained Application Protocol (CoAP). The proposed algorithm is implemented and evaluated using the Cooja network simulator provided by Contiki OS. Subsequently, it is deployed and evaluated in a real testbed by using the FIT/IoT-LAB. We observe that delay gradients give a more accurate measure of congestion and the Retransmission Time Out (RTO) is reduced significantly, thereby leading to less delays and high packet sending rates. CoCoA++ being a minor improvement over the existing algorithm is easy to deploy. © 2019 Elsevier B.V.Item Congestion control performance investigation of ModQUIC protocol using JioFi network: A case study(IOS Press Nieuwe Hemweg 6B Amsterdam 1013 BG, 2020) Kharat, P.; Kulkarni, M.Quick UDP Internet (QUIC) protocol is a transport and application layer solution developed by Google, which is the strong competitor to popular and well established Transmission Control Protocol (TCP). The QUIC protocol is being updated faster resulting into many new versions of the protocol. In this paper, the performance of Modified QUIC (ModQUIC) protocol has been tested with respect to congestion control using India's rapidly growing Internet service provider, the Reliance Jio 4G network (JioFi), which has captured 17% of the market share in a short time. This experimental study investigated ModQUIC protocol performance with congestion control mechanisms CUBIC and Bottleneck Bandwidth Round-trip-propagation-time (BBR) in the JioFi network. The experiment is conducted using a testbed, developed with JioFi and RaspberryPi-3 wireless router along with network emulator: Netem. The ModQUIC performance is verified using test video files stored on Google drive. The performance is tested in packet loss and packet reorder situations using metrics, Throughput and Retransmission Ratio (RTR). We observed that overall ModQUIC/BBR performance is better than ModQUIC/CUBIC in the current Internet. We observed that Reliance Jio is an economical solution for highly populated countries like India, but not a contemporary solution to fulfill India's newly launched digitization project. © 2020 - IOS Press and the authors. All rights reserved.Item ModQUIC protocol performance verification with CUBIC and BBR congestion control mechanisms(Inderscience Publishers, 2021) Kharat, P.; Kulkarni, M.ModQUIC protocol is developed to compete for TCP’s dominance. In this work, ModQUIC protocol performance is evaluated using the BBR protocol and suggested a new decrease factor (?) for CUBIC protocol. Results show that ModQUIC with BBR outperforms ModQUIC with CUBIC and QUIC with CUBIC and BBR. To verify the performance of ModQUIC, a chromium server-client model-based testbed is created. The experiment result shows that throughput, delay and data rate performance of ModQUIC with BBR is superior. The performance is tested for limited and sufficient link bandwidth in presence of loss. The result analysis shows that throughput with ModQUIC/BBR improved by 6.8%, 19.06% and 27.9% over ModQUIC/CUBIC, QUIC/BBR and QUIC/CUBIC respectively whereas, a delay is reduced by 8.02%, 6.56% and 14.38% over ModQUIC/CUBIC, QUIC/BBR and QUIC/CUBIC, respectively. Overall observations conclude that the performance of ModQUIC/BBR is improved and stable as compared to ModQUIC/CUBIC, QUIC/BBR and QUIC/CUBIC. © © 2021 Inderscience Enterprises Ltd.Item Geometric Series based effective RTO estimation Technique for CoCoA(Elsevier B.V., 2022) Rathod, V.; Tahiliani, M.P.Constrained Application Protocol (CoAP) is a standard data transfer protocol for Internet of Things. It has an in-built support for the basic congestion control mechanism that uses fixed Retransmission Time Out (RTO) for every transmission regardless of Round Trip Time (RTT), and performs Binary Exponential Backoff (BEB) when the packets get dropped. CoAP Simple Congestion Control/Advanced (CoCoA) is an enhanced congestion control mechanism over CoAP that adapts RTO based on RTT. It maintains Strong and Weak RTO estimators and uses a Variable Backoff Factor (VBF) instead of BEB when the packets get dropped. CoCoA uses an Exponential Weighted Moving Average (EWMA) to estimate the RTO for the next transmission. The weight used in EWMA is determined on the basis of whether the RTT estimated for the recent transmission was a Strong RTT or Weak RTT. However, the weights used to estimate the RTO are fixed (0.5 for Strong and 0.25 for Weak). These fixed weights lead to slow adaptation of RTO and affect the performance of the IoT applications. In this paper, we highlight the impact of having fixed weights while estimating the RTO in CoCoA. In particular, we show that the RTO in CoCoA fails to adapt quickly when the network conditions are lossless because it uses a fixed value for Strong RTO estimation (0.5). We propose a new algorithm called Geometric Series based effective RTO estimation Technique for CoCoA (GSRTC) to adapt the weight used in EWMA for estimating Strong RTO. GSRTC is integrated into CoCoA and validated against existing mechanisms using the Cooja simulator in Contiki OS and in a real testbed FIT/IoT-LAB. Our results show that GSRTC has lower Flow Completion Times (FCT), lesser retransmissions and better network throughput. © 2022 Elsevier B.V.