Gourish Goudar

@nmit.ac.in

Assistant Professor, Dept. of Artificial Intelligence and Data Science
NITTE Meenakhsi Institute of Technology, Bengaluru



                    

https://researchid.co/gourish

EDUCATION

BE in Computer Science and Engineering, SJCE Mysore, 2011.

ME in Computer Science, BITS Pilani, 2015.

PhD in Computer Science, BITS Pilani, 2022.

RESEARCH INTERESTS

Future Networks, Computer Vision (Intelligent Transportation Systems), Machine Learning and Mathematical Modelling.

6

Scopus Publications

35

Scholar Citations

3

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Optimizing Bulk Transfer Size and Scheduling for Efficient Buffer Management in Mobile Opportunistic Networks
    Gourish Goudar and Suvadip Batabyal

    Institute of Electrical and Electronics Engineers (IEEE)
    Mobile Opportunistic Networks (MONs) are characterized by intermittent connectivity with long isolation period, and nodes following redundant transmissions for reliable message delivery. This often leads to unnecessary buffer occupancy, preventing new messages from getting replicated due to small contact duration and low bandwidth, or leading to packet drop under constrained buffer. Although attempts have been made to mitigate buffer congestion, the existing schemes are localized, are slow to react, or are specific to a routing scheme. Moreover, they rely on message exchanges to obtain buffer state/occupancy, thereby incurring additional overhead. In this paper, we first develop a generalized probabilistic forwarding model where the forwarding probability denotes the likelihood of a message to get forwarded to the encountered node. Based on the forwarding probability, we develop a congestion indicator and predict the point of congestion using the Kalman filter. Using this, a node can decide the optimal number and the exact set of messages to replicate, which leads to an optimal performance with minimal packet drop and overhead. Simulation results using a synthetic mobility model and a real-life mobility trace show that the proposed scheme outperforms the existing schemes.

  • Offloading in 5G Cellular Networks: Unexplored Strategies
    Gourish Goudar and Sanket Mishra

    IEEE
    With the escalating demands for data-intensive content, and the convergence of mobile and connected devices, there is a growing requirement of high bandwidth speeds in multimedia applications. 5G will be a game-changer in the business operations and in providing a engaging customer experience. The 5G vision promises to deliver high-speed downloads with low latency. Managing the exponential growth in data traffic is one of the mobile operator's most challenging issues in 5G networks. Mobile data offloading is a potential and low-cost method for alleviating cellular network congestion. To make this conceivable, we need a new paradigm for hybrid networks that capitalizes on the presence of several alternative communication ways. This entails significant modifications in how data is handled, thereby influencing the behavior of network protocols. This paper presents various techniques for data offloading in cellular 5G networks, discussing the requirements, advantages, and limitations. The research work in this paper provides a detailed presentation of the gaps identified in 5G networks data offloading techniques, the requirements and challenges, and a way forward to solve the challenges, including the most recent technological advancements such as deep learning, edge computing, WiFi-6, social networks and software-defined networks (considering the heterogeneity aspect of the network).

  • To forward or not to forward: Optimal message scheduling in mobile opportunistic networks
    Gourish Goudar, Suvadip Batabyal, and Ozgur Ercetin

    IEEE
    Mobile opportunistic networks (MONs) are characterized by frequently changing network topology that rely on multi-copy transmission schemes to ensure the delivery of messages. However, the limited buffer capacity of mobile nodes leads to buffer overflow and head-of-line blocking. Head-of-line-blocking is caused due to short contact duration, which causes the older messages to be replicated at a faster rate than the newer messages waiting behind them. This unfair replication decreases the message delivery ratio and increases the average delivery delay. For implementation, we categorize a message as new or old and calculate the necessary maximum number of replicas required to deliver a message to the destination. If the instantaneous number of replicas in the network is less than this number, we schedule a message for replication and vice-versa. We demonstrate that our proposed scheme achieves a delivery ratio comparable to a utility-based optimal message drop algorithm with significantly lower overhead.

  • Point of Congestion in Large Buffer Mobile Opportunistic Networks
    Gourish Goudar and Suvadip Batabyal

    Institute of Electrical and Electronics Engineers (IEEE)
    Congestion detection and management are difficult to realize in Mobile Opportunistic Networks (MONs) due to the lack of end-to-end connectivity, global information, absence of ACKs/NACK messages. One of the simplest means of detecting congestion in any network, primarily in the intermediate nodes, is buffer overflow leading to packet drop. Although researchers in this area have used this phenomenon to detect congestion, this is not always true for a MON, especially under large buffers. We show that in MONs with large buffers, there exists a critical buffer occupancy beyond which congestion sets in, and network performance degrades even though the buffer may not be full. To study this behavior, we develop an analytical model based on forwarding probability by considering the nodes to have a large buffer size and finite bandwidth. Using Epidemic forwarding as the underlying routing protocol, the analytical model is used to detect the exact buffer occupancy that leads to congestion. The theoretical results have been compared with the simulation results to prove the correctness of the model.

  • A modified balls-into-bins model for expected buffer occupancy in mobile opportunistic networks
    Gourish Goudar and Suvadip Batabyal

    IEEE
    Due to the unavailability of an end-to-end path between the source and the destination, nodes in Mobile Opportunistic Networks (MON) follow a replication based strategy for message delivery. Such replications occur in bulks during intermittent and very short contact events, which often lead to buffer congestion in the relay nodes, thereby affecting the network performance. Older messages (those which have already been delivered to the destination) also tend to stay in the network for a longer time period hindering the spread of newly generated messages. Earlier works have considered buffer management techniques through local information exchange, which leads to overhead. In this work, an expression for the expected buffer occupancy under a given network scenario is obtained using the notion of a classical balls-into-bins problem. Thereafter, an estimator to estimate the buffer occupancy is designed, which can be directly used in buffer management algorithms without local information exchange. We compare the theoretical model, with estimated and simulated results, to prove the correctness of the model.

  • Characterizing and estimating bulk transfer size in mobile opportunistic network
    Gourish Goudar and Suvadip Batabyal

    IEEE
    In Mobile Opportunistic Networks (MON), messages are transferred in bulk during a contact event. Such bulk transfers may cause a sudden increase in buffer occupancy, which may lead to congestion, and hence impact network performance. Apriori information of bulk transfer size distribution may help in taking proactive measures to prevent the onset of congestion. Therefore, we study the characteristic of bulk transfer size (BTS) and its impact on buffer occupancy. For this, we simulated the network using synthetic and real-life mobility traces and found that the aggregate inter-contact time (ICT) and aggregate BTS can be well approximated by the lognormal distribution. Further, we devised an estimator for mean BTS, which can be used by a receiving node to decide whether to accept or reject the bulk in order to avoid buffer overflow. We also found that an increase in expected ICT leads to an increase in expected BTS, which is confirmed using a simple linear regression model.

RECENT SCHOLAR PUBLICATIONS

  • Offloading in 5G Cellular Networks: Unexplored Strategies
    G Goudar, S Mishra
    2022 IEEE Future Networks World Forum (FNWF), 474-479 2022

  • Estimating Buffer Occupancy sans Message Exchange in Mobile Opportunistic Networks
    G Goudar, S Batabyal
    IEEE Networking Letters 4 (2), 73-77 2022

  • Designing Proactive Buffer Management Schemes in Mobile Opportunistic Networks
    G Goudar
    Pilani 2022

  • To forward or not to forward: optimal message scheduling in mobile opportunistic networks
    G Goudar, S Batabyal, O Ercetin
    2021 IEEE 46th Conference on Local Computer Networks (LCN), 201-208 2021

  • Optimizing bulk transfer size and scheduling for efficient buffer management in mobile opportunistic networks
    G Goudar, S Batabyal
    IEEE Transactions on Mobile Computing 21 (12), 4471 - 4487 2021

  • Point of congestion in large buffer mobile opportunistic networks
    G Goudar, S Batabyal
    IEEE Communications Letters 24 (7), 1586-1590 2020

  • A modified balls-into-bins model for expected buffer occupancy in mobile opportunistic networks
    G Goudar, S Batabyal
    2019 15th International Wireless Communications & Mobile Computing 2019

  • Characterizing and estimating bulk transfer size in mobile opportunistic network
    G Goudar, S Batabyal
    2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 1-5 2019

MOST CITED SCHOLAR PUBLICATIONS

  • Point of congestion in large buffer mobile opportunistic networks
    G Goudar, S Batabyal
    IEEE Communications Letters 24 (7), 1586-1590 2020
    Citations: 15

  • Optimizing bulk transfer size and scheduling for efficient buffer management in mobile opportunistic networks
    G Goudar, S Batabyal
    IEEE Transactions on Mobile Computing 21 (12), 4471 - 4487 2021
    Citations: 10

  • Estimating Buffer Occupancy sans Message Exchange in Mobile Opportunistic Networks
    G Goudar, S Batabyal
    IEEE Networking Letters 4 (2), 73-77 2022
    Citations: 5

  • A modified balls-into-bins model for expected buffer occupancy in mobile opportunistic networks
    G Goudar, S Batabyal
    2019 15th International Wireless Communications & Mobile Computing 2019
    Citations: 3

  • Characterizing and estimating bulk transfer size in mobile opportunistic network
    G Goudar, S Batabyal
    2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 1-5 2019
    Citations: 2