Qualification: 
Ph.D, M.Tech, BE
mk_panda@cb.amrita.edu

Dr. Manoj Kumar Panda currently serves as an Assistant Professor (SG) at the Department of Electronics and Communication Engineering, School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore campus.

Dr. Panda received Ph. D. in Electrical Communication Engineering from the Indian Institute of Science Bangalore and M. Tech. in Electrical Engineering from the Indian Institute of Technology, Kanpur. His research interest lies in the area of modeling, analysis and optimization of computer communication networks, vehicular networks, cloud-based robotic networks, and transportation networks. He is also interested in the multi-sensor fusion and multi-object tracking problems in the aforementioned networks,

Dr. Panda has published 17 journal articles in top-ranked IEEE transactions, Elsevier and Springer journals and 27 conference papers in the areas of Wireless Networks and Intelligent Transportation Systems. Two of his conference papers have won the ‘Best Paper’ and the ‘Best Student Paper’ awards. His RG score is 20.4 which is higher than 72.5% of all ResearchGate members. According to Google Scholar, his h-index is 11.

Dr. Panda joined the Department of Electronics and Communication Engineering, School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, in December 2016. Prior to joining Amrita, he has held a four-year Research Fellow position at the Centre for Advanced Internet Architecture, Swinburne University of Technology, Australia, where he was involved in the VicRoads-funded project 'Integrated Network Management' and was responsible for developing the Traffic Queue Estimator. Prior to that, he has held post-doctoral positions at INRIA, Sophia Antipolis, France, for one year, and at Telecom SudParis, France, for two years. Prior to commencing his Ph.D., he worked as a Software Engineer in the Applied Research Group, Satyam Computer Services Ltd., Bangalore, for about two years where he won the 'Star Performer' award. He was selected for a three-month Fellowship at the Institute of Pure and Applied Mathematics (IPAM), University of California Los Angeles, for its Fall 2015 Program on “New Directions in Mathematical Approaches for Traffic Flow Management”.

Dr. Panda has co-supervised four Ph. D. students at Swinburne University of Technology, Australia, and has supervised and mentored several masters and bachelor’s students. He is a regular reviewer of several leading journals in the area of computer and communication networks, including IEEE/ACM Transactions on Networking, IEEE Transactions on Mobile Computing, IEEE Transactions on Vehicular Technology, IEEE Vehicular Technology Magazine, IEEE Communication Letters, IEEE Access, IET Communications, etc.

Education

  • January 2005 - March 2010: Ph. D. Wireless Networks
    Indian Institute of Science, Bangalore
  • July 2001 - March 2003: M. Tech. / ME /MS Electrical Engineering (Data & Optical Networks)
    Indian Institute of Technology Kanpur 
    Qualified GATE – 2001, AIR 210 in ECE (MTech Scholarship at IIT Kanpur)
     

Professional Appointments

Year Affiliation
December 2016 - Present Assistant Professor (Selection Grade), Amrita Vishwa Vidyapeetham
Domain: Teaching and Research 
March 2013 - November 2017 Postdoctoral Research Fellow (Level B4), Swinburne University of Technology, Australia
Domain: Research and Casual Teaching
February 2012-December 2012 R & D Engineer (Postdoctoral), Telecom SudParis, France 
Domain: Research
February 2011 - December 2011 Postdoctoral Fellow, INRIA, Sophia Antipolis, France
Domain: Research 
April 2010 - December 2010 Research Engineer (Postdoctoral), Telecom SudParis, France
Domain: Research
April 2003 - December 2004 Software Engineer (Post-MTech), Satyam Computer Services Limited Bangalore (Applied Research Group)
Domain: Research and Projects

Academic Responsibilities

Sl. No. Position Class/Batch Responsibility
1. Research Coordinator ECE Department (Jul 2017 – to date) Represent the department in research discussions for external collaborations; Maintain the research data of the department
2. Class Adviser ECE B / 2017–2021 Various
3. Chief Mentor (M. Tech. Course) Estimation and Detection Theory (2016 – 2017) Prepare periodical and end-semester question papers with answer keys, monitor the progress of teaching for all classes
4. Mentor (M. Tech. Course) Vehicular Networks and Communication (2016 – 2017) -do-
5. Mentor (M. Tech. Course) Data Communication and Networks (2017 – 2018, 2019 – 2020) -do-
6. Mentor (M. Tech. Course) Vehicular Communication (2017 – 2020) -do-
7. Mentor (M. Tech. Course) Communication Theory (2018 – 2020) -do-
8. Mentor (M. Tech. Course) Wireless Networks and Protocols (2017 – 2018) -do-
9. Mentor (M. Tech. Course) Multi-Sensor Data Fusion (2019 – 2020) -do-

Courses Handled

Post-Graduate / Ph. D. Courses Undergraduate
Estimation and Detection Theory (M. Tech., Communication Engineering and Signal Processing) Communication Theory
Wireless Networks and Protocols (M. Tech., Communication Engineering and Signal Processing) Data Communication and Networks
Vehicular Communications and Networks (M. Tech., Automotive Electronics) Wireless Communications (BTech Contact Course)
Vehicular Communications (M. Tech., Automotive Electronics)  
Multi-Sensor Data Fusion (M. Tech., Automotive Electronics)  

Specialized Courses Developed

Course Name Specialization Course Outcome
Stochastic Modelling and Queuing Theory (18CE722) MTech, Elective, Communication Engineering and Signal Processing CO1: Acquire the skill of mapping frequently occurring scenarios in telecommunication and computer networking into standard stochastic models, i.e., develop the ability to construct mathematical models from the physical description of the problems.
CO2: Be able to identify appropriate solution methods in each case and physically interpret the mathematical results
Delay Tolerant Networks MTech, Fractal Elective, Communication Engineering and Signal Processing CO1: Be able to model and analyze communication scenarios with disruption applying the delay-tolerant framework
Network Coding MTech, Fractal Elective, Communication Engineering and Signal Processing CO1: Be able to demonstrate the improvement in the performance of wireless networks due to network coding

FDP/ STTP/ Workshops/ Conferences Attended

  • Participated in a Faculty Enablement Program on the Internet of Things, organized by CIR, Amrita Vishwa Vidyapeetham, Coimbatore campus, from February 15-17, 2018.
    Outcome: Exposure to IoT applications and technologies; hands-on experience.

Academic Research

Ph. D. Guidance

  • Co-supervised four Ph. D. theses at Swinburne University of Technology, Australia.

PG Projects

Sl. No. Name of the Scholar Program Specialization Duration Status
1. Deexa Vashishtha M. Tech.  Automotive Electronics 2017-18 Completed
2. S. R. Nikhitha M. Tech.  Communication Engineering and Signal Processing 2017-18 Completed
3. Nithin N. M. Tech.  Automotive Electronics 2018-19 Completed
4. Sreenath S. M. Tech. Automotive Electronics 2018-19 Completed
5. Aiswarya A.  M. Tech. Communication Engineering and Signal Processing 2018-19 Completed
6. T. Leela Aiswarya M. Tech. Automotive Electronics 2019-20 Ongoing
7. Satya Goutham P. M. Tech. Automotive Electronics 2019-20 Ongoing
8. Nandan Kuppa M. Tech. Automotive Electronics 2019-20 Ongoing

Publications

Publication Type: Conference Proceedings

Year of Publication Title

2020

M. Nithin and Manoj Kumar Panda, “Multiple Model Filtering for Vehicle Trajectory Tracking with Adaptive Noise Covariances”, Intelligent Computing, Information and Control Systems. Springer International Publishing, Cham, pp. 557-565, 2020.[Abstract]


As the automotive world is moving towards its ultimate aim of fully autonomous vehicles, predicting the trajectories itself and that of the neighboring vehicles is essential for each vehicle. This paper proposes a novel filtering method for predicting the path of an ego vehicle (i.e., a vehicle of interest) using measurements by a Global Positioning System (GPS) device and combining such measurements with multiple candidate kinematic motion models. The proposed Multiple Model filtering method adapts to the noise conditions as inferred by measurements. It is shown that the proposed adaptive method provides a considerable level of improvement compared to the existing non-adaptive multiple model filtering.

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2020

C. V. N. S. Lalitha, Aditya, M., and Manoj Kumar Panda, “Smart Irrigation Alert System Using Multihop Wireless Local Area Networks”, Inventive Computation Technologies. Springer International Publishing, Cham, pp. 115-122, 2020.[Abstract]


From past decades, India is an agriculture-based country where the majority of the population is heavily dependent on farming. However, energy management and resource conservation continues to be the major issues in agricultural domain. The main motivations of this research is to conserve water which is a fast depleting source, and also automates the process of watering in order to reduce human workload in remote areas. In this paper, a smart irrigation alert system is developed using NodeMCU boards, a soil moisture sensor and a servo motor. The sensor measures the volumetric content of water in the soil and data is uploaded to the cloud. The main challenge addressed in this research is to seamlessly connect multiple Node MCUs to a sink (or, gateway) node such that the data can be uploaded to the cloud. Two topologies are considered. The first one is the star topology which is efficient for a kitchen garden where each of the plants is in close proximity of the sink. The second one is the multi-hop topology which is necessary in a big agriculture field. The soil moisture is sensed using multiple FC-28 sensors and uploaded to the cloud. When the moisture content drops below the threshold value, an alert notification is sent to the subscriber by e-mail and automatic watering follows by actuating the servo motor. The user can monitor and control the status of watering anywhere through the Internet. The integration of sensors, cloud and the servo motor through multiple Node MCUs is the main novelty of this work.

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2019

S. Sreenath and Manoj Kumar Panda, “Traffic Counting and Turning Fraction Estimation using Vehicle-to-UAV Co-operative communication”, 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). 2019.[Abstract]


The current roads and supporting infrastructure are often found to be incapable of handling the rapid increase in traffic, leading to congestion and incidents. The availability of accurate and real-time information about the traffic demands may go a long way in designing better traffic control and management systems. Two important quantities of interest for traffic control are the ‘traffic count’ on road segments between junctions and ‘turning fractions’ at the junctions. Together, these two quantities can determine the traffic flow requirements over the road network. The aims of the paper are to investigate the performance of the Vehicle-to-UAV (V2U) communication method for traffic counting and turning fraction estimation using vehicular network simulations and compare with the performance of Bluetooth and loop detectors.

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2019

S. Smruthi, Krishna, R. S., and Manoj Kumar Panda, “Low Energy Sensor Data Collection using Unmanned Aerial Vehicles”, 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). 2019.[Abstract]


Wireless Sensor Networks (WSNs) are one of the most important technologies today due to their numerous applications in the fields of environment monitoring, defense and agriculture, to name a few. The paper proposes some architectural alternatives to the traditional WSNs with static sinks by including mobile sinks mounted on Unmanned Aerial Vehicles (UAVs). The main performance measures of interest, energy consumption per node, throughput evolution over time, and delay per packet are studied and compared for the different architectures. The simulation results exhibit how better performance is achieved by using a mobile sink than with a static sink and how clustered topologies perform better than flat topologies.

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2018

S. R. Nikhitha and Manoj Kumar Panda, “Optimal sensor data harvesting using a mobile sink”, Procedia Computer Science, vol. 143. Elsevier B.V., pp. 921-930, 2018.[Abstract]


We investigate the idea of using a fixed-wing Unmanned Aerial Vehicle (UAV) as a mobile sink in a Wireless Sensor Network (WSN) to increase the network lifetime. We formulate and solve an optimization problem to minimize the scanning delay incurred by the UAV subject to a motion energy constraint. We also formulate and solve another optimization problem to minimize the total energy consumption for motion of the UAV and communication between the UAV and the sensor nodes subject to a delay constraint. These two optimization problems are for the case when the UAV collects the sensor data by communicating with certain special nodes called Cluster Heads. For the alternative architecture, where the UAV directly communicates with each sensor node, we investigate the performance using NS-2 simulations and provide several insightful observations. © 2018 The Authors. Published by Elsevier B.V.

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2017

Tarikul Islam, Hai Le Vu, Manoj Kumar Panda, Hoang, N., and Dong Ngoduy, “The Accuracy of Cell-based Dynamic Traffic Assignment: Impact of Signal Control on System Optimality”, The 20th International Conference of Hong Kong Society for Transportation Studies, Dec2015, Hong Kong. pp. 355-362, 2017.[Abstract]


Dynamic Traffic Assignment (DTA) provides an approach to determine the optimal path and/or departure time based on the transportation network characteristics and user behavior (e.g., selfish or social). In the literature, most of the contributions study DTA problems without including traffic signal control in the framework. The few contributions that report signal control models are either mixed-integer or nonlinear formulations and computationally intractable. The only continuous linear signal control method presented in the literature is the Cycle-length Same as Discrete Time-interval (CSDT) control scheme. This model entails a trade-off between cycle-length and cell-length. Furthermore, this approach compromises accuracy and usability of the solutions.
In this study, we propose a novel signal control model namely, Signal Control with Realistic Cycle length (SCRC) which overcomes the trade-off between cycle-length and cell-length and strikes a balance between complexity and accuracy. The underlying idea of this model is to use a different time scale for the cycle-length. This time scale can be set to any multiple of the time slot of the Dynamic Network Loading (DNL) model (e.g. CTM, TTM, and LTM) and enables us to set realistic lengths for the signal control cycles. Results show, the SCRC model not only attains accuracy comparable to the CSDT model but also more resilient against extreme traffic conditions. Furthermore, the presented approach substantially reduces computational complexity and can attain solution faster.

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2017

A. Rahman, Jin, J., Cricenti, A., Rahman, A., and Manoj Kumar Panda, “Motion and Connectivity Aware Offloading in Cloud Robotics via Genetic Algorithm”, GLOBECOM 2017 - 2017 IEEE Global Communications Conference. 2017.[Abstract]


Task offloading opens a gateway for robotic applications to leverage computation support from the cloud infrastructure. It exploits a trade-off between the robot's and cloud's processing capabilities, and the communication between the two entities plays a critical role in making these decisions. Two major factors that significantly influence communication are network connectivity (bandwidth) and mobility of the robot. We integrate these two factors with the offloading decisions to formulate an optimization problem. Our objective in this paper is to improve the quality of service (QoS) for a 25 node application taskflow, known as direct acyclic graph. We propose a genetic algorithm based approach to solve the optimization problem which performs a novel three-layer decision making: (i) whether to offload a task or not, (ii) path planning to reach a desired location for offloading/local execution, (iii) select access point to associate with for offloading. We simulate for a smart city scenario consisting of 36-cell workspace with obstacles and compare the offloading results with a well- established fixed movement offloading method. The outcomes of our study suggest that motion and connectivity aware offloading leads to more efficient performance in terms of improved QoS and minimum consumption of resources, i.e., energy, time or distance.

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Publication Type: Journal Article

Year of Publication Title

2019

S. R. Pokhrel, Manoj Kumar Panda, and Hai Le Vu, “Fair Coexistence of Regular and Multipath TCP over Wireless Last-Miles”, IEEE Transactions on Mobile Computing, vol. 18, no. 3, pp. 574-587, 2019.[Abstract]


Recent advancements in Internet congestion control have introduced a multipath TCP (MPTCP) that aims to simultaneously utilize multiple available paths in the network. In this paper, we develop an integrated fluid and packet-level analytical model to study the coexistence of regular and MPTCP users sharing a common WiFi access point (AP). We observe a throughput unfairness of MPTCP with regular TCP in the last-mile WiFi networks. In order to fix the fairness issue, we develop a real-time Adaptive Loss Management (ALM) algorithm that continuously monitors the deviation in AP buffer occupancy and adapts its packet admission probability based on a closed form expression derived from our analytical model. We provide a proof as well as show via numerical and simulation results that the proposed ALM algorithm is TCP-friendly by design, and provably stable.

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2019

Tarikul Islam, Hai Le Vu, and Manoj Kumar Panda, “System optimal dynamic traffic assignment: solution structures of the signal control in non-holding-back formulations”, Transportmetrica B: Transport Dynamics, vol. 7, no. 1, pp. 967-991, 2019.[Abstract]


This paper devises locally optimal traffic Signal Control (SC) settings in a Non-Holding-Back Dynamic Traffic Assignment with SC (NHB DTA-SC) formulation for single destination (i.e. one source to one destination and many sources to one destination) networks. To this end, we apply temporal–spatial dual decomposition method and decompose the NHB DTA-SC problem into intersection cells and non-intersection cells. Then we further decompose the intersection cells into different subproblems, i.e. Occupancy Minimization (OM), Flow Maximization (FM), and SC. To study the optimal SC structures, we examine the Karush–Kuhn–Tucker (KKT) optimality conditions of the decomposed SC subproblem. Finally, we obtain the locally optimal SC structures under different network conditions that include over-saturated, under-saturated, and queue spillback traffic scenarios. We also present several numerical results to verify the optimality structures found by our theoretical derivations.

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2019

N. H. Hoang, Hai Le Vu, Manoj Kumar Panda, and Lo, H. K., “A linear framework for dynamic user equilibrium traffic assignment in a single origin-destination capacitated network”, Transportation Research Part B: Methodological, vol. 126, pp. 329 - 352, 2019.[Abstract]


The dynamic traffic assignment (DTA) problem has been studied intensively in the literature. However, there is no existing linear framework to solve the user equilibrium (UE) DTA problem. In this paper, we develop a novel linear programming framework to solve the UE-DTA problem in a dynamic capacity network that exploits the linkage between the UE and system optimal (SO) solutions underpinned by a first-in-first-out (FIFO) principle. This important property enables us to develop an incremental loading method to obtain the UE solutions efficiently by solving a sequence of linear programs. The proposed solution methodology possesses several nice properties such as a predictable number of iterations before reaching the UE solution, and a linear system of equations to be solved in each of the iterations. In contrast to the related iterative methods, such as Frank–Wolfe algorithm, successive average (MSA) or projection and their extensions where the purpose of iteration is to seek the solution convergence, whereas ours is to solve a linear problem over multiple iterations but only for a single unit of demand in each iteration. Furthermore, we provide a theoretical proof that in the limit, the SO objective can be used to obtain the UE solution as the system time step goes to zero given the satisfaction of the FIFO constraint. We show via numerical examples the significant improvements in the obtained UE solutions both in terms of accuracy and computational complexity.

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2019

Manoj Kumar Panda, Dong Ngoduy, and Hai Le Vu, “Multiple model stochastic filtering for traffic density estimation on urban arterials”, Transportation Research Part B: Methodological, vol. 126, pp. 280-306, 2019.[Abstract]


Traffic state estimation plays an important role in Intelligent Transportation Systems (ITS). It provides the latest traffic information to travelers and feedback to signal control systems. The Interactive Multiple Model (IMM) filtering provides a powerful estimation method to deal with the non-differentiable nonlinearity caused by the phase transitions between the under-critical and above-critical traffic density regimes. The IMM filtering also accounts for the uncertainty in the current ‘mode of operation’. In this paper, we develop an enhanced IMM filtering approach to traffic state estimation, with an underlying Cell Transmission Model (CTM) for traffic flow propagation. We improve the IMM filtering with CTM in two ways: (1) We apply two simplifying assumptions that are highly likely to hold in urban roads in incident-free conditions, which makes the computational complexity to grow with the number of cells only polynomially, rather than exponentially as reported in prior work. (2) We apply a novel approach to noise modeling wherein the process noise is explicitly obtained in terms of the randomness in more fundamental quantities (e.g., free-flow speed, maximum flow capacity, etc.), which not only makes noise calibration using real data convenient but also makes the computation of the cross-correlation between the process and measurement noises transparent. However, it leads to ‘process dynamic’ and ‘measurement’ equations that involve multiplier matrices whose elements are random variables rather than deterministic scalars, and hence, standard filtering equations cannot be applied. We derive the appropriate filtering equations from first principles. We calibrate the traffic parameters and the total inflow and outflow on the links using the SCATS loop detector data collected in Melbourne and report significant improvements in accuracy, which is due to the accurate computation of the cross-covariance of process and measurement noises. © 2019 Elsevier Ltd More »»

2018

H. P. Luong, Manoj Kumar Panda, Hai Le Vu, and Vo, B. Q., “Beacon Rate Optimization for Vehicular Safety Applications in Highway Scenarios”, IEEE Transactions on Vehicular Technology, vol. 67, no. 1, pp. 524-536, 2018.[Abstract]


Vehicle-to-vehicle (V2V) communication enables exchanging information between vehicles by broadcasting safety and beacon messages. Safety applications based on a so-called dedicated short-range communication, which are one of the main applications of V2V, require a very strict network performance for safety messages. In this paper, we investigate the effect of the beacon rate on the network performance of safety messages and develop an optimization problem to recommend optimal beacon rates based on a utility maximization framework. The message utility is constructed to account for the reliability requirements of safety messages and maintain the accuracy of neighborhood information collected by beacons. Specifically, we obtain the relationship between the optimal beacon rate and the system parameters. Our results show that the optimal beacon rates can meet the requirements of safety applications and improve the network performance up to 40%.

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2018

Tarikul Islam, Hai Le Vu, Manoj Kumar Panda, and Dong Ngoduy, “A study of realistic dynamic traffic assignment with signal control, time-scale, and emission”, Journal of Intelligent Transportation Systems, vol. 22, no. 5, pp. 446-461, 2018.[Abstract]


Dynamic Traffic Assignment (DTA) is a mathematical framework that with a System Optimal (SO) objective is often used for long-term transport planning, design, and traffic management. However, the conventional SO-DTA formulation gives optimal solutions having an unrealistic vehicle Holding–Back (HB) property. Existing approaches in the literature aiming to resolve the HB problem are either computationally intractable or suffer from recursive parameter selection problem. In addition, most of the existing Signal Control (SC) models considered in the DTA formulation are mixed-integer or nonlinear in nature that are not scalable for large networks. With an exception, there exists a linear signal control model that can only set signal control cycle-length equal to DTA time-slot duration, and thus trades the accuracy of the SO-DTA solution for a more realistic cycle-length. In this article, we address the above issues by proposing a linear Non-Holding-Back SO-DTA with SC (NHB DTA-SC) formulation for single destination networks. The embedded signal control in the proposed framework enables us to set realistic cycle-length using any DTA time-slot (i.e., flexible time-scale). We find that the time-scale has a significant impact on traffic density which affects vehicle-discharged emissions. To this end, we develop a novel linear Emission-Based DTA with SC (EB DTA-SC) formulation that obtains NHB flows as well as lowest possible emission. Our results show that there is a 32% difference between emission estimated by 60-second and 5-second time-scales.

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2017

B. Dhivyabharathi, Kumar, B. N. Anil, Vanajakshi, L., and Manoj Kumar Panda, “Particle Filter for Reliable Bus Travel Time Prediction Under Indian Traffic Conditions”, Transportation in Developing Economies, vol. 3, no. 13, pp. 1-11, 2017.[Abstract]


In recent times, traffic congestion has been increasing rapidly and deteriorating the quality of traffic systems in urban areas of many developed and developing countries. This became a serious problem faced by society, as many people are using private vehicles while commuting from one place to the other. One of the reasons people are shifting towards private transportation is due to lack of reliability of the public transportation systems. Attracting more travelers towards public transportation using Intelligent Transportation Systems (ITS) technologies is one way to reduce the negative impacts. In this context, prediction of bus travel time and providing information about bus arrival time to passengers accurately is a potential solution, which will help in reducing the uncertainty and waiting time associated uncertainties with public transit systems. However, for this solution to be effective, the information provided to passengers should be highly reliable. The present study proposes a model based prediction method that uses particle filtering technique for accurate prediction of bus travel times for the development of a real time passenger information system under heterogeneous traffic conditions that exist in India. The results obtained from the implementation of the above method are validated using the measured travel time. The prediction accuracy is quantified using the Mean Absolute Percentage Error (MAPE) and the performance is compared with a base approach namely, the historic average method. The quantified error in terms of MAPE is 20% for the proposed method and 37% for the historic average method, indicating the superiority of the proposed method over historic average method. Thus, it can be concluded that particle filter is a viable tool in the prediction of bus travel times.

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2017

S. R. Pokhrel, Manoj Kumar Panda, and Hai Le Vu, “Analytical Modeling of Multipath TCP Over Last-Mile Wireless”, IEEE/ACM Transactions on Networking, vol. 25, no. 3, pp. 1876-1891, 2017.[Abstract]


We develop a comprehensive analytical model for multiple long-lived multipath Transmission Control Protocol (TCP) connections downloading content from a remote server in the Internet using parallel paths with Wi-Fi and cellular last-miles. This is the first analytical model developed in the literature that captures the coupling between the paths through heterogeneous wireless networks where the coupling arises due to the multipath TCP coupled congestion control protocol. The model also takes into account the impact of the shared nature of the wireless medium and the finite access point (AP) buffer in the Wi-Fi last-mile. The accuracy of the proposed model is demonstrated via extensive ns-2 simulations. Furthermore, we discover a new type of throughput unfairness among the competing regular and multipath TCP connections going through the same AP with a droptail buffer; the regular TCP connections essentially steal almost all the Wi-Fi bandwidth away from the multipath TCP connections. To tackle this problem, we present two simple solutions utilizing our analytical model and achieve fairness.

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Faculty Research Interest: