Dr. Manoj Kumar Panda

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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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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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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Traffic congestion is a major concern in metropolitan areas and a quick congestion assessment of large-scale network is required for modern traffic management referred to as Intelligent Transport Systems (ITS). However, ITSs are facing the challenge of real-time storage, retrieval and processing of a vast amount of collected data over a large-scale network. Compressed sensing (CS) is an efficient technique of sampling high-dimensional data and is successfully used to reconstruct signals via a small set of non-adaptive, linear measurements. Whilst CS has mainly been applied for data reconstruction, we propose in this paper the use of CS for classification and estimation of some meaningful parameters in the traffic problem. To this end, we develop a novel sensing matrix for congestion analysis and show that for traffic data collected in Melbourne urban network, our CS provides an opportunity to extract the desired information from a small number of random projections. In addition, our method could improve the efficiency of database query and has the ability to deal with missing or defective data.

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Broadcasting is the most prevalent method for disseminating information in vehicular networks. At high vehicle densities, the so-called broadcast storm problem degrades the efficiency of broadcasting. A so-called Irresponsible Forwarding (IF) scheme has recently been proposed in the literature that can effectively combat the broadcast storm problem. For messages consisting of multiple packets, the coupon collector problem also degrades the broadcast efficiency at all vehicle densities. In this paper, we extend the basic IF scheme to multi-packet messages, which we call the max-min IF, and combine it with Random Linear Coding (RLC) of packets at the source to solve the coupon collector problem and improve the broadcast efficiency of IF. Through discrete event simulations, with a widely accepted realistic vehicular mobility model based on cellular automata, we demonstrate that our IF+RLC scheme can significantly improve the reachability in sparsely connected vehicular networks at low vehicle densities as well as reduce the mean delay under high probability of collisions at high vehicle densities.

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We consider a Delay/Disruption Tolerant Network under two-hop routing. Our objective is to estimate and track the degree of spread of a message/file in the network. Indeed, having such real-time information is critical for on-line control of routing and energy expenditure. It also benefits the multi-casting application. With exponential inter-meeting times of mobile nodes: (i) for the estimation problem, we obtain exact expressions for the minimum mean-squared error (MMSE) estimator, and (ii) for the tracking problem, we first derive the diffusion approximations for the system dynamics and the measurements and then apply Kalman filtering. We also apply the solutions of the estimation and filtering problems to predict the time when a certain pre-defined fraction of nodes have received a copy of the message/file. Our analytical results are corroborated with extensive simulation results.

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We propose a new reliable transport scheme for Delay Tolerant Networks (DTNs) based on the use of acknowledgments (ACKs) as well as coding. We, specifically, develop a fluid-limit model to derive expressions for the delay performance of the proposed reliable transport scheme and derive the optimal setting of the parameters which minimize the file transfer time. Our results yield optimal values for the number of outstanding random linear combinations to be sent before time-out as well as the optimal value of the time-out itself, which, in turn, minimize the file transfer time.

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We focus on the energy spent in radio communication by the stations (STAs) in an IEEE 802.11 infrastructure WLAN. All the STAs are engaged in web browsing, which is characterized by a short file downloads over TCP, with short duration of inactivity or think time in between two file downloads. Under this traffic, Static PSM (SPSM) performs better than CAM, since the STAs in SPSM can switch to low power state (sleep) during think times while in CAM they have to be in the active state all the time. In spite of this gain, performance of SPSM degrades due to congestion, as the number of STAs associated with the access point (AP) increases. To address this problem, we propose an algorithm, which we call opportunistic PSM (OPSM). We show through simulations that OPSM performs better than SPSM under the aforementioned TCP traffic. The performance gain achieved by OPSM over SPSM increases as the mean file size requested by the STAs or the number of STAs associated with the AP increases. We implemented OPSM in NS-2.33, and to compare the performance of OPSM and SPSM, we evaluate the number of file downloads that can be completed with a given battery capacity and the average time taken to download a file.

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The network scenario is that of an infrastructure IEEE 802.11 WLAN with a single AP with which several stations (STAs) are associated. The AP has a finite size buffer for storing packets. In this scenario, we consider TCP controlled upload and download file transfers between the STAs and a server on the wireline LAN (e.g., 100 Mbps Ethernet) to which the AP is connected. In such a situation, it is known (see, for example, [3], [9]) that because of packet loss due to finite buffers at the AP, upload file transfers obtain larger throughputs than download transfers. We provide an analytical model for estimating the upload and download throughputs as a function of the buffer size at the AP. We provide models for the undelayed and delayed ACK cases for a TCP that performs loss recovery only by timeout, and also for TCP Reno.

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In the recent years, IEEE 802.11 wireless local area networks (WLANS) have increasingly been deployed in a variety of situations, such as homes, business enterprises, academic campuses, and public places such as airports, hotels, and shopping centers. It has therefore become very important to understand the performance of such networks, and also how to effectively design, deploy and manage them. In this paper our concern is mainly with the analytical performance evaluation of WLANs. We will also consider an aspect of optimisation of such networks. We will begin with a discussion of saturation throughput analysis of single cell WLANs. In this context the seminal contribution is due to G. Bianchi who proposed a decoupling approximation that led to a fixed point equation, the solution of which yielded an approximation to the attempt rate of any node. We show that, in fact, the fixed point equation can be established using a renewal reward argument and in a much more general setting. Further, in this setting a natural condition on the back-off sequence leads to uniqueness of the fixed point. It is possible to take the same decoupling approximation and develop a vector fixed point equation, assuming that the nodes have possibly unequal attempt rates. If a vector fixed point has unequal coordinates, then we say that it is unbalanced. The traditional approach only considered balanced fixed points. We consider the vector fixed point equation, and show that, in general, there can exist multiple unbalanced fixed points, even in those situations where there is a unique balanced fixed point. Simulations show that in situations where this happens the system exhibits significant short term unfairness, and further, the balanced fixed point analysis fails to capture the steady state performance. For the case in which the mean back-off grows multiplicatively with collisions, we establish a sufficient condition for a system to have a unique fixed point (that is also balanced). The original IEEE 802.11 medium access control (MAC) mechanism provided no means for differentiating the channel access provided to the contending devices. A new addition to the IEEE 802.11 suite of standards, IEEE 802.11e, now provides several access differentiation mechanisms. One set of mechanisms differentiates access by permitting different devices (or queues in devices) to have different channel access parameters, such as the initial back-off, the back-off multiplier, and the maximum back-off. Another, mechanism is that, after every successful transmission, nodes with a lower access priority wait for a little longer than other nodes before reinitiating their back-off and attempt processes, thus giving the higher priority class nodes a better chance to access the channel. This latter mechanism is called AIFS (arbitration interframe space). The vector fixed point analysis is extended to both these mechanisms, and we establish a condition for uniqueness of the fixed point. For all the above access mechanisms, we also provide asymptotic results in the regime where the number of retrials is unbounded and the number of nodes goes to ∞. This analysis provides interesting analytical insights into the role of some of the access parameters. Saturation throughput analysis is normally conducted to assess the "capacity" of these networks. However, it is possible to use the saturation throughput analysis directly in certain application situations. We provide a demonstration of this in the context of TCP controlled transfer of large files. While much of the analysis discussed above is for single cell WLANs, in practice, in order to cover large spaces, WLANs comprise multiple overlapping cells. Since there are only three nonoverlapping frequency bands in the operational spectrum, in a typical WLAN deployment, cochannel WLAN cells will overlap. We develop a fixed point based saturation throughput analysis of two cells whose decoding ranges are disjoint but their carrier sense ranges completely overlap. The analysis captures an interesting unfairness that occurs in this situation. The model turns out to be similar to the one obtained for the AIFS based throughput differentiation mechanism mentioned above. At the present time there do not appear to be systematic techniques to design and optimise WLANs. We will briefly discuss the problem of optimal association of devices to access points (APs) in an infrastructure WLAN. The problem is that there are several mobile devices, each of which can potentially connect via one of several candidate APs, at various physical layer rates. The question is: "What is an optimal association?" We formulate the problem as one of maximising, over the possible associations, the sum of the up-link utilities obtained at the devices. Thus the problem is like the optimal bandwidth sharing problem, well known in wired packet networks, with the additional complexity that the network "topology" also needs to be simultaneously obtained. We formulate the problem, discuss the issues, and provide some preliminary results.

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IEEE 802.11 wireless local area networks that span large buildings or campuses must comprise multiple cells, several of which must necessarily be cochannel cells. It can be shown that in such multicell networks, typically, the radio ranges of cochannel cells overlap. The paper studies the saturation throughput performance of two cochannel cells with critical overlap, i.e., their interference ranges completely overlap but no node in either cell can decode any transmissions from the other cell. We identify that the difference between the two MAC parameters, EIFS (extended interframe space) and DIFS (DCF interframe space) is a key issue and incorporate this difference as a parameter into an analytical model. The model yields a fixed point equation that yields an approximation to the saturation throughputs of the two cells. The results from the analysis are validated against ns-2 simulations. We find that with EIFS>DIFS there is substantial temporal unfairness in the channel access between the two cells, but, because of fewer collisions, the critical overlap configuration has higher per cell throughput than if the cells' decoding ranges overlapped.

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The boom in new streaming media applications in the recent past calls for innovative strategies that can support both data and media over the same global IP based Internet in a fair and efficient manner. Several solutions have already been proposed to control the rate of media traffic and to maintain fairness among the heterogeneous traffic flows. We propose a mechanism that solves many of the problems associated with the earlier schemes. A new concept, called "loss sharing", is introduced for 'media rate control' and 'maintenance of fairness'. We show that these two objectives are automatically achieved as desirable side-effects of the recently proposed "TTL routing algorithm". This algorithm adopts a new interpretation of the TTL (time-to-live) field of the IP header. It is shown that rate control by "TTL routing" has certain other desirable features.

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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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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 »»

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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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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We propose an analytical model for a Wi-Fi network acting as a last-mile Internet access with multiple long-lived TCP connections on both the up and down links. Our model considers the joint impact of buffer losses at the access point, contention at the medium access control layer, and packet losses due to the wireless channel being erroneous. We show that the model accurately quantifies the probability of an arbitrary TCP packet being discarded, and the total throughput obtained on the up and down links. Furthermore, quantitative insights can be gained into the throughput that long-lived TCP flows achieve under the joint impact of all aforementioned types of losses. In particular, we find that the wireless channel errors and buffer overflows both lead to throughput unfairness, but that they do so in the opposite direction on the up and down links, respectively. We demonstrate that this insight can be exploited so as to significantly mitigate the throughput unfairness without compromising the total obtainable network throughput.

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TCP NewReno is one of the most widely deployed TCP versions in today's Internet. However, a full understanding of the complex inter-dependencies between the losses due to wireless channel errors and those due to buffer overflows, and their (joint) impact on TCP NewReno's congestion control algorithm in wireless and wired-cum-wireless networks is still lacking. In this paper, we develop a comprehensive analytical model for, and study the performance of, TCP NewReno with a cellular last-mile access, taking into account both types of losses. We assume a frame-level Markovian loss model, and build a model that features the system's basic controllable parameters (such as the number of retransmissions and the buffer size), so as to study how they (jointly) affect the TCP-level throughput. We model certain finer aspects, e.g., correlations in wireless and buffer losses and their cross-correlation. We provide a summary of numerical results highlighting several non-trivial findings. In particular, we demonstrate that there exist optimal (i.e., TCP throughput maximizing) pairs of the number of retransmissions and the buffer size.

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We propose and study a new set of enhancement features to improve the performance of reliable transport in Delay Tolerant Networks (DTNs) consisting of both unicast and multicast flows. The improvement in reliability is brought in by a novel Global Selective ACKnowledgment (G-SACK) scheme and random linear network coding. The motivation for using network coding and G-SACKs comes from the observation that one should take the maximum advantage of the contact opportunities which occur quite infrequently in DTNs. Network coding and G-SACKs perform “mixing” of packet and acknowledgment information, respectively, at the contact opportunities and essentially solve the randomness and finite capacity limitations of DTNs. In contrast to earlier work on network coding in DTNs, we observe and explain the gains due to network coding even under an inter-session setting. Our results from extensive simulations of appropriately chosen “minimal” topologies quantify the gains due to each enhancement feature. We show that substantial gains can be achieved by our proposed enhancements that are very simple to implement.

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