Research work

Stability and delay performance for wireless systems with reconfiguration delay

We consider wireless downlinks where the base station switches between different users in order to transmit data intended for the respective users. When switching between users, the logical links between the user and the base station need to be configured. For example, the user’s state may need to be changed from an idle to an active state. This incurs a reconfiguration delay, which is the delay between the time at which the base station scheduler decides to serve the user and the time at which the actual data transmission starts. Motivated by such scenarios, we consider the stability region and throughput optimal scheduling for a wireless downlink model with random connectivity over time and reconfiguration delay. We have also looked at the problem of minimizing average delay for wireless systems with reconfiguration delay when the channel connectivity is correlated

• J4: Scheduling Policies for Wireless Downlink with Correlated Random Connectivity and Multislot Reconfiguration Delay, with Amit Kumar - Accepted to IEEE Communications Letters.
• C11: Throughput Optimal Scheduling for Wireless Downlinks with Reconfiguration Delay - accepted to NCC 2018.Extended version of paper submitted to NCC-2018

Stability and delay analysis for delay tolerant networks with random packet arrivals

Our research objective is to theoretically analyze the stability of queues and average delay of messages in a delay tolerant network. We consider a simple delay tolerant network model with the source spray and wait routing protocol without feedback for our initial analysis. This is work in progress. Some approximations to the average queueing delay has been obtained by interpreting the system as a M^{K}/G/N system. Simulation code for this work is available here.

• C9: Stability and delay analysis of delay tolerant networks with random message arrivals, with Sarath A. Y. and Chandramani Singh - COMSNETS, 2017.
• C13: Stability properties of delay tolerant networks with buffered relay nodes, with Chandramani Singh - CCDWN, 2018. (Extended version of paper submitted to CCDWN)

Bayesian quickest detection for active sensors

Active sensors use radar, ultrasound, or optical sensing to control the information content in the sequentially collected noisy data. Using such active sensing to increase the extent of collected information, it is possible to quickly detect changes in the environment. However, increasing the extent of information contained in the collected data would lead to a cost or energy expenditure, where the cost would naturally increase as the extent of contained information increases. For such a sensor, our objective is to design control policies that optimally trade off performance metrics such as detection delay, average cost expended in control, and probability of false alarm. We consider this problem in the setting of Bayesian quickest change detection. Our preliminary results can be found in the following paper.

• J3: Bayesian quickest change detection for active sensors - In IEEE Communications Letters, November 2016.

Optimal addition of links to a communication network

The quality of service offered by a communication network to its users can be improved by the addition of communication links between appropriate nodes in the network. We pose this link addition problem as an optimal edge addition problem in graphs. Some of our preliminary results are given in the following paper, where we have considered a simple linear graph.

• J2: Analytical Identification of Anchor Nodes in a Small-World Network, with Abhishek Chakraborty and B. S. Manoj - In IEEE Communications Letters, 2016.

Power delay tradeoff for dynamic data compression and transmission over a wireless channel

In power constrained sensor networks and satellite telemetry systems there arises scenarios where multiple sensors produce data which is correlated. We consider a communication scenario where a power-limited transmitter aggregates correlated data from different sources for transmission to a sink over a wireless fading channel. In order to reduce the average queueing delay, the transmitter could compress the data before transmission. We note that it is not obvious that compressing the data to the maximum extent possible leads to the best possible tradeoff. Prior work has found that although wireless transmission of a bit can require energy over a 1000 times more than a single 32-bit computation, compression using typical algorithms (LZW) may actually lead to larger power expenditure, due to power expensive memory accesses. So both data compression as well as wireless transmission expends comparable amounts of power which is a precious resource for the transmitter. We consider the problem of designing joint compression and transmission policies for the transmitter which can optimally tradeoff the average queueing delay of the transmitted data with the average total power of compression and transmission. Our preliminary results are reported in this work.

• C8: Power delay tradeoff for dynamic data compression and transmission over a wireless channel, with Utpal Mukherji - In Signal Processing and Communication Conference, Bangalore - 2016.

On the tradeoff of average delay, average service cost, and average utility for single server queues with monotone policies

We studied the tradeoff of average delay with average service cost and average utility, for single server queueing models without and with admission control. We considered continuous time and discrete time queueing models with a random environment. The tradeoff problem is studied for the class of monotone scheduling policies, i.e., scheduling policies for which the service rate is a non-decreasing function of the queue length for each environment state. The continuous time and discrete time queueing models that we considered are motivated by cross-layer models for point-to-point links with random packet arrivals and fading at slow and fast time scales. Our objective is motivated by the need to optimally tradeoff the average delay of the packets (a network layer performance measure), with the average service cost of transmitting the packets, e.g. the average power required for transmission (a physical layer performance measure), under a lower bound constraint on the average throughput. We also considered the problem of optimally trading off the average delay and average error rate of randomly arriving message symbols which are transmitted over a noisy point-to-point link. It is intuitive that to keep a queue stable under a lower bound constraint on the average utility, a minimum number of customers have to be served per unit time. This in turn implies that queue stability requires a minimum average service cost expenditure. In this thesis, we obtain primarily an asymptotic characterization of the minimum average delay for monotone policies, subject to an upper bound constraint on the average service cost and a lower bound constraint on the average utility, in the asymptotic regime where the average service cost constraint is made arbitrarily close to the above minimum average service cost. The results are presented in J1, C4, and C5. This is also presented in the thesis.

• J1: Asymptotic Bounds on the Power-Delay Tradeoff for Fading Point-to-Point Links From Geometric Bounds on the Stationary Distribution of the Queue Length, with Utpal Mukherji - In IEEE Transactions on Information Theory, 2015.
• C4 : Tradeoff of average power and average delay for a point-to-point link with fading, with Utpal Mukherji - In Proceedings of the National Conference on Communications (NCC), 2013.
• C5 : Tradeoff of average service cost and average delay for the state dependent M/M/1 queue, with Utpal Mukherji - In Proceedings of the National Conference on Communications (NCC), 2013.

Reliable and delay-optimal communication of bursty sources over communication channels (DRDO-IISc programme on mathematical engineering)

An understanding of communication networks is possible only if queueing-theoretic and information-theoretic aspects of communication are considered as a whole. Classical information theory assumes that sources always have information to send and characterizes performance through metrics such as capacity regions and the asymptotic dependence of error probability on coding length. But real world sources produce information that is bursty in nature. The bursty nature of sources has two main implications : a) a bursty source uses the channel resources intermittently thus presenting a time varying channel to the other sources in the network, and b) the random nature of information production and its transmission leads to queueing at the transmitters and resource scheduling problems. In this project, we restricted ourselves to understanding the implication (b) by considering simple discrete time point-to-point channels. We studied the queueing process at the transmitter of a point-to-point channel with a refined information theoretic model, based on the channel coding error exponent, for the transmission scheme. For point-to-point channels using variable length block codes, that guarantee a constant error probability per transmission, we obtain an approximately average-delay-optimal policy, presented in C1 and T1. We also obtain analytical upper and lower bounds on the minimum average delay, presented in C3 and T2. For point-to-point channels using block coding we obtain the exponential decay rate of average error probability with average delay for both fixed and variable length block coding in C2 and T3. Furthermore for fixed block length coding schemes we obtain upper and lower bounds on the tradeoff in C2. In T4 we show that using streaming codes the exponential decay rate of average error probability with average delay can be improved from what that is achieved by block coding schemes. We then consider the problem of allocating transmitter power, for channel inversion, for a slow fading point-to-point channel in T5. Approximations to the optimal allocation are obtained when the average delay is allowed to be large or equivalently when the available average transmitter power is reduced.

• C1 : Average-delay optimal policies for the point-to-point channel with Utpal Mukherji - In proceedings of the 7th international symposium on modeling and optimization in mobile, ad hoc, and wireless networks (WiOpt), 2009.
• C2 : Queueing delay - error probability tradeoff for point-to-point channels with fixed length block codes, with Utpal Mukherji - In proceedings of the IEEE International symposium on Information Theory (ISIT), 2011.
• C3 : Delay optimal scheduling of a discrete time batch service queue for point-to-point channel code rate selection, with Utpal Mukherji - In proceedings of the National Conference on Communications (NCC), 2012.
• T1 : Average-delay optimal policies for the point-to-point channel, TR-PME-2010-13, 2010
• T2 : Bounds on the optimal queueing delay for variable rate point-to-point channels with fixed block error probability, TR-PME-2011-11, 2011.
• T3 : Queueing delay - error probability tradeoff for point-to-point channels using block codes, TR-PME-2011-12, 2011.
• T4 : Queueing delay - error probability tradeoff for point-to-point channels using streaming codes, TR-PME-2011-13, 2011.
• T5 : Tradeoff of average power and average delay for slow fading point-to-point channels under reliability constraints, TR-PME-2011-14, 2011.

• C32: On Identifying Optimal Shortcut Edge Locations in a Linear Small-World Wireless Sensor Network, with Abhishek Chakraborty, B. S. Manoj, and Ramesh R. Rao, IEEE ICC 2024.
• C31: Resistance Network Synthesis for Analog Thermistor Linearizer Circuits using Differential Evolution and Graph Laplacian, with S. Nani and Anoop C. S., International Conference on Sensing Technology (ICST), Hyderabad, 2023
• C30: Remote control of bandits over queues - relevance of information freshness, with Vatsalya Gupta, Modelling and optimization in semantic communications (WiOpt Workshop), Singapore, 2023
• C29: Studies on Linearizing Direct-Digital Converter Schemes for Thermistors, with Thomaskutty Mathew, S. Nani, Anoop C. S., IEEE International Instrumentation and Measurement Technology Conference, Malaysia, May 2023
• C28: On the Optimal Tradeoff of Age of Information and Transmission Power for Point-To-Point Links, with Sudarsanan A. K. and Chandra R. Murthy, NCC2023. (Best paper award in networking track)
• C27: On Age of Information for Remote Control of Markov Decision Processes over Multiple Access Channels, with Minha Mubarak, NCC 2023.
• C26: IndoorRSSINet - Deep learning based 2D RSSI map prediction for indoor environments with application to wireless localization, with Nibin Raj, COMSNETS 2023.
• C25: Safe Sequential Optiization using Posterior Sampling, with Pratik Kar, SPCOM 2022. (Shortlisted for best paper award)
• C24: Safe Sequential Optimization in Switching Environments, with Durgesh Kalwar, NCC 2021.
• C23: Slotted Aloha for FMCW Radar Multiple Access Networks, with Haritha K. and Chandramani Singh, NCC 2021.
• C22: Design of Joint Relay Placement and Scheduling Algorithms for Time-Slotted Networks with Half-Duplex Constraints, with Harshavardhana T. G. and Pragya Shah, COMSNETS 2021.
• C21: On the average and peak age-of-information for Berkeley-MAC protocol, with Govind A. M, ANTS 2020.
• C20: Pano2RSSI: Generation of RSSI maps for a room environment from a single panoramic image, with Nibin Raj and D.V.V. Sai Teja, ANTS 2020.
• C19: Optimal Downlink Scheduling and Power Allocation with Reconfiguration Delay, with Gowri M., and Premkumar K., COMSNETS 2020.
• C18: Minimum delay scheduling under average power constraint for 802.11ax uplink, with Binoy B, ANTS 2019.
• C17: A study of Average and Peak Age-of-Information for MAC protocols in Contiki, ANTS 2019.
• C16: Signal Design and Detection Algorithms for Quick Detection Under False Alarm Rate Constraints, with Alamuru Pavan Kumar, NCC 2019.
• C15: On the Evolution of Finite-Sized Complex Networks with Constrained Link Addition, with Abhishek Chakraborty and B. S. Manoj, ANTS 2018.
• C14: Empirical Delay Models for 802.11 under Deterministic Convergecast Traffic, with Anand Ramesh, ANTS 2018.
• C13: Stability properties of delay tolerant networks with buffered relay nodes, with Chandramani Singh, CCDWN 2018.
• C12: Optimal Association of Wireless Devices to Cellular and Wi-Fi Base Stations, with Chandramani Singh, NCC 2018.
• C11: Throughput Optimal Scheduling for Wireless Downlinks with Reconfiguration Delay, NCC 2018.
• C10: Power control and cross-layer design of RPL objective function for low power and lossy networks, with Harshavardhana T. G., SVR Anand, and Malati Hegde, COMSNETS 2018.
• C9: Stability and delay analysis of delay tolerant networks with random message arrivals, with Sarath A. Y. and Chandramani Singh, COMSNETS 2017.
• C8: Power delay tradeoff for dynamic data compression and transmission over a wireless channel, with Utpal Mukherji, SPCOM 2016.
• C7: Influence of Greedy Reasoning on Network Evolution, with Abhishek Chakraborty and B. S. Manoj, LSCNA 2015.
• C6: On power-law decay exponents and Barabasi models for subscriber usage behaviour in mobile networks], with Jobin Wilson and Prateek Kapadia, NCC 2015.
• C5: Tradeoff of average service cost and average delay for the state dependent M/M/1 queue, with Utpal Mukherji, NCC 2013.
• C4: Tradeoff of average power and average delay for a point-to-point link with fading, with Utpal Mukherji, NCC 2013.
• C3: Delay optimal scheduling of a discrete time batch service queue for point-to-point channel code rate selection, with Utpal Mukherji, NCC 2012.
• C2: Queueing delay - error probability tradeoff for point-to-point channels with fixed length block codes, with Utpal Mukherji, ISIT 2011.
• C1: Average-delay optimal policies for the point-to-point channel, with Utpal Mukherji, WiOpt 2009

See https://vineethbs.github.io for more details.