Deepthi Chander

Indian Institute of Technology Bombay

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i-10 index

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Co-Authors

S. N. Merchant

Indian Institute of Technology Bombay

Bhushan Jagyasi

University of California, Davis

Koustuv Dasgupta

Xerox (France)

U.B. Desai

Goa University

Uday B. Desai

Indian Institute of Technology Hyderabad

Tridib Mukherjee

Karlsruhe Institute of Technology

Archan Misra

Singapore Management University

Kannan Govindan

University of Adelaide

Anirban Mondal

Case Western Reserve University

Kannan Govindan

Indian Institute of Technology Bombay

Cooperative Institutions

Indian Institute of Technology Bombay

Xerox (France)

Singapore Management University

Indian Institute of Technology Indore

Tata Consultancy Services (India)

Indian Institute of Technology Hyderabad

Amrita Vishwa Vidyapeetham

Punjab Engineering College

University of California, Davis

University of Southern Denmark

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Performance characterization and scalable design of sensing-as-a-service platform

Tridib Mukherjee Amit Kumar Deepthi Chander Koustuv Dasgupta Amandeep Chugh

Advancements and proliferation of sensing and actuation technologies in diverse computing and physical devices call for a flexible Sensing-as-a-Service Platform (SeaaS-P) that can enable massive-scale next generation applications. A key aspect of such a platform, which has been largely unexplored in terms of applicability at a massive scale, is the notification system (e.g. city incident notification) to send event alerts to subscribers. Conventional event-based systems (e.g. publish-subscribe) typically trigger notifications with every event arrival. Observations based on deployment of even a simple SeaaS-P instantiation (with just mobile based event reporting at a very large scale) show resources (e.g. CPU) can become bottleneck and get overused when event rates and number of subscriptions go beyond certain thresholds. Thus, it may be necessary to opportunistically delay the notification, i.e. not send the notifications with every event update (e.g., time-triggered periodic notifications), depending on the delay-tolerance of the application. This paper proposes a: (i) performance profiling of SeaaS-P in terms of resource utilizations and % notification drop; and (ii) design framework to determine the design boundaries of SeaaS-P notification system for both event-triggered and time-triggered notifications.

Notification system

Event monitoring

Profiling (computer programming)

10.1145/2695664.2696042

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Citations (2)

Efficient and Scalable Spatial Retrieval of Resident Involvement Information in City Events

Anirban Mondal Tridib Mukherjee Amandeep Chugh Atul Kumar Singh Deepthi Chander

Information about resident involvement in reporting various city-related events (e.g., Potholes, traffic jams) via mobile apps is critical to key stakeholders for effective city management. While existing efforts have primarily focused on event data collection in space, they are not capable of performing efficient retrieval of information about resident involvement in event reporting across different spatial regions and at different spatial granularities. Hence, this work makes the following contributions. First, we present CRIS, a scalable system for efficient retrieval of resident involvement and event information across different spatial regions and at varying spatial granularities. Second, we propose the euR-tree, a novel R-tree-based index augmented with (a) a hash-based array for indexing events in space, and (b) fixed-length arrays for indexing resident involvement information in reporting events in space. The euR-tree is integrated into CRIS to realize efficient retrieval. Third, our performance study indicates that the euR-tree is indeed effective in performing such retrieval with reduced query response times and disk I/Os.

R-tree

Tree (set theory)

10.1109/mdm.2015.47

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Citations (2)

Conclusions

River Publishers eBooks (2022)

Kannan Govindan Deepthi Chander Bhushan Jagyasi S. N. Merchant Uday B. Desai

10.1201/9781003357162-15

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Citations (0)

Blind Adaptive Weighted Aggregation Scheme for Event Detection in Multihop Wireless Sensor Networks

Wireless Personal Communications (2010)

Bhushan Jagyasi Deepthi Chander U.B. Desai S. N. Merchant Bikash Kumar Dey

Fusion center

Robustness

10.1007/s11277-010-0123-4

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Citations (1)

CrowdUtility: A Recommendation System for Crowdsourcing Platforms

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (2014)

Deepthi Chander Sakyajit Bhattacharya Elisa Celis Koustuv Dasgupta Saraschandra Karanam

Crowd workers exhibit varying work patterns, expertise, and quality leading to wide variability in the performance of crowdsourcing platforms. The onus of choosing a suitable platform to post tasks is mostly with the requester, often leading to poor guarantees and unmet requirements due to the dynamism in performance of crowd platforms. Towards this end, we demonstrate CrowdUtility, a statistical modelling based tool for evaluating multiple crowdsourcing platforms and recommending a platform that best suits the requirements of the requester. CrowdUtility uses an online Multi-Armed Bandit framework, to schedule tasks while optimizing platform performance. We demonstrate an end-to end system starting from requirements specification, to platform recommendation, to real-time monitoring.

Crowdsourcing

Dynamism

10.1609/hcomp.v2i1.13138

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Citations (1)

Post It or Not: Viewership Based Posting of Crowdsourced Tasks

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (2014)

Pallavi Manohar Deepthi Chander Elisa Celis Koustuv Dasgupta Sakyajit Bhattacharya

We propose an online scheduling algorithm for posting crowdsourcing tasks which maximizes a novel metric called task viewership. This metric is computed using stochastic model based on coverage process and it measures the likelihood that a task is viewed by multiple crowd workers, which is correlated to the likelihood that it will be selected and completed.

Crowdsourcing

Audience measurement

10.1609/hcomp.v2i1.13188

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Citations (0)

Distributed Detection in Wireless Sensor Networks: Preliminaries

River Publishers eBooks (2022)

Kannan Govindan Deepthi Chander Bhushan Jagyasi S. N. Merchant Uday B. Desai

10.1201/9781003357162-9

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Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

EURASIP Journal on Wireless Communications and Networking (2010)

Deepthi Chander Bhushan Jagyasi U.B. Desai S. N. Merchant

Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD) protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN). DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP) distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW) protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.

Waypoint

10.1155/2009/192985

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Citations (1)

SafeStreet: An automated road anomaly detection and early-warning system using mobile crowdsensing

Vikrant Singh Deepthi Chander Umang Chhaparia Bhaskaran Raman

In this work, we present SafeStreet, an automated road anomaly detection and early warning system. A pilot of SafeStreet was conducted by deploying the SafeStreet mobile app on 1800 cabs in Mumbai and Bengaluru. We discuss some of the design considerations and early results from our pilot study.

Crowdsensing

Early warning system

Mobile apps

Anomaly (physics)

10.1109/comsnets.2018.8328270

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Citations (14)

Improving Urban Transportation through Social Media Analytics

Manjira Sinha Preethy Varma Gayatri Sivakumar Mridula Singh Tridib Mukherjee

Citizens tend to discuss issues in public forums, social media, and web blogs. Given that issues related to public transportation are most actively reported across web-based sources, we present a holistic framework for collection, categorization, aggregation and visualization of urban public transportation issues. The primary challenges in deriving useful insights from web-based sources, stem from -- (a) the number of reports; (b) incomplete or implicit spatio-temporal context; and the (c) unstructured nature of text in these reports. The work initiates with the formal complaint data from the largest public transportation agency in Bangalore, complemented by complaint reports from web-based and social media sources. Text data is categorized into different transportation related problems and spatio-temporal context is added to the text data for geo-tagging and identifying persistent issues. A well-organized dashboard is developed for efficient visualization. The dashboard is currently being piloted with the largest transportation agency in Bangalore.

Dashboard

Complaint

10.1145/2888451.2888478

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Citations (1)