Agrawala, Ashok

Ashok Agrawala
Dept of Computer Science & Dept of Electrical Engineering
College of Computer, Mathematical and Natural Sciences
A.V. Williams Building, Room 4149
General Research Interests: 
  • Intergration Technologies
  • Context-Aware Systems
  • Context-Aware Security
  • Location Determination
  • PinPoint
  • Nuzzer
  • Time Synchronization Strategies


  • Integration Technologies
M-Urgency - redefining public safety:
Built on the Rover II platform, M-Urgency is a public safety system that significantly advances how emergency calls are handled. It connects a person with an emergency dispatcher with two-way audio and a one-way video stream. M-Urgency enables mobile users to stream live video from their devices to local PSAP along with the audio stream, the real time location information and any relevant information about the caller and the situation/environment around the point of event. M-Urgency demonstrates how effective and efficient emergency handling can be if the right contextual information is available to decision makers with a convenient interface to initiate the activities. M-Urgency presents information that facilitates time-critical decisions by the dispatcher and responder.
  • Context-Aware Systems
The Rover technology uses the Information Dynamics paradigm developed at the MIND Lab to provide a context-aware integration platform that is platform independent. The Rover infrastructure focuses on two major tasks: to expose as much contextual information as possible and to create services which need to communicate with each other and external sources, such as the Internet. We provide an easy to use application programming interface (API) that allows developers to create Rover-enabled applications with communication and messaging in mind.
We are currently working on Rover II, designed to support human decision making, keeping three essential features of context-aware systems in mind, namely customization,adaptability and interactivity. Based on the Rover Context Model (RoCoM), the framework allows the customization through user-specific context. With the idea of relevant context comes adaptability. Since, the system is designed to aid a human decision maker, it constantly interacts with him/her through a UI console. It is an integration and fusion platform that caters to the development of context-aware applications. It not only provides the means to store and retrieve contextual information, but also facilitates delivery of relevant services to applications to more effectively use the contextual information
  • Context-Aware Security
Context-aware security, in which context is utilized to allow security mechanisms to adjust based on the current situation, is essential to enabling effective security in dynamic and mobile computing environments. Our research focuses on studying how, and the extent to which, utilizing context enhances security, with a focus on access control.
  • Location Determination
Our research focuses on identifying the noisy characteristics of the wireless channel and developing techniques to overcome them to obtain accurate positioning. It is advantageous to run the location determination algorithm on the client devices to achieve privacy and decentralized implementation. Since these devices are usually energy constrained, it is important to reduce the computation requirements for location determination algorithms. We have developed location-clustering techniques based on the signal strength received from the access points to reduce the computational requirements of the location determination algorithm and allow the system to scale to large areas.
  • PinPoint
PinPoint is a distributed algorithm that enables a set of n nodes to determine the RF propagation delays between every pair of nodes, from which the inter-node distances and hence the spatial topology can be readily determined. PinPoint does not require any calibration of the area of interest and thus is rapidly deployable. Unlike existing time-of-arrival techniques, PinPoint does not require an infrastructure of accurate clocks (e.g., GPS) nor does it incur the o(n^2) message exchanges of .echoing. techniques. PinPoint can work with nodes having inexpensive crystal oscillator clocks, and incurs a constant number of message exchanges per node to determine the location of n nodes. Each node.s clock is assumed to run reliably but asynchronously with respect to the other nodes, i.e., they can run at slightly different rates because of hardware (oscillator) inaccuracies. PinPoint provides a mathematical way to compensate for these clock differences in order to arrive at a very precise timestamp recovery that in turn leads to a precise distance determination. Moreover, each node is able to determine the clock characteristics of other nodes in its neighborhood allowing network synchronization. Evaluation of the prototype in typical indoor and outdoor environments shows that PinPoint gives an average accuracy of four to six feet, in different environments, allowing PinPoint to support accurate rapidly deployable localization scenarios. We are collaborating with Oregano Systems and Austrian Academy of Sciences in developing timestamp based accurate location determination systems.
  • Nuzzer
Nuzzer focuses on exploiting the variability of signals sent in wireless networks due to the presence of objects, such as people. The ongoing goal is to determine whether or not we can determine the location of a particular person or persons. This technology currently uses fixed wireless transmitters and receivers at fixed locations that measure the signal strength of a particular area. Disturbances in the signal potentially indicate the presence of a foreign object in the area in question.
  • Time Synchronization Strategies
Cyclone Time Technology enables heterogeneous systems that include clocks of various inherent precision, resolution and stability to synchronize. Cyclone offers several advantages over the current master-slave based techniques by avoiding a single point of failure and achieving accuracy that does not depend on the actual local clock drift rates. Further, the use of only local information makes the scheme highly scalable.

In 1971, Dr. Agrawala joined the Department of Computer Science at the University of Maryland. He also holds joint positions with University of Maryland Institute for Advanced Computer Studies (UMIACS) and the Department of Electrical Engineering. For the past thirty Years, he has pursued research activities in the design, implementation and performance of computer systems. He is recognized for achievements in the areas of transient analysis of queues, distributed algorithms, and hard real-time systems design. Much of his research has gained national and corporate recognition through practical applications of his innovative solutions in these areas worldwide.

Achievements include:
  • Clustering for the characterization of workloads in computer systems, now a common approach in the design of benchmarks for computer procurements
  • Techniques for the transient analysis of queues leading to the solution of unsolved problems in the design and control of multi-computer systems
  • Introducing the Ricart/Agrawala algorithm for distributed mutual exclusion leading to major worldwide research activities
  • Development of the Maruti Operating System and program development environment demonstrating temporal guarantees of few tens of nanoseconds for making any software event happen while running on commercial Pentium processors
  • Development of Cyclone technology giving a jitter-free, loss-free delivery of data end-to-end in very high speed networks
  • Development of highly accurate location technology that allows users to locate objects within inches of specified coordinates both indoors and outdoors which will be the basis for one his MIND Lab proposed projects
  • Development and organization of the MIND Lab that he will direct.
He is the author of seven books and over two hundred technical papers.
Professor Agrawala has served as consultant to the UNDP, Government of India, and as a technical expert for legal casework. His research activities have been supported by various federal agencies including DARPA, NSF, and AFOSR. Corporate support has been received from IBM, Novell, AT&T, and others.
Professor Agrawala's former students includes more that thirty Ph.D. graduates who serve on the faculty of prestigious universities, as well as in nationally recognized industrial research labs and successful high tech companies operating both nationally and abroad.
Before joining the faculty of the Department of Computer Science, Professor Agrawala worked at Honeywell information Systems where he successfully designed an Optical Character Reader.
Professor Agrawala received B.E. and M.E. degrees in Electrical Engineering from Indian Institute of Sciences, Banglore, India; Masters and Ph.D. degrees in Applied Mathematics from Harvard University, Cambridge, Massachusetts. He is also a Fellow of the IEEE and a member of then ACM, AAAS, and Sigma Xi.