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Ajay D. Kshemkalyani

Researcher at University of Illinois at Chicago

Publications -  163
Citations -  3419

Ajay D. Kshemkalyani is an academic researcher from University of Illinois at Chicago. The author has contributed to research in topics: Distributed algorithm & Vector clock. The author has an hindex of 24, co-authored 156 publications receiving 3192 citations. Previous affiliations of Ajay D. Kshemkalyani include Ohio State University & University of Cincinnati.

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Journal ArticleDOI

Clock synchronization for wireless sensor networks: a survey

TL;DR: In this paper, a survey and evaluation of clock synchronization protocols based on a palette of factors such as precision, accuracy, cost, and complexity is presented, which can help developers either in choosing an existing synchronization protocol or in defining a new protocol that is best suited to the specific needs of a sensor network application.
MonographDOI

Distributed Computing: Principles, Algorithms, and Systems

TL;DR: This comprehensive textbook covers the fundamental principles and models underlying the theory, algorithms and systems aspects of distributed computing, and is suitable for advanced undergraduate and graduate students of electrical and computer engineering and computer science.
Journal ArticleDOI

An efficient implementation of vector clocks

TL;DR: This work presents an efficient implementation of vector clocks that reduces the size of timestamp related information to be transferred in a message and is resilient to changes in the topology of the distributed system.
Journal ArticleDOI

Efficient detection and resolution of generalized distributed deadlocks

TL;DR: An efficient one-phase algorithm that consists of two concurrent sweeps of messages to detect generalized distributed deadlocks and it is proved that the correctness of the algorithm is proved.
Journal ArticleDOI

Necessary and sufficient conditions on information for causal message ordering and their optimal implementation

TL;DR: The paper presents an algorithm for enforcing causal message ordering that allows a process to multicast to arbitrary and dynamically changing process groups, and shows that the algorithm is optimal in the space complexity of the overhead of control information in both messages and message logs.