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Everywhere-tight information cost tradeoffs for augmented index

By Amit Chakrabarti, Graham Cormode, Ranganath Kondapally and Andrew Mcgregor


Abstract. This paper makes three main contributions to the theory of communication complexity and stream computation. First, we present new bounds on the information complexity of augmented-index. In contrast to analogous results for index by Jain, Radhakrishnan, and Sen [J. ACM, 56 (2009), article 33], we have to overcome the significant technical challenge that protocols for augmented-index may violate the “rectangle property ” due to the inherent input sharing. Second, we use these bounds to resolve an open problem of Magniez, Mathieu, and Nayak [Proceedings of the 42nd Annual ACM Symposium on Theory of Computing, 2010, pp. 261–270] that asked about the multipass complexity of recognizing Dyck languages. This results in a natural separation between the standard multipass model and the multipass model that permits reverse passes. Third, we present the first passive memory checkers that verify the interaction transcripts of priority queues, stacks, and double-ended queues. We obtain tight upper and lower bounds for these problems, thereby addressing an important subclass of the memory checking framework of Blum et al. [Algorithmica, 12 (1994), pp. 225–244]

Topics: Key words. communication complexity, lower bounds, data streams, memory checking
Year: 2013
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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