20 research outputs found
Verifying Computations with Streaming Interactive Proofs
When computation is outsourced, the data owner would like to be assured that
the desired computation has been performed correctly by the service provider.
In theory, proof systems can give the necessary assurance, but prior work is
not sufficiently scalable or practical. In this paper, we develop new proof
protocols for verifying computations which are streaming in nature: the
verifier (data owner) needs only logarithmic space and a single pass over the
input, and after observing the input follows a simple protocol with a prover
(service provider) that takes logarithmic communication spread over a
logarithmic number of rounds. These ensure that the computation is performed
correctly: that the service provider has not made any errors or missed out some
data. The guarantee is very strong: even if the service provider deliberately
tries to cheat, there is only vanishingly small probability of doing so
undetected, while a correct computation is always accepted. We first observe
that some theoretical results can be modified to work with streaming verifiers,
showing that there are efficient protocols for problems in the complexity
classes NP and NC. Our main results then seek to bridge the gap between theory
and practice by developing usable protocols for a variety of problems of
central importance in streaming and database processing. All these problems
require linear space in the traditional streaming model, and therefore our
protocols demonstrate that adding a prover can exponentially reduce the effort
needed by the verifier. Our experimental results show that our protocols are
practical and scalable.Comment: VLDB201
An Improved Interactive Streaming Algorithm for the Distinct Elements Problem
The exact computation of the number of distinct elements (frequency moment
) is a fundamental problem in the study of data streaming algorithms. We
denote the length of the stream by where each symbol is drawn from a
universe of size . While it is well known that the moments can
be approximated by efficient streaming algorithms, it is easy to see that exact
computation of requires space . In previous work, Cormode
et al. therefore considered a model where the data stream is also processed by
a powerful helper, who provides an interactive proof of the result. They gave
such protocols with a polylogarithmic number of rounds of communication between
helper and verifier for all functions in NC. This number of rounds
can quickly make such
protocols impractical.
Cormode et al. also gave a protocol with rounds for the exact
computation of where the space complexity is but the total communication . They managed to give round protocols with
complexity for many other interesting problems
including , Inner product, and Range-sum, but computing exactly with
polylogarithmic space and communication and rounds remained open.
In this work, we give a streaming interactive protocol with rounds
for exact computation of using bits of space and the communication is . The update
time of the verifier per symbol received is .Comment: Submitted to ICALP 201
Semi-Streaming Algorithms for Annotated Graph Streams
Considerable effort has been devoted to the development of streaming
algorithms for analyzing massive graphs. Unfortunately, many results have been
negative, establishing that a wide variety of problems require
space to solve. One of the few bright spots has been the development of
semi-streaming algorithms for a handful of graph problems -- these algorithms
use space .
In the annotated data streaming model of Chakrabarti et al., a
computationally limited client wants to compute some property of a massive
input, but lacks the resources to store even a small fraction of the input, and
hence cannot perform the desired computation locally. The client therefore
accesses a powerful but untrusted service provider, who not only performs the
requested computation, but also proves that the answer is correct.
We put forth the notion of semi-streaming algorithms for annotated graph
streams (semi-streaming annotation schemes for short). These are protocols in
which both the client's space usage and the length of the proof are . We give evidence that semi-streaming annotation schemes
represent a substantially more robust solution concept than does the standard
semi-streaming model. On the positive side, we give semi-streaming annotation
schemes for two dynamic graph problems that are intractable in the standard
model: (exactly) counting triangles, and (exactly) computing maximum matchings.
The former scheme answers a question of Cormode. On the negative side, we
identify for the first time two natural graph problems (connectivity and
bipartiteness in a certain edge update model) that can be solved in the
standard semi-streaming model, but cannot be solved by annotation schemes of
"sub-semi-streaming" cost. That is, these problems are just as hard in the
annotations model as they are in the standard model.Comment: This update includes some additional discussion of the results
proven. The result on counting triangles was previously included in an ECCC
technical report by Chakrabarti et al. available at
http://eccc.hpi-web.de/report/2013/180/. That report has been superseded by
this manuscript, and the CCC 2015 paper "Verifiable Stream Computation and
Arthur-Merlin Communication" by Chakrabarti et a
Streaming Verification of Graph Properties
Streaming interactive proofs (SIPs) are a framework for outsourced
computation. A computationally limited streaming client (the verifier) hands
over a large data set to an untrusted server (the prover) in the cloud and the
two parties run a protocol to confirm the correctness of result with high
probability. SIPs are particularly interesting for problems that are hard to
solve (or even approximate) well in a streaming setting. The most notable of
these problems is finding maximum matchings, which has received intense
interest in recent years but has strong lower bounds even for constant factor
approximations.
In this paper, we present efficient streaming interactive proofs that can
verify maximum matchings exactly. Our results cover all flavors of matchings
(bipartite/non-bipartite and weighted). In addition, we also present streaming
verifiers for approximate metric TSP. In particular, these are the first
efficient results for weighted matchings and for metric TSP in any streaming
verification model.Comment: 26 pages, 2 figure, 1 tabl
A Time-Space Tradeoff for the Sumcheck Prover
The sumcheck protocol is an interactive protocol for verifying the sum of a low-degree polynomial over a hypercube. This protocol is widely used in practice, where an efficient implementation of the (honest) prover algorithm is paramount. Prior work contributes highly-efficient prover algorithms for the notable special case of multilinear polynomials (and related settings): [CTY11] uses logarithmic space but runs in superlinear time; in contrast, [VSBW13] runs in linear time but uses linear space.
In this short note, we present a family of prover algorithms for the multilinear sumcheck protocol that offer new time-space tradeoffs. In particular, we recover the aforementioned algorithms as special cases. Moreover, we provide an efficient implementation of the new algorithms, and our experiments show that the asymptotics translate into new concrete efficiency tradeoffs