Topic
Communication complexity
About: Communication complexity is a research topic. Over the lifetime, 3870 publications have been published within this topic receiving 105832 citations.
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IBM1
TL;DR: A new protocol for Byzantine agreement in a completely asynchronous network is presented that makes use of cryptography, specifically of threshold signatures and coin-tossing protocols that is both practical and nearly matches the known theoretical lower bounds.
Abstract: Byzantine agreement requires a set of parties in a distributed system to agree on a value even if some parties are corrupted. A new protocol for Byzantine agreement in a completely asynchronous network is presented that makes use of cryptography, specifically of threshold signatures and coin-tossing protocols. These cryptographic protocols have practical and provably secure implementations in the “random oracle” model. In particular, a coin-tossing protocol based on the Diffie-Hellman problem is presented and analyzed.The resulting asynchronous Byzantine agreement protocol is both practical and nearly matches the known theoretical lower bounds. More precisely, it tolerates the maximum number of corrupted parties, runs in constant expected time, has message and communication complexity close to the maximum, and uses a trusted dealer only in a setup phase, after which it can process a virtually unlimited number of transactions. Novel dual-threshold variants of both cryptographic protocols are used.The protocol is formulated as a transaction processing service in a cryptographic security model, which differs from the standard information-theoretic formalization and may be of independent interest.
109 citations
TL;DR: Three different types of complexity lower bounds for the one-way unbounded-error and bounded-error error probabilistic communication protocols for boolean functions are proved.
108 citations
TL;DR: Two models of the cost of data movement in parallel numerical algorithms are described, one suitable for shared memory multiprocessors where each processor has vector capabilities and the other applicable to highly parallel nonshared memory MIMD systems.
Abstract: This paper describes two models of the cost of data movement in parallel numerical algorithms. One model is a generalization of an approach due to Hockney, and is suitable for shared memory multiprocessors where each processor has vector capabilities. The other model is applicable to highly parallel nonshared memory MIMD systems. In this second model, algorithm performance is characterized in terms of the communication network design. Techniques used in VLSI complexity theory are also brought in, and algorithm-independent upper bounds on system performance are derived for several problems that are important to scientific computation.
108 citations
22 Apr 2001
TL;DR: It is shown that small co-ordination buffers can eliminate the need for a centralized packet scheduling algorithm, allowing a full distributed implementation with low computational and communication complexity.
Abstract: A parallel packet switch (PPS) is a switch in which the memories run slower than the line rate. Arriving packets are spread (or load-balanced) packet-by-packet over multiple slower-speed packet switches. It is already known that with a speedup of S/spl ges/2, a PPS can theoretically mimic a FCFS output-queued (OQ) switch. However, the theory relies on a centralized packet scheduling algorithm that is essentially impractical because of high communication complexity. In this paper, we attempt to make a high performance PPS practical by introducing two results. First, we show that small co-ordination buffers can eliminate the need for a centralized packet scheduling algorithm, allowing a full distributed implementation with low computational and communication complexity. Second, we show that without speedup, the resulting PPS can mimic an FCFS OQ switch within a delay bound.
108 citations
TL;DR: A distributed recursive least-squares algorithm is developed for cooperative estimation using ad hoc wireless sensor networks, and computer simulations demonstrate that the theoretical findings are accurate also in the pragmatic settings whereby sensors acquire temporally-correlated data.
Abstract: The recursive least-squares (RLS) algorithm has well-documented merits for reducing complexity and storage requirements, when it comes to online estimation of stationary signals as well as for tracking slowly-varying nonstationary processes. In this paper, a distributed recursive least-squares (D-RLS) algorithm is developed for cooperative estimation using ad hoc wireless sensor networks. Distributed iterations are obtained by minimizing a separable reformulation of the exponentially-weighted least-squares cost, using the alternating-minimization algorithm. Sensors carry out reduced-complexity tasks locally, and exchange messages with one-hop neighbors to consent on the network-wide estimates adaptively. A steady-state mean-square error (MSE) performance analysis of D-RLS is conducted, by studying a stochastically-driven `averaged' system that approximates the D-RLS dynamics asymptotically in time. For sensor observations that are linearly related to the time-invariant parameter vector sought, the simplifying independence setting assumptions facilitate deriving accurate closed-form expressions for the MSE steady-state values. The problems of mean- and MSE-sense stability of D-RLS are also investigated, and easily-checkable sufficient conditions are derived under which a steady-state is attained. Without resorting to diminishing step-sizes which compromise the tracking ability of D-RLS, stability ensures that per sensor estimates hover inside a ball of finite radius centered at the true parameter vector, with high-probability, even when inter-sensor communication links are noisy. Interestingly, computer simulations demonstrate that the theoretical findings are accurate also in the pragmatic settings whereby sensors acquire temporally-correlated data.
108 citations