Communication complexity

About: Communication complexity is a research topic. Over the lifetime, 3870 publications have been published within this topic receiving 105832 citations.

Exponential Separation of Information and Communication.

Abstract: We show an exponential gap between communication complexity and information complexity, by giving an explicit example for a communication task (relation), with information complexity ≤ O(k), and distributional communication complexity ≥ 2k. This shows that a communication protocol cannot always be compressed to its internal information. By a result of Braverman [1], our gap is the largest possible. By a result of Braverman and Rao [2], our example shows a gap between communication complexity and amortized communication complexity, implying that a tight direct sum result for distributional communication complexity cannot hold.

Quantum communication with coherent states and linear optics

Abstract: that use only a sequence of coherent states, linear optics operations, and measurements with single-photon threshold detectors. The new class of protocols requires a number of optical modes equal to the dimension of the original states, but the total number of photons can be chosen independently from the dimension and is typically very small. The protocols obtained from the mapping share important properties with the original ones, meaning that they can also full the goal that the original protocols where intended to achieve. Overall, the mapping is suitable for its application to protocols that originally require a moderate number of qubits, but are still hard to implement with usual methods. In the remainder of this paper, we describe the mapping in detail and discuss the various properties of the coherent-state protocols. We proceed by examining how the mapping can be applied to construct protocols in quantum communication complexity and describe protocols for the hidden matching problem and for quantum digital signatures, both of which can be realized with technology that is within current reach.

More Efficient Oblivious Transfer and Extensions for Faster Secure Computation.

Abstract: Protocols for secure computation enable parties to compute a joint function on their private inputs without revealing anything but the result. A foundation for secure computation is oblivious transfer (OT), which traditionally requires expensive public key cryptography. A more efficient way to perform many OTs is to extend a small number of base OTs using OT extensions based on symmetric cryptography. In this work we present optimizations and efficient implementations of OT and OT extensions in the semi-honest model. We propose a novel OT protocol with security in the standard model and improve OT extensions with respect to communication complexity, computation complexity, and scalability. We also provide specific optimizations of OT extensions that are tailored to the secure computation protocols of Yao and GoldreichMicali-Wigderson and reduce the communication complexity even further. We experimentally verify the efficiency gains of our protocols and optimizations. By applying our implementation to current secure computation frameworks, we can securely compute a Levenshtein distance circuit with 1.29 billion AND gates at a rate of 1.2 million AND gates per second. Moreover, we demonstrate the importance of correctly implementing OT within secure computation protocols by presenting an attack on the FastGC framework.

Lean and mean: network coding for commercial devices

Abstract: With its ability to reduce the number of transmissions in lossy networks as well as its potential to simplify the design and required signaling of communication protocols, network coding has emerged as an attractive solution to harness the power of wireless and cooperative networks in order to provide higher throughput and lower energy expenditure. This article shows that network coding's complexity is not an issue for current mobile devices even without hardware acceleration. We provide real-life measurements of energy savings gains of two design styles of network coding, namely, inter- and intra-session network coding using commercial platforms, including Open-Mesh routers and various mobile phones. We demonstrate that the energy per bit invested in coding/decoding operations can be several orders of magnitude smaller than that used for transmission/reception, while also maintaining processing speeds as high as several hundreds of Mb/s or even several Gb/s depending on the device and coding configuration used.

On Complexity, Energy- and Implementation-Efficiency of Channel Decoders

Abstract: Future wireless communication systems require efficient and flexible baseband receivers. Meaningful efficiency metrics are key for design space exploration to quantify the algorithmic and the implementation complexity of a receiver. Most of the current established efficiency metrics are based on counting operations, thus neglecting important issues like data and storage complexity. In this paper we introduce suitable energy and area efficiency metrics which resolve the afore-mentioned disadvantages. These are decoded information bit per energy and throughput per area unit. Efficiency metrics are assessed by various implementations of turbo decoders, LDPC decoders and convolutional decoders. An exploration approach is presented, which permit an appropriate benchmarking of implementation efficiency, communications performance, and flexibility trade-offs. Two case studies demonstrate this approach and show that design space exploration should result in various efficiency evaluations rather than a single snapshot metric as done often in state-of-the-art approaches.