Algorithms for interactive, distributed and networked systems

In recent years, massive growth in internet usage has spurred the emergence of complex large-scale networking systems to serve growing user bases, bandwidth and computation requirements. For example, data center facilities -- workhorses of today's internet -- have evolved to house upward of several hundreds of thousands of servers; content distribution networks with high capacity and wide coverage have emerged as a de facto content dissemination modality, and peer-to-peer applications with hundreds of thousands of users are increasingly becoming popular. At these scales, it becomes critical to operate at high efficiencies as the price of idling resources can be significant. In particular, the interaction between agents (servers, peers etc.) is a defining factor of efficiency in these systems -- applications are often communication intensive, whereas agents share links of only limited bandwidth. This necessitates the use of principled algorithms, as efficient communication to a large extent depends on the interaction protocols. We study data center networks and peer-to-peer networks as canonical examples of modern-day large-scale networking systems. Server-to-server interaction is an integral part of the data center's operation. The latency of these interactions is often a significant bottleneck toward overall job completion times. We study complementary approaches toward reducing this latency: (i) design of computation algorithms that minimize interaction and (ii) optimal scheduling algorithms to maximally utilize the network fabric. We also consider peer-to-peer networks as an emerging mode of content distribution and sharing. Unlike data centers, these networks are flexible in their network structure and also scale well, but require decentralized algorithms for control. Of central importance here is the design of a network topology that enables efficient peer interactions for optimal application performance. We propose novel topology designs for two popular applications: (i) multimedia streaming and (ii) anonymity in Bitcoin's peer-to-peer network

An interference alignment scheme for multiple multicast traffic

We propose a new coding scheme for interference alignment in a single hop fast fading wireless network with general message demands. For the X Channel, the Degrees of Freedom (DoF) region achievable by the scheme is shown to touch a known outer bound at several points. For multiple multicast demands we show that the achievable region is at least half of the cut-set bound region. We also recover previous results of the K-user interference channel, X channel and the multicast channel. The key innovation in our scheme is the reduction of the vector space alignment problem to a combinatorial arrangement problem

Less is More: Fairness in Wide-Area Proof-of-Work Blockchain Networks

Blockchain is rapidly emerging as an important class of network application, with a unique set of trust, security and transparency properties. In a blockchain system, participants record and update the `server-side' state of an application as blocks of a replicated, immutable ledger using a consensus protocol over the Internet. Mining blocks has become lucrative in recent years; e.g., a miner receives over USD 200,000 per mined block in Bitcoin today. A key factor affecting mining rewards, is the latency of broadcasting blocks over the network. In this paper, we consider the problem of topology design for optimizing mining rewards in a wide-area blockchain network that uses a Proof-of-Work protocol for consensus. Contrary to general wisdom that a faster network is always better for miners, we show a counter intuitive result where a slower network is actually beneficial to some miners. This is because competing miners must choose neighbors that not only decrease their own latency to others, but also ensure that the latency between other miners do not decrease because of itself. We formalize this problem, and provide both theoretical analysis and experimental results to support our claim

DecVi: Adaptive Video Conferencing on Open Peer-to-Peer Networks

Video conferencing has become the preferred way of interacting virtually. Current video conferencing applications, like Zoom, Teams or WebEx, are centralized, cloud-based platforms whose performance crucially depends on the proximity of clients to their data centers. Clients from low-income countries are particularly affected as most data centers from major cloud providers are located in economically advanced nations. Centralized conferencing applications also suffer from occasional outages and are embattled by serious privacy violation allegations. In recent years, decentralized video conferencing applications built over p2p networks and incentivized through blockchain are becoming popular. A key characteristic of these networks is their openness: anyone can host a media server on the network and gain reward for providing service. Strong economic incentives combined with lower entry barrier to join the network, makes increasing server coverage to even remote regions of the world. These reasons, however, also lead to a security problem: a server may obfuscate its true location in order to gain an unfair business advantage. In this paper, we consider the problem of multicast tree construction for video conferencing sessions in open p2p conferencing applications. We propose DecVi, a decentralized multicast tree construction protocol that adaptively discovers efficient tree structures based on an exploration-exploitation framework. DecVi is motivated by the combinatorial multi-armed bandit problem and uses a succinct learning model to compute effective actions. Despite operating in a multi-agent setting with each server having only limited knowledge of the global network and without cooperation among servers, experimentally we show DecVi achieves similar quality-of-experience compared to a centralized globally optimal algorithm while achieving higher reliability and flexibility

Kadabra: Adapting Kademlia for the Decentralized Web

Blockchains have become the catalyst for a growing movement to create a more decentralized Internet. A fundamental operation of applications in a decentralized Internet is data storage and retrieval. As today's blockchains are limited in their storage functionalities, in recent years a number of peer-to-peer data storage networks have emerged based on the Kademlia distributed hash table protocol. However, existing Kademlia implementations are not efficient enough to support fast data storage and retrieval operations necessary for (decentralized) Web applications. In this paper, we present Kadabra, a decentralized protocol for computing the routing table entries in Kademlia to accelerate lookups. Kadabra is motivated by the multi-armed bandit problem, and can automatically adapt to heterogeneity and dynamism in the network. Experimental results show Kadabra achieving between 15-50% lower lookup latencies compared to state-of-the-art baselines.Comment: 26 pages, 19 figure