12 research outputs found
Decentralization in Bitcoin and Ethereum Networks
Blockchain-based cryptocurrencies have demonstrated how to securely implement
traditionally centralized systems, such as currencies, in a decentralized
fashion. However, there have been few measurement studies on the level of
decentralization they achieve in practice. We present a measurement study on
various decentralization metrics of two of the leading cryptocurrencies with
the largest market capitalization and user base, Bitcoin and Ethereum. We
investigate the extent of decentralization by measuring the network resources
of nodes and the interconnection among them, the protocol requirements
affecting the operation of nodes, and the robustness of the two systems against
attacks. In particular, we adapted existing internet measurement techniques and
used the Falcon Relay Network as a novel measurement tool to obtain our data.
We discovered that neither Bitcoin nor Ethereum has strictly better properties
than the other. We also provide concrete suggestions for improving both
systems.Comment: Financial Cryptography and Data Security 201
DMFSGD: A Decentralized Matrix Factorization Algorithm for Network Distance Prediction
The knowledge of end-to-end network distances is essential to many Internet
applications. As active probing of all pairwise distances is infeasible in
large-scale networks, a natural idea is to measure a few pairs and to predict
the other ones without actually measuring them. This paper formulates the
distance prediction problem as matrix completion where unknown entries of an
incomplete matrix of pairwise distances are to be predicted. The problem is
solvable because strong correlations among network distances exist and cause
the constructed distance matrix to be low rank. The new formulation circumvents
the well-known drawbacks of existing approaches based on Euclidean embedding.
A new algorithm, so-called Decentralized Matrix Factorization by Stochastic
Gradient Descent (DMFSGD), is proposed to solve the network distance prediction
problem. By letting network nodes exchange messages with each other, the
algorithm is fully decentralized and only requires each node to collect and to
process local measurements, with neither explicit matrix constructions nor
special nodes such as landmarks and central servers. In addition, we compared
comprehensively matrix factorization and Euclidean embedding to demonstrate the
suitability of the former on network distance prediction. We further studied
the incorporation of a robust loss function and of non-negativity constraints.
Extensive experiments on various publicly-available datasets of network delays
show not only the scalability and the accuracy of our approach but also its
usability in real Internet applications.Comment: submitted to IEEE/ACM Transactions on Networking on Nov. 201
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems
Mobile edge computing (MEC) is a promising technique for providing low-latency access to services at the network
edge. The services are hosted at various types of edge nodes
with both computation and communication capabilities. Due to
the heterogeneity of edge node characteristics and user locations,
the performance of MEC varies depending on where the service
is hosted. In this paper, we consider such a heterogeneous MEC
system, and focus on the problem of placing multiple services
in the system to maximize the total reward. We show that the
problem is NP-hard via reduction from the set cover problem,
and propose a deterministic approximation algorithm to solve
the problem, which has an approximation ratio that is not worse
than (1 − e−1)/4. The proposed algorithm is based on two subroutines that are suitable for small and arbitrarily sized services,
respectively. The algorithm is designed using a novel way of
partitioning each edge node into multiple slots, where each slot
contains one service. The approximation guarantee is obtained
via a specialization of the method of conditional expectations,
which uses a randomized procedure as an intermediate step. In
addition to theoretical guarantees, simulation results also show
that the proposed algorithm outperforms other state-of-the-art
approache