38 research outputs found
Complexity of Multi-Value Byzantine Agreement
In this paper, we consider the problem of maximizing the throughput of
Byzantine agreement, given that the sum capacity of all links in between nodes
in the system is finite. We have proposed a highly efficient Byzantine
agreement algorithm on values of length l>1 bits. This algorithm uses error
detecting network codes to ensure that fault-free nodes will never disagree,
and routing scheme that is adaptive to the result of error detection. Our
algorithm has a bit complexity of n(n-1)l/(n-t), which leads to a linear cost
(O(n)) per bit agreed upon, and overcomes the quadratic lower bound
(Omega(n^2)) in the literature. Such linear per bit complexity has only been
achieved in the literature by allowing a positive probability of error. Our
algorithm achieves the linear per bit complexity while guaranteeing agreement
is achieved correctly even in the worst case. We also conjecture that our
algorithm can be used to achieve agreement throughput arbitrarily close to the
agreement capacity of a network, when the sum capacity is given
Deterministic Consensus Algorithm with Linear Per-Bit Complexity
In this report, building on the deterministic multi-valued one-to-many
Byzantine agreement (broadcast) algorithm in our recent technical report [2],
we introduce a deterministic multi-valued all-to-all Byzantine agreement
algorithm (consensus), with linear complexity per bit agreed upon. The
discussion in this note is not self-contained, and relies heavily on the
material in [2] - please refer to [2] for the necessary background
TOFEC: Achieving Optimal Throughput-Delay Trade-off of Cloud Storage Using Erasure Codes
Our paper presents solutions using erasure coding, parallel connections to
storage cloud and limited chunking (i.e., dividing the object into a few
smaller segments) together to significantly improve the delay performance of
uploading and downloading data in and out of cloud storage.
TOFEC is a strategy that helps front-end proxy adapt to level of workload by
treating scalable cloud storage (e.g. Amazon S3) as a shared resource requiring
admission control. Under light workloads, TOFEC creates more smaller chunks and
uses more parallel connections per file, minimizing service delay. Under heavy
workloads, TOFEC automatically reduces the level of chunking (fewer chunks with
increased size) and uses fewer parallel connections to reduce overhead,
resulting in higher throughput and preventing queueing delay. Our trace-driven
simulation results show that TOFEC's adaptation mechanism converges to an
appropriate code that provides the optimal delay-throughput trade-off without
reducing system capacity. Compared to a non-adaptive strategy optimized for
throughput, TOFEC delivers 2.5x lower latency under light workloads; compared
to a non-adaptive strategy optimized for latency, TOFEC can scale to support
over 3x as many requests
On Diagnosis of Forwarding Plane via Static Forwarding Rules in Software Defined Networks
Software Defined Networks (SDN) decouple the forwarding and control planes
from each other. The control plane is assumed to have a global knowledge of the
underlying physical and/or logical network topology so that it can monitor,
abstract and control the forwarding plane. In our paper, we present solutions
that install an optimal or near-optimal (i.e., within 14% of the optimal)
number of static forwarding rules on switches/routers so that any controller
can verify the topology connectivity and detect/locate link failures at data
plane speeds without relying on state updates from other controllers. Our upper
bounds on performance indicate that sub-second link failure localization is
possible even at data-center scale networks. For networks with hundreds or few
thousand links, tens of milliseconds of latency is achievable.Comment: Submitted to Infocom'14, 9 page
New Efficient Error-Free Multi-Valued Consensus with Byzantine Failures
In this report, we investigate the multi-valued Byzantine consensus problem.
We introduce two algorithms: the first one achieves traditional validity
requirement for consensus, and the second one achieves a stronger "q-validity"
requirement. Both algorithms are more efficient than the ones introduces in our
recent PODC 2011 paper titled "Error-Free Multi-Valued Consensus with Byzantine
Failures"