185,803 research outputs found
Randomized protocols for asynchronous consensus
The famous Fischer, Lynch, and Paterson impossibility proof shows that it is
impossible to solve the consensus problem in a natural model of an asynchronous
distributed system if even a single process can fail. Since its publication,
two decades of work on fault-tolerant asynchronous consensus algorithms have
evaded this impossibility result by using extended models that provide (a)
randomization, (b) additional timing assumptions, (c) failure detectors, or (d)
stronger synchronization mechanisms than are available in the basic model.
Concentrating on the first of these approaches, we illustrate the history and
structure of randomized asynchronous consensus protocols by giving detailed
descriptions of several such protocols.Comment: 29 pages; survey paper written for PODC 20th anniversary issue of
Distributed Computin
The Role of Inter-Controller Traffic for Placement of Distributed SDN Controllers
We consider a distributed Software Defined Networking (SDN) architecture
adopting a cluster of multiple controllers to improve network performance and
reliability. Besides the Openflow control traffic exchanged between controllers
and switches, we focus on the control traffic exchanged among the controllers
in the cluster, needed to run coordination and consensus algorithms to keep the
controllers synchronized. We estimate the effect of the inter-controller
communications on the reaction time perceived by the switches depending on the
data-ownership model adopted in the cluster. The model is accurately validated
in an operational Software Defined WAN (SDWAN). We advocate a careful placement
of the controllers, that should take into account both the above kinds of
control traffic. We evaluate, for some real ISP network topologies, the delay
tradeoffs for the controllers placement problem and we propose a novel
evolutionary algorithm to find the corresponding Pareto frontier. Our work
provides novel quantitative tools to optimize the planning and the design of
the network supporting the control plane of SDN networks, especially when the
network is very large and in-band control plane is adopted. We also show that
for operational distributed controllers (e.g. OpenDaylight and ONOS), the
location of the controller which acts as a leader in the consensus algorithm
has a strong impact on the reactivity perceived by switches.Comment: 14 page
An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A novel framework to prevent manipulation behaviour
in consensus reaching process under social network
group decision making is proposed, which is based on a theoretically
sound optimal feedback model. The manipulation
behaviour classification is twofold: (1) ‘individual manipulation’
where each expert manipulates his/her own behaviour to achieve
higher importance degree (weight); and (2) ‘group manipulation’
where a group of experts force inconsistent experts to adopt
specific recommendation advices obtained via the use of fixed
feedback parameter. To counteract ‘individual manipulation’, a
behavioural weights assignment method modelling sequential
attitude ranging from ‘dictatorship’ to ‘democracy’ is developed,
and then a reasonable policy for group minimum adjustment cost
is established to assign appropriate weights to experts. To prevent
‘group manipulation’, an optimal feedback model with objective
function the individual adjustments cost and constraints related
to the threshold of group consensus is investigated. This approach
allows the inconsistent experts to balance group consensus and
adjustment cost, which enhances their willingness to adopt the
recommendation advices and consequently the group reaching
consensus on the decision making problem at hand. A numerical
example is presented to illustrate and verify the proposed optimal
feedback model
CHANGE AND FIRM VALUATION IN U.S. FOOD RETAILING AND MANUFACTURING
The competitive environment in the agri-food sector is evolving as the food manufacturing and retailing industries become more concentrated. Evolving industry structure and new firm investment portend changes in future firm competitiveness and performance. This research describes how large food-manufacturing and retail firm performance has shifted and how firm valuation signals expected future change in performance. While there have been expectations that return on investment of large food retailers would increase relative to large packaged-food manufacturers, we find that this has not yet happened and that market valuations imply that retailers are not likely to gain on manufacturers in the future.Agribusiness,
Distributed Random Convex Programming via Constraints Consensus
This paper discusses distributed approaches for the solution of random convex
programs (RCP). RCPs are convex optimization problems with a (usually large)
number N of randomly extracted constraints; they arise in several applicative
areas, especially in the context of decision under uncertainty, see [2],[3]. We
here consider a setup in which instances of the random constraints (the
scenario) are not held by a single centralized processing unit, but are
distributed among different nodes of a network. Each node "sees" only a small
subset of the constraints, and may communicate with neighbors. The objective is
to make all nodes converge to the same solution as the centralized RCP problem.
To this end, we develop two distributed algorithms that are variants of the
constraints consensus algorithm [4],[5]: the active constraints consensus (ACC)
algorithm, and the vertex constraints consensus (VCC) algorithm. We show that
the ACC algorithm computes the overall optimal solution in finite time, and
with almost surely bounded communication at each iteration. The VCC algorithm
is instead tailored for the special case in which the constraint functions are
convex also w.r.t. the uncertain parameters, and it computes the solution in a
number of iterations bounded by the diameter of the communication graph. We
further devise a variant of the VCC algorithm, namely quantized vertex
constraints consensus (qVCC), to cope with the case in which communication
bandwidth among processors is bounded. We discuss several applications of the
proposed distributed techniques, including estimation, classification, and
random model predictive control, and we present a numerical analysis of the
performance of the proposed methods. As a complementary numerical result, we
show that the parallel computation of the scenario solution using ACC algorithm
significantly outperforms its centralized equivalent
ARES: Adaptive, Reconfigurable, Erasure coded, atomic Storage
Atomicity or strong consistency is one of the fundamental, most intuitive,
and hardest to provide primitives in distributed shared memory emulations. To
ensure survivability, scalability, and availability of a storage service in the
presence of failures, traditional approaches for atomic memory emulation, in
message passing environments, replicate the objects across multiple servers.
Compared to replication based algorithms, erasure code-based atomic memory
algorithms has much lower storage and communication costs, but usually, they
are harder to design. The difficulty of designing atomic memory algorithms
further grows, when the set of servers may be changed to ensure survivability
of the service over software and hardware upgrades, while avoiding service
interruptions. Atomic memory algorithms for performing server reconfiguration,
in the replicated systems, are very few, complex, and are still part of an
active area of research; reconfigurations of erasure-code based algorithms are
non-existent.
In this work, we present ARES, an algorithmic framework that allows
reconfiguration of the underlying servers, and is particularly suitable for
erasure-code based algorithms emulating atomic objects. ARES introduces new
configurations while keeping the service available. To use with ARES we also
propose a new, and to our knowledge, the first two-round erasure code based
algorithm TREAS, for emulating multi-writer, multi-reader (MWMR) atomic objects
in asynchronous, message-passing environments, with near-optimal communication
and storage costs. Our algorithms can tolerate crash failures of any client and
some fraction of servers, and yet, guarantee safety and liveness property.
Moreover, by bringing together the advantages of ARES and TREAS, we propose an
optimized algorithm where new configurations can be installed without the
objects values passing through the reconfiguration clients
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