52,012 research outputs found
Dynamic sharing of a multiple access channel
In this paper we consider the mutual exclusion problem on a multiple access
channel. Mutual exclusion is one of the fundamental problems in distributed
computing. In the classic version of this problem, n processes perform a
concurrent program which occasionally triggers some of them to use shared
resources, such as memory, communication channel, device, etc. The goal is to
design a distributed algorithm to control entries and exits to/from the shared
resource in such a way that in any time there is at most one process accessing
it. We consider both the classic and a slightly weaker version of mutual
exclusion, called ep-mutual-exclusion, where for each period of a process
staying in the critical section the probability that there is some other
process in the critical section is at most ep. We show that there are channel
settings, where the classic mutual exclusion is not feasible even for
randomized algorithms, while ep-mutual-exclusion is. In more relaxed channel
settings, we prove an exponential gap between the makespan complexity of the
classic mutual exclusion problem and its weaker ep-exclusion version. We also
show how to guarantee fairness of mutual exclusion algorithms, i.e., that each
process that wants to enter the critical section will eventually succeed
Preserving Stabilization while Practically Bounding State Space
Stabilization is a key dependability property for dealing with unanticipated
transient faults, as it guarantees that even in the presence of such faults,
the system will recover to states where it satisfies its specification. One of
the desirable attributes of stabilization is the use of bounded space for each
variable. In this paper, we present an algorithm that transforms a stabilizing
program that uses variables with unbounded domain into a stabilizing program
that uses bounded variables and (practically bounded) physical time. While
non-stabilizing programs (that do not handle transient faults) can deal with
unbounded variables by assigning large enough but bounded space, stabilizing
programs that need to deal with arbitrary transient faults cannot do the same
since a transient fault may corrupt the variable to its maximum value. We show
that our transformation algorithm is applicable to several problems including
logical clocks, vector clocks, mutual exclusion, leader election, diffusing
computations, Paxos based consensus, and so on. Moreover, our approach can also
be used to bound counters used in an earlier work by Katz and Perry for adding
stabilization to a non-stabilizing program. By combining our algorithm with
that earlier work by Katz and Perry, it would be possible to provide
stabilization for a rich class of problems, by assigning large enough but
bounded space for variables.Comment: Moved some content from the Appendix to the main paper, added some
details to the transformation algorithm and to its descriptio
Distributed match-making
In many distributed computing environments, processes are concurrently executed by nodes in a store- and-forward communication network. Distributed control issues as diverse as name server, mutual exclusion, and replicated data management involve making matches between such processes. We propose a formal problem called distributed match-making as the generic paradigm. Algorithms for distributed match-making are developed and the complexity is investigated in terms of messages and in terms of storage needed. Lower bounds on the complexity of distributed match-making are established. Optimal algorithms, or nearly optimal algorithms, are given for particular network topologies
Extended Cognition, The New Mechanists’ Mutual Manipulability Criterion, and The Challenge of Trivial Extendedness
Many authors have turned their attention to the notion of constitution to determine whether the hypothesis of extended cognition (EC) is true. One common strategy is to make sense of constitution in terms of the new mechanists’ mutual manipulability account (MM). In this paper I will show that MM is insufficient. The Challenge of Trivial Extendedness arises due to the fact that mechanisms for cognitive behaviors are extended in a way that should not count as verifying EC. This challenge can be met by adding a necessary condition: cognitive constituents satisfy MM and they are what I call behavior unspecific
Understanding interdependency through complex information sharing
The interactions between three or more random variables are often nontrivial,
poorly understood, and yet, are paramount for future advances in fields such as
network information theory, neuroscience, genetics and many others. In this
work, we propose to analyze these interactions as different modes of
information sharing. Towards this end, we introduce a novel axiomatic framework
for decomposing the joint entropy, which characterizes the various ways in
which random variables can share information. The key contribution of our
framework is to distinguish between interdependencies where the information is
shared redundantly, and synergistic interdependencies where the sharing
structure exists in the whole but not between the parts. We show that our
axioms determine unique formulas for all the terms of the proposed
decomposition for a number of cases of interest. Moreover, we show how these
results can be applied to several network information theory problems,
providing a more intuitive understanding of their fundamental limits.Comment: 39 pages, 4 figure
Value Iteration for Long-run Average Reward in Markov Decision Processes
Markov decision processes (MDPs) are standard models for probabilistic
systems with non-deterministic behaviours. Long-run average rewards provide a
mathematically elegant formalism for expressing long term performance. Value
iteration (VI) is one of the simplest and most efficient algorithmic approaches
to MDPs with other properties, such as reachability objectives. Unfortunately,
a naive extension of VI does not work for MDPs with long-run average rewards,
as there is no known stopping criterion. In this work our contributions are
threefold. (1) We refute a conjecture related to stopping criteria for MDPs
with long-run average rewards. (2) We present two practical algorithms for MDPs
with long-run average rewards based on VI. First, we show that a combination of
applying VI locally for each maximal end-component (MEC) and VI for
reachability objectives can provide approximation guarantees. Second, extending
the above approach with a simulation-guided on-demand variant of VI, we present
an anytime algorithm that is able to deal with very large models. (3) Finally,
we present experimental results showing that our methods significantly
outperform the standard approaches on several benchmarks
Separation of Circulating Tokens
Self-stabilizing distributed control is often modeled by token abstractions.
A system with a single token may implement mutual exclusion; a system with
multiple tokens may ensure that immediate neighbors do not simultaneously enjoy
a privilege. For a cyber-physical system, tokens may represent physical objects
whose movement is controlled. The problem studied in this paper is to ensure
that a synchronous system with m circulating tokens has at least d distance
between tokens. This problem is first considered in a ring where d is given
whilst m and the ring size n are unknown. The protocol solving this problem can
be uniform, with all processes running the same program, or it can be
non-uniform, with some processes acting only as token relays. The protocol for
this first problem is simple, and can be expressed with Petri net formalism. A
second problem is to maximize d when m is given, and n is unknown. For the
second problem, the paper presents a non-uniform protocol with a single
corrective process.Comment: 22 pages, 7 figures, epsf and pstricks in LaTe
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