221 research outputs found
Prototyping Formal System Models with Active Objects
We propose active object languages as a development tool for formal system
models of distributed systems. Additionally to a formalization based on a term
rewriting system, we use established Software Engineering concepts, including
software product lines and object orientation that come with extensive tool
support. We illustrate our modeling approach by prototyping a weak memory
model. The resulting executable model is modular and has clear interfaces
between communicating participants through object-oriented modeling.
Relaxations of the basic memory model are expressed as self-contained variants
of a software product line. As a modeling language we use the formal active
object language ABS which comes with an extensive tool set. This permits rapid
formalization of core ideas, early validity checks in terms of formal invariant
proofs, and debugging support by executing test runs. Hence, our approach
supports the prototyping of formal system models with early feedback.Comment: In Proceedings ICE 2018, arXiv:1810.0205
Attributes of fault-tolerant distributed file systems
Fault tolerance in distributed file systems will be investigated by analyzing recovery techniques and concepts implemented within the following models of distributed systems: pool-processor model and user-server model. The research presented provides an overview of fault tolerance characteristics and mechanisms within current implementations and summarizes future directions for fault tolerant distributed file systems
Rigorous Design of Fault-Tolerant Transactions for Replicated Database Systems using Event B
System availability is improved by the replication of data objects in a distributed database system. However, during updates, the complexity of keeping replicas identical arises due to failures of sites and race conditions among conflicting transactions. Fault tolerance and reliability are key issues to be addressed in the design and architecture of these systems. Event B is a formal technique which provides a framework for developing mathematical models of distributed systems by rigorous description of the problem, gradually introducing solutions in refinement steps, and verification of solutions by discharge of proof obligations. In this paper, we present a formal development of a distributed system using Event B that ensures atomic commitment of distributed transactions consisting of communicating transaction components at participating sites. This formal approach carries the development of the system from an initial abstract specification of transactional updates on a one copy database to a detailed design containing replicated databases in refinement. Through refinement we verify that the design of the replicated database confirms to the one copy database abstraction
Програмування в обмеженнях у системі інсерційного моделювання
The paper relates to practical aspects of insertion modeling. Insertion modeling system is an environment for the development of insertion machines, used to represent insertion models of distributed systems. The architecture of insertion machines and insertion modeling system IMS is presented. Insertion machine for constraint programming is specified as an example, and as a starting point of ‘verifiable programming’ project
Програмування в обмеженнях у системі інсерційного моделювання
The paper relates to practical aspects of insertion modeling. Insertion modeling system is an environment for the development of insertion machines, used to represent insertion models of distributed systems. The architecture of insertion machines and insertion modeling system IMS is presented. Insertion machine for constraint programming is specified as an example, and as a starting point of ‘verifiable programming’ project
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Analysis of a class of distributed queues with application
Recently we have developed a class of media access control algorithms for different types of Local Area Networks. A common feature of these LAN algorithms is that they represent various strategies by which the processors in the LAN can simulate the availability of a centralized packet transport facility, but whose service incorporates a particular type of change over time known as 'moving sever' overhead. First we describe the operation of moving server systems in general, for both First-Come - First-Served and Head-of-the-Line orders of service, together with an approach for their delay analysis in which we transform the moving server queueing system into a conventional queueing system having proportional waiting times. Then we describe how the various LAN algorithms may be obtained from the ideal moving server system, and how a significant component of their performance characteristics is determined by the performance characteristics of that ideal system. Finally, we evaluate the compatibility of such LAN algorithms with separable queueing network models of distributed systems by computing the interdeparture time distribution for M/M/1 in the presence of moving server overhead. Although it is not exponential, except in the limits of low server utilization or low overhead, the interdeparture time distribution is a weighted sum of exponential terms with a coefficient of variation not much smaller than unity. Thus, we conjecture that a service centre with moving server overhead could be used to represent one of these LAN algorithms in a product form queueing network model of a distributed system without introducing significant approximation errors
Simultaneous State and Parameter Estimation of Distributed-Parameter Physical Systems based on Sliced Gaussian Mixture Filter
This paper presents a method for the simultaneous state and parameter estimation of finite-dimensional models of distributed systems monitored by a sensor network. In the first step, the distributed system is spatially and temporally decomposed leading to a linear finite-dimensional model in state space form. The main challenge is that the simultaneous state and parameter estimation of such systems leads to a high-dimensional nonlinear problem. Thanks to the linear substructure contained in the resulting finite-dimensional model, the development of an overall more efficient estimation process is possible. Therefore, in the second step, we propose the application of a novel density representation - sliced Gaussian mixture density - in order to decompose the estimation problem into a (conditionally) linear and a nonlinear problem. The systematic approximation procedure minimizing a certain distance measure allows the derivation of (close to) optimal and deterministic results. The proposed estimation process provides novel prospects in sensor network applications. The performance is demonstrated by means of simulation results
Deterministic blind radio networks
Ad-hoc radio networks and multiple access channels are classical and well-studied models of distributed systems, with a large body of literature on deterministic algorithms for fundamental communications primitives such as broadcasting and wake-up. However, almost all of these algorithms assume knowledge of the number of participating nodes and the range of possible IDs, and often make the further assumption that the latter is linear in the former. These are very strong assumptions for models which were designed to capture networks of weak devices organized in an ad-hoc manner. It was believed that without this knowledge, deterministic algorithms must necessarily be much less efficient.
In this paper we address this fundamental question and show that this is not the case. We present deterministic algorithms for blind networks (in which nodes know only their own IDs), which match or nearly match the running times of the fastest algorithms which assume network knowledge (and even surpass the previous fastest algorithms which assume parameter knowledge but not small labels)
Partial evaluation in insertion modeling system
The paper relates to practical aspects of insertion modeling. Insertion modeling system is an environment for development of insertion machines, used to represent insertion models of distributed systems. The notions of insertion modeling are stated. The main features of partial evaluation are described in the paper. The concep-tion of partial evaluation in insertion modeling is presented
Learning Broadcast Protocols
The problem of learning a computational model from examples has been
receiving growing attention. For the particularly challenging problem of
learning models of distributed systems, existing results are restricted to
models with a fixed number of interacting processes. In this work we look for
the first time (to the best of our knowledge) at the problem of learning a
distributed system with an arbitrary number of processes, assuming only that
there exists a cutoff, i.e., a number of processes that is sufficient to
produce all observable behaviors. Specifically, we consider fine broadcast
protocols, these are broadcast protocols (BPs) with a finite cutoff and no
hidden states. We provide a learning algorithm that can infer a correct BP from
a sample that is consistent with a fine BP, and a minimal equivalent BP if the
sample is sufficiently complete. On the negative side we show that (a)
characteristic sets of exponential size are unavoidable, (b) the consistency
problem for fine BPs is NP hard, and (c) that fine BPs are not polynomially
predictable.Comment: 13 pages, 7 figures, 3 input files of plot
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