610,157 research outputs found
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Distributed System Development At Toko Emas Makmur Based On Desktop and Web Applications is an application used to allow users to store to report all transactions and data items. This application uses three (3) platforms, the Desktop and Web applications are distributed using the Web Service. This application was built using Visual Studio 2015 software on desktop and web applications, as well as SQL Server 2015 as the database of the program. This application involves three (3) the results of which will be a report that sales transactions, purchase transactions, and Data Products. This application uses the UAT (User Aceptence Test), and Blackbox testing in the testing process. From the testing that has been done shows that desktop applications can be connected or properly distributed to the web through the Web Service
Diffusion Adaptation Strategies for Distributed Estimation over Gaussian Markov Random Fields
The aim of this paper is to propose diffusion strategies for distributed
estimation over adaptive networks, assuming the presence of spatially
correlated measurements distributed according to a Gaussian Markov random field
(GMRF) model. The proposed methods incorporate prior information about the
statistical dependency among observations, while at the same time processing
data in real-time and in a fully decentralized manner. A detailed mean-square
analysis is carried out in order to prove stability and evaluate the
steady-state performance of the proposed strategies. Finally, we also
illustrate how the proposed techniques can be easily extended in order to
incorporate thresholding operators for sparsity recovery applications.
Numerical results show the potential advantages of using such techniques for
distributed learning in adaptive networks deployed over GMRF.Comment: Submitted to IEEE Transactions on Signal Processing. arXiv admin
note: text overlap with arXiv:1206.309
Atomic Appends: Selling Cars and Coordinating Armies with Multiple Distributed Ledgers
The various applications using Distributed Ledger Technologies (DLT) or blockchains, have led to the introduction of a new "marketplace" where multiple types of digital assets may be exchanged. As each blockchain is designed to support specific types of assets and transactions, and no blockchain will prevail, the need to perform interblockchain transactions is already pressing.
In this work we examine the fundamental problem of interoperable and interconnected blockchains. In particular, we begin by introducing the Multi-Distributed Ledger Objects (MDLO), which is the result of aggregating multiple Distributed Ledger Objects - DLO (a DLO is a formalization of the blockchain) and that supports append and get operations of records (e.g., transactions) in them from multiple clients concurrently. Next we define the AtomicAppends problem, which emerges when the exchange of digital assets between multiple clients may involve appending records in more than one DLO. Specifically, AtomicAppend requires that either all records will be appended on the involved DLOs or none. We examine the solvability of this problem assuming rational and risk-averse clients that may fail by crashing, and under different client utility and append models, timing models, and client failure scenarios. We show that for some cases the existence of an intermediary is necessary for the problem solution. We propose the implementation of such intermediary over a specialized blockchain, we term Smart DLO (SDLO), and we show how this can be used to solve the AtomicAppends problem even in an asynchronous, client competitive environment, where all the clients may crash
Maintaining consistency in distributed systems
In systems designed as assemblies of independently developed components, concurrent access to data or data structures normally arises within individual programs, and is controlled using mutual exclusion constructs, such as semaphores and monitors. Where data is persistent and/or sets of operation are related to one another, transactions or linearizability may be more appropriate. Systems that incorporate cooperative styles of distributed execution often replicate or distribute data within groups of components. In these cases, group oriented consistency properties must be maintained, and tools based on the virtual synchrony execution model greatly simplify the task confronting an application developer. All three styles of distributed computing are likely to be seen in future systems - often, within the same application. This leads us to propose an integrated approach that permits applications that use virtual synchrony with concurrent objects that respect a linearizability constraint, and vice versa. Transactional subsystems are treated as a special case of linearizability
Probabilistic and Distributed Control of a Large-Scale Swarm of Autonomous Agents
We present a novel method for guiding a large-scale swarm of autonomous
agents into a desired formation shape in a distributed and scalable manner. Our
Probabilistic Swarm Guidance using Inhomogeneous Markov Chains (PSG-IMC)
algorithm adopts an Eulerian framework, where the physical space is partitioned
into bins and the swarm's density distribution over each bin is controlled.
Each agent determines its bin transition probabilities using a
time-inhomogeneous Markov chain. These time-varying Markov matrices are
constructed by each agent in real-time using the feedback from the current
swarm distribution, which is estimated in a distributed manner. The PSG-IMC
algorithm minimizes the expected cost of the transitions per time instant,
required to achieve and maintain the desired formation shape, even when agents
are added to or removed from the swarm. The algorithm scales well with a large
number of agents and complex formation shapes, and can also be adapted for area
exploration applications. We demonstrate the effectiveness of this proposed
swarm guidance algorithm by using results of numerical simulations and hardware
experiments with multiple quadrotors.Comment: Submitted to IEEE Transactions on Robotic
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