SYNCHRONIZING MECHANISM IN DISTRIBUTED INFORMATION PROCESSING SYSTEMS

2021 ◽  
pp. 44-48
Author(s):  
С.А. Багирова ◽  
А.А. Алиев
Keyword(s):  
Information Processing ◽  
Distributed Systems ◽  
Distributed System ◽  
Distributed Information ◽  
Process Synchronization

В работе описывается модель распределенной системы. На базе этой модели анализируется одна из задач, в основе, которой лежит проблема синхронизации процессов, а именно, задача обеспечения сериализуемости параллельных транзакций в распределенных системах. Приводится пример обеспечения сериализуемости распределенного плана. The paper describes a model of a distributed system. On the basis of this model, one of the problems is analyzed, which is based on the problem of process synchronization, namely, the problem of ensuring serializability of parallel transactions in distributed systems. An example of ensuring the serializability of a distributed plan is given.

NVESTIGATION OF THE EFFICIENCY OF DISTRIBUTED INFORMATION SYSTEMS BASED ON THE PROCESSING OF LARGE AMOUNTS OF DATA

2019 ◽  
Author(s):  
Mykhajlo Klymash ◽  
Olena Hordiichuk — Bublivska ◽  
Ihor Tchaikovskyi ◽  
Oksana Urikova
Keyword(s):  
Distributed Systems ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Data Decomposition ◽  
Distributed Information ◽  
Software Model ◽  
Computing Performance ◽  
Mapreduce Model ◽  
Singular Data

In this article investigated the features of processing large arrays of information for distributed systems. A method of singular data decomposition is used to reduce the amount of data processed, eliminating redundancy. Dependencies of com­putational efficiency on distributed systems were obtained using the MPI messa­ging protocol and MapReduce node interaction software model. Were analyzed the effici­ency of the application of each technology for the processing of different sizes of data: Non — distributed systems are inefficient for large volumes of information due to low computing performance. It is proposed to use distributed systems that use the method of singular data decomposition, which will reduce the amount of information processed. The study of systems using the MPI protocol and MapReduce model obtained the dependence of the duration calculations time on the number of processes, which testify to the expediency of using distributed computing when processing large data sets. It is also found that distributed systems using MapReduce model work much more efficiently than MPI, especially with large amounts of data. MPI makes it possible to perform calculations more efficiently for small amounts of information. When increased the data sets, advisable to use the Map Reduce model.

XERIS/APEX

2021 ◽  
Vol 40 (2) ◽  
pp. 65-69
Author(s):  
Richard Wai
Keyword(s):  
Distributed Systems ◽  
Real Time ◽  
Distributed System ◽  
Dynamic Scaling ◽  
Distributed Application ◽  
Heavy Weight ◽  
System Models ◽  
In The Wild ◽  
On Line ◽  
Language Technologies

Modern day cloud native applications have become broadly representative of distributed systems in the wild. However, unlike traditional distributed system models with conceptually static designs, cloud-native systems emphasize dynamic scaling and on-line iteration (CI/CD). Cloud-native systems tend to be architected around a networked collection of distinct programs ("microservices") that can be added, removed, and updated in real-time. Typically, distinct containerized programs constitute individual microservices that then communicate among the larger distributed application through heavy-weight protocols. Common communication stacks exchange JSON or XML objects over HTTP, via TCP/TLS, and incur significant overhead, particularly when using small size message sizes. Additionally, interpreted/JIT/VM-based languages such as Javascript (NodeJS/Deno), Java, and Python are dominant in modern microservice programs. These language technologies, along with the high-overhead messaging, can impose superlinear cost increases (hardware demands) on scale-out, particularly towards hyperscale and/or with latency-sensitive workloads.

APPLICABILITY OF THE TRANSPORT PROBLEM ON THE TIME CRITERION WITH ATOMIC REQUIREMENTS FOR OPTIMIZING THE CONTROL OF COMPUTED RESOURCES IN HETEROGENEOUS DISTRIBUTED INFORMATION PROCESSING SYSTEM

2021 ◽  
pp. 8-14
Author(s):  
Г.А. Онтужева
Keyword(s):  
Information Processing ◽  
Processing System ◽  
Time Algorithm ◽  
Transport Problem ◽  
Distributed Information ◽  
Information Processing System ◽  
Time Criterion

В статье рассматривается возможность применения методов решения транспортной задачи к задаче распределения вычислительных ресурсов в гетерогенных распределенных системах обработки информации. Приведено сравнение эффективности алгоритмов с ранее разработанным алгоритмом наименьшего времени для атомарных заявок. The paper examines the applicability of methods for solving the transport problem to the problem of distribution of computing resources in heterogeneous distributed information processing systems. A comparison of the efficiency of the algorithms with the previously developed least time algorithm for atomic claims is given.

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