A Survey of Tasks Scheduling Algorithms in Distributed Computing Systems

2021 ◽  
pp. 233-244
Author(s):  
Nutan Kumari Chauhan ◽  
Harendra Kumar
Keyword(s):  
Distributed Computing ◽  
Scheduling Algorithms ◽  
Computing System ◽  
Communication Link ◽  
Scheduling Problems ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Tasks Scheduling ◽  
Scheduling Strategies ◽  
User Tasks

Distributed computing system (DCS) is a very popular field of computer science. DCS consists of various computers (processors) located at possibly different sites and connected by a communication link in such a manner that it appears as one system to the user. Tasks scheduling is a very interesting field of research in DCS. The main objectives of tasks scheduling problems are load balancing of processors, maximization of system reliability, minimizing the system cost, and minimizing the response time. Obviously, it is very complicated to satisfy all of the above objectives simultaneously. So, most of the researchers have solved the tasks scheduling problem with one or more objectives. The purpose of this chapter is to produce an overview of much (certainly not all) of tasks scheduling algorithms. The chapter is covering the little much valuable survey, tasks scheduling strategies, and different approaches used for tasks scheduling with one or more objectives.

A Survey of Tasks Scheduling Algorithms in Distributed Computing Systems

2021 ◽  
pp. 1269-1281
Author(s):  
Nutan Kumari Chauhan ◽  
Harendra Kumar
Keyword(s):  
Distributed Computing ◽  
Scheduling Algorithms ◽  
Computing System ◽  
Communication Link ◽  
Scheduling Problems ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Tasks Scheduling ◽  
Scheduling Strategies ◽  
User Tasks

Distributed computing system (DCS) is a very popular field of computer science. DCS consists of various computers (processors) located at possibly different sites and connected by a communication link in such a manner that it appears as one system to the user. Tasks scheduling is a very interesting field of research in DCS. The main objectives of tasks scheduling problems are load balancing of processors, maximization of system reliability, minimizing the system cost, and minimizing the response time. Obviously, it is very complicated to satisfy all of the above objectives simultaneously. So, most of the researchers have solved the tasks scheduling problem with one or more objectives. The purpose of this chapter is to produce an overview of much (certainly not all) of tasks scheduling algorithms. The chapter is covering the little much valuable survey, tasks scheduling strategies, and different approaches used for tasks scheduling with one or more objectives.

Security Issues in Distributed Computing System Models

2017 ◽  
pp. 211-259 ◽  
Author(s):  
Ghada Farouk Elkabbany ◽  
Mohamed Rasslan
Keyword(s):  
Distributed Systems ◽  
Distributed Computing ◽  
Computing System ◽  
Computing Environment ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Research Directions ◽  
System Models ◽  
Security Issues ◽  
Systems Security

Distributed computing systems allow homogenous/heterogeneous computers and workstations to act as a computing environment. In this environment, users can uniformly access local and remote resources in order to run processes. Users are not aware of which computers their processes are running on. This might pose some complicated security problems. This chapter provides a security review of distributed systems. It begins with a survey about different and diverse definitions of distributed computing systems in the literature. Different systems are discussed with emphasize on the most recent. Finally, different aspects of distributed systems security and prominent research directions are explored.

Dynamic Tasks Scheduling Algorithm for Distributed Computing Systems under Fuzzy Environment

2016 ◽  
Vol 5 (4) ◽  
pp. 77-95 ◽  
Author(s):  
Harendra Kumar ◽  
Nutan Kumari Chauhan ◽  
Pradeep Kumar Yadav
Keyword(s):  
Distributed Computing ◽  
Present Model ◽  
Scheduling Algorithm ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Fuzzy Environment ◽  
Multiple Processors ◽  
Tasks Scheduling ◽  
Present Algorithm ◽  
System Phase

Distributed computing systems [DCS] offer the potential for allocating a number of tasks to different processors for execution. It is desired to assign the tasks dynamically to that processor whose characteristics are most appropriate for the execution in order to make the best use of the computational power available. This paper proposes a new mathematical model for allocating the tasks of distributed program to multiple processors in order to achieve optimal cost and optimal reliability of the system. Phase-wise execution cost, residence cost of each task on different processors, inter task communication cost and relocation cost for each task have been considered as a fuzzy number which is more realistic and general in nature. The fuzzy problem has been transformed into crisp one by using the defuzzification method. The present algorithm is formulated and applied to numerical examples to demonstrate its effectiveness. The present model is suitable for arbitrary number of phases and processors with random program structure.

scholarly journals Particle Swarm Optimization for Load Balancing in Distributed Computing Systems – A Survey

2021 ◽  
Vol 12 (1S) ◽  
pp. 257-265
Author(s):  
Vidya S. Handur, Et. al.
Keyword(s):  
Particle Swarm Optimization ◽  
Distributed Computing ◽  
Load Balancing ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Computing System ◽  
Optimization Approach ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Swarm Optimization

Development of technology like Cloud Computing and its widespread usage has given rise to exponential increase in the volume of traffic. With this increase in huge traffic the resources in the network would either be insufficient to handle the traffic or the situation may cause some of the resources to be over utilized or underutilized. This condition leads to reduced performance of the system. To improve the performance of the system the traffic requires to be regulated such that all the resources are utilized conferring to their capacity which is known as load balancing. Load balancing has been one of the concerns in the distributed computing systems where the computing nodes do not have a global view of the network. There have been constant efforts to provide an efficient solution for load balancing through the approaches like game theory, fuzzy logic, heuristics and metaheuristics. Even though various solutions exist for balancing the load, the issue is challenging as there does not exist one best fit solution. The paper aims at the study of how Particle Swarm Optimization approach is used to achieve an optimal solution for load balancing in distributed computing system.

scholarly journals Research and Organization of Priority Modes in a Network Distributed Computing System with Cloud Service Architecture

2019 ◽  
Vol 23 (2) ◽  
pp. 153-173
Author(s):  
M. Sadeq Jaafar
Keyword(s):  
Distributed Computing ◽  
Petri Nets ◽  
Storage System ◽  
Cloud Service ◽  
Computing System ◽  
Cloud Services ◽  
Service Architecture ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Replicated Databases

Purpose of research. The object of the study is a network cloud service built on the basis of a replicated database. Data in distributed computing systems are replicated in order to ensure the reliability of their storage, facilitate access to data as well as to improve the storage system performance. In this regard, the problem of analyzing the effectiveness of processing the queries to replicated databases in a network-based cloud environment, and, in particular, the problem of organizing priority query queues for updating databae copies (update requests) and for searching and reading information in databases (query-requests). The purpose of this work is to study and organize priority modes in a network distributed computing system with cloud service architecture.Methods. The study was conducted on the basis of two types of behavioural patterns: models based on Petri nets to describe and verify the functioning of a distributed computing system with replicated databases represented as a pool of resource units with several units, and models based on the GPSS simulation language for possible evaluation of passage of query time of each type in queues depending on the priority of queries.Results. Based on two simulation methods, the operation of a cloud system with database replicas was analyzed. In this system two distributed cloud computing systems interact: MANET Cloud based on a wireless network and Internet Cloud based on the Internet. These databases together are the basis of the DBaaSoD (Data Bases as a Service on Demand) cloud service (databases as a service organized at user’s query). To study this system the models of two classes were developed. The model based on Petri nets is designed to test the simulated distributed application for proper functioning. The decisions on the mapping of Petri nets on the architecture of computer networks are discussed. The simulation statistical model is used to compare the priority and non-priority maintenance modes of query- and update-requests by the criterion of average passage of time of queries in queues.Conclusion. System models based on Petri nets were tested, which showed their liveness and security, which makes it possible to move from models to building formalized specifications for network applications for network cloud services in distributed computing systems with replicated databases. The study of GPSS-model showed that in the case of priority service of update-requests, the time of passage for them is reduced by about 2 to 4 times compared with query-requests, depending on the intensity of the query-requests. In the non-priority mode, the serving conditions for update-queries deteriorate and the time of passage in the queue for them increases by about 2 to 6 times as compared with query-requests depending on the intensity of the query-requests.

Security Issues in Distributed Computing System Models

2018 ◽  
pp. 381-418
Author(s):  
Ghada Farouk Elkabbany ◽  
Mohamed Rasslan
Keyword(s):  
Distributed Systems ◽  
Distributed Computing ◽  
Computing System ◽  
Computing Environment ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Research Directions ◽  
System Models ◽  
Security Issues ◽  
Systems Security

Distributed computing systems allow homogenous/heterogeneous computers and workstations to act as a computing environment. In this environment, users can uniformly access local and remote resources in order to run processes. Users are not aware of which computers their processes are running on. This might pose some complicated security problems. This chapter provides a security review of distributed systems. It begins with a survey about different and diverse definitions of distributed computing systems in the literature. Different systems are discussed with emphasize on the most recent. Finally, different aspects of distributed systems security and prominent research directions are explored.

scholarly journals A Survey on ANN Based Task Scheduling Strategies in Heterogeneous Distributed Computing Systems

2016 ◽  
Vol 16 (1) ◽  
pp. 69-78
Author(s):  
Altaf Hussain ◽  
Faisal Azam ◽  
Muhammad Sharif ◽  
Mussarat Yasmin ◽  
Sajjad Mohsin
Keyword(s):  
Distributed Computing ◽  
Task Scheduling ◽  
High Speed ◽  
Directed Acyclic Graphs ◽  
Parallel Applications ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Heterogeneous Distributed Computing ◽  
Scheduling Strategies ◽  
Heterogeneous Distributed Computing Systems

Heterogeneous Distributed Computing Systems (HeDCS) efficiently utilize the heterogeneity of diverse computational resources which are interlinked through high speed networks for executing a group of computing intensive applications. Directed acyclic graphs (DAGs) are usually used to represent these parallel applications with varied computational requirements and constraints. The optimal scheduling of the given set of precedence constrained tasks to available resources is a core concern in HeDCS and is known to be NP Complete problem. Non deterministic nature of application programs and heterogeneous environment are the main challenges in designing, implementing and analyzing phases of task scheduling techniques. A myriad of heuristic and meta-heuristic approaches have been proposed in the literature to solve this complex problem. The basic purpose of this study is to cover ANN based task scheduling strategies in the distributed computing environment perspective. Further existing scheduling heuristics could be classified in a new state of art classification including the description of frequently used parameters in the mentioned scheduling strategies. The flexible and powerful nature of ANN for identifying the data patterns, underlying time and other constraints and learning capabilities have shown to be a promising candidate among other heuristics.Nepal Journal of Science and Technology Vol. 16, No.1 (2015) pp. 69-78

APPLICATION OF DISTRIBUTED COMPUTING SYSTEMS FOR IMAGE PROCESSING IN ORDER TO SEARCH FOR UNMANNED AERIAL VEHICLES

2021 ◽  
pp. 46-53
Author(s):  
A. I. Kalyaev
Keyword(s):  
Image Processing ◽  
Distributed Computing ◽  
Unmanned Aerial Vehicles ◽  
Video Processing ◽  
Computing System ◽  
Frame Rate ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Aerial Vehicles ◽  
Low Efficiency

This article describes an approach to solving the problem of searching, identifying and tracking UAVs (Unmanned Aerial Vehicles) using a distributed computing system for processing images from multiple surveillance cameras. Today, the problem of finding UAVs is becoming especially relevant due to their widespread distribution and low cost, which gives a wide scope for illegal use: the implementation of terrorist attacks in crowded places and critical infrastructure, as well as unauthorized tracking of specially protected areas. At the same time, modern radars have low efficiency for searching for UAVs, so today visual detection tools are used, for which effective work requires complex calculations. In this article, it is proposed to use distributed computing systems to solve these complex problems of processing a video stream for the purpose of searching, identifying and tracking objects (UAVs). For this, the author of the article, proceeding from the potential areas of application of such systems, decided to apply a multiagent approach, which makes it possible to create fault-tolerant and scalable systems. In the course of work on the article, softwarefor a distributed computing system for image processing in order to search for unmanned aerial vehicleswas created, a hardware stand was assembled to test it. While performing tests, it was concluded that the proposed method can be applied to implement high-resolution video processing and frame rate in a distributed computing system.

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