Data Specific Ranking in Cloud

2014 ◽  
Vol 4 (4) ◽  
pp. 32-41 ◽  
Author(s):  
Anirban Kundu ◽  
Guanxiong Xu ◽  
Chunlin Ji
Keyword(s):  
Dynamic Scheduling ◽  
System Structure ◽  
Distributed Network ◽  
Major Goal ◽  
Data Redundancy ◽  
Time Dynamic ◽  
Run Time

In this paper, the major goal is to achieve searching in distributed network with proper ranking. Heterogeneous framework is going to be utilized using existing machines and high-end workstations. Data redundancy is responsible for enhancing dynamic scheduling in run-time. Dynamic scheduling is going to be exploited determining possible sub-network and related servers for specific user targeted tasks using active and busy ranking status of servers. Minimization of time and maximization of speed are objectives of proposed system structure.

Software-as-a-Service using Heterogeneous Distributed System for User Specific Applications

2014 ◽  
Vol 4 (1) ◽  
pp. 15-32 ◽  
Author(s):  
Anirban Kundu ◽  
Chunlin Ji ◽  
Ruopeng Liu
Keyword(s):  
Dynamic Scheduling ◽  
Cost Minimization ◽  
System Structure ◽  
Main Concern ◽  
Distributed Environment ◽  
Time Dynamic ◽  
Server Side ◽  
Dedicated Servers ◽  
Background Mode ◽  
Cost Feasibility

In this paper, major goal is to achieve distributed environment configuring heterogeneous system framework using existing machines and high-end workstations as servers without involving extra cost. Feasibility of proposed system network is main concern in this paper having cost minimization. Data replication is responsible for enhancing dynamic scheduling in run-time. Dynamic scheduling is going to be exploited determining possible sub-network and related servers for specific user targeted tasks using active status and busy status of servers. Server-side background mode of operation is to be conducted for accessing dedicated or non-dedicated servers. Minimization of time and maximization of speed are objectives of proposed system structure.

Dynamic Scheduling Model of Rail-Guided Vehicle (RGV) Based on Genetic Algorithms in the Context of Mobile Computing

2021 ◽  
Vol 12 (1) ◽  
pp. 43-62
Author(s):  
Chen Xu ◽  
Xueyan Xiong ◽  
Qianyi Du ◽  
Shudong Liu ◽  
Yipeng Li ◽  
...  
Keyword(s):  
Information System ◽  
Mobile Computing ◽  
Dynamic Scheduling ◽  
Distributed Processing ◽  
Processing System ◽  
Time Dynamic ◽  
Scheduling Model ◽  
Practical Operation ◽  
Optimization Efficiency ◽  
Production And Operation

Track guidance vehicle (RGV) is widely used in logistics warehousing and intelligent workshop, and its scheduling effectiveness will directly affect the production and operation efficiency of enterprises. In practical operation, central information system often lacks flexibility and timeliness. By contrast, mobile computing can balance the central information system and the distributed processing system, so that useful, accurate, and timely information can be provided to RGV. In order to optimize the RGV scheduling problem in uncertain environment, a genetic algorithm scheduling rule (GAM) using greedy algorithm as the genetic screening criterion is proposed in this paper. In the experiment, RGV scheduling of two-step processing in an intelligent workshop is selected as the research object. The experimental results show that the GAM model can carry out real-time dynamic programming, and the optimization efficiency is remarkable before a certain threshold.

APPLICATION OF A REAL-TIME CONTROL STRATEGY FOR BAYESIAN BELIEF NETWORKS TO SHIP CLASSIFICATION PROBLEM SOLVING

1993 ◽  
Vol 07 (03) ◽  
pp. 513-526 ◽  
Author(s):  
S.A. MUSMAN ◽  
L.W. CHANG ◽  
L.B. BOOKER
Keyword(s):  
Real Time ◽  
Control Strategy ◽  
Bayesian Belief Networks ◽  
System Structure ◽  
Belief Networks ◽  
Classification Problems ◽  
Real Time Control ◽  
Time Control ◽  
Run Time ◽  
Ship Classification

Many classification problems must be performed in a timely or time constrained manner. For this reason, the generation of control schemes which are capable of responding in real-time are fundamental to many applications. For our problem, that of ship classification, tactical scenarios often dictate the response time required from a system. In this paper, we discuss efficient ways to prioritize and gather evidence within belief networks. We also suggest ways in which we can structure our large problem into a series of small ones. This both pre-defines much of our control strategy into the system structure and also localizes our run-time control issues into much smaller networks. The overall control strategy thus includes the combination of both of these methods. By combining them correctly we can reduce the amount of dynamic computation required during run-time and thus improve the responsiveness of the system.

scholarly journals Run-Time Dynamic Resource Adjustment for Mitigating Skew in MapReduce

2021 ◽  
Vol 126 (2) ◽  
pp. 771-790
Author(s):  
Zhihong Liu ◽  
Shuo Zhang ◽  
Yaping Liu ◽  
Xiangke Wang ◽  
Dong Yin
Keyword(s):  
Time Dynamic ◽  
Resource Adjustment ◽  
Dynamic Resource ◽  
Run Time
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