Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

Cloud computing plays a significant role in Information Technology(IT)industry to deliver scalable resources as a service.One of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task scheduling.The main advantage of this scheduling is to max-imize the performance and minimize the time loss.Various researchers examined numerous scheduling methods to achieve Quality of Service(QoS)and to reduce execution time.However,it had disadvantages in terms of low throughput and high response time.Hence,this study aimed to schedule the task efficiently and to eliminate the faults in scheduling the tasks to the Virtual Machines(VMs).For this purpose,the research proposed novel Particle Swarm Optimization-Bandwidth Aware divisible Task(PSO-BATS)scheduling with Multi-Layered Regression Host Employment(MLRHE)to sort out the issues of task scheduling and ease the scheduling operation by load balancing.The proposed efficient sche-duling provides benefits to both cloud users and servers.The performance evalua-tion is undertaken with respect to cost,Performance Improvement Rate(PIR)and makespan which revealed the efficiency of the proposed method.Additionally,comparative analysis is undertaken which confirmed the performance of the intro-duced system than conventional system for scheduling tasks with highflexibility.

Task Space Division and Trajectory Planning for a Flexible Macro-Micro Manipulator System

This paper deals with a flexible macro-micro manipulator system, which includes a long flexible manipulator and a relatively short rigid manipulator attached to the tip of the macro manipulator. A flexible macro manipulator possesses the advantages of wide operating range, high speed, and low energy consumption, but the disadvantage of a low tracking precision. The macro-micro manipulator system improves tracking performance by compensating for the endpoint tracking error while maintaining the advantages of the flexible macro manipulator. A trajectory planning scheme was built utilizing the task space division method. The division point is chosen to optimize the error compensation and energy consumption for the whole system. Then movements of the macro-micro manipulator can be determined using separate inverse kinematic models. Simulation results for a planar 4-DOF macro-micro manipulator system are presented to show the effectiveness of the control system.

Analysing spatial data performance in inter-organisational processes

The use of spatial data has become a key factor in numerous public sector processes.However,recent evidence suggests that the seemingly obvious benefits of spatial data use and sharing often stay beyond reach.This paper examines whether the performance of spatial data in inter-organisational processes depends on the structural characteristics of the process involved.Process structure here refers to the way in which tasks are divided and coordinated between the organisations in a process chain,and to the allocation of the spatial data handling tasks in that process.Spatial data performance describes the level of access,use and sharing of spatial data in the process.The paper presents the results of a comparative case study of interorganisational public sector processes in the fields of urban planning,flood management,population registration,environmental permit delivery and road safety monitoring.The findings suggest that spatial data performance in inter-organisational processes depends on the interplay between the structural characteristics of the process.Unfragmented processes with embedded activities that are related to spatial data are apparently linked to a high level of spatial data performance,while fragmented processes without centralised coordination,or processes in which the spatial datarelated activities are separated from the actual process,seem to relate to lower levels of spatial data performance.