Low-time complexity budget–deadline constrained workflow scheduling on heterogeneous resources

2016 ◽  
Vol 55 ◽  
pp. 29-40 ◽  
Author(s):  
Hamid Arabnejad ◽  
Jorge G. Barbosa ◽  
Radu Prodan
2022 ◽  
Vol 12 (1) ◽  
pp. 0-0

Fog computing and Edge computing are few of the latest technologies which are offered as solution to challenges faced in Cloud Computing. Instead of offloading of all the tasks to centralized cloud servers, some of the tasks can be scheduled at intermediate Fog servers or Edge devices. Though this solves most of the problems faced in cloud but also encounter other traditional problems due to resource-related constraints like load balancing, scheduling, etc. In order to address task scheduling and load balancing in Cloud-fog-edge collaboration among servers, we have proposed an improved version of min-min algorithm for workflow scheduling which considers cost, makespan, energy and load balancing in heterogeneous environment. This algorithm is implemented and tested in different offloading scenarios- Cloud only, Fog only, Cloud-fog and Cloud-Fog-Edge collaboration. This approach performed better and the result gives minimum makespan, less energy consumption along with load balancing and marginally less cost when compared to min-min and ELBMM algorithms


Author(s):  
Suresha .M ◽  
. Sandeep

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.


Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.


2009 ◽  
Vol 31 (2) ◽  
pp. 282-290 ◽  
Author(s):  
Ying-Chun YUAN ◽  
Xiao-Ping LI ◽  
Qian WANG ◽  
Yi ZHANG

2011 ◽  
Vol 30 (12) ◽  
pp. 3184-3186
Author(s):  
Ming-quan WANG ◽  
Jiong YU ◽  
Yuan TIAN ◽  
Yun HAN

Sign in / Sign up

Export Citation Format

Share Document