Consistent Hashing and Real-Time Task Scheduling in Fog Computing

2022 ◽  
pp. 245-261
Author(s):  
Geetha J. J. ◽  
Jaya Lakshmi D. S. ◽  
Keerthana Ningaraju L. N.

Distributed caching is one such system used by dynamic high-traffic websites to process the incoming user requests to perform the required tasks in an efficient way. Distributed caching is currently employing hashing algorithm in order to serve its purpose. A significant drawback of hashing in this circumstance is the addition of new servers that would result in a change in the previous hashing method (rehashing), hence, goes into a rigmarole. Thus, we need an effective algorithm to address the problem. This technique has served as a solution for distributed and rehashing problems. Most of upcoming internet of things will have to be latency aware and will not afford the data transmission and computation time in the cloud servers. The real-time processing in proximal distance device would be much needed. Hence, the authors aim to employ a real-time task scheduling algorithm. Computations referring to the user requests that are to be handled by the servers can be efficiently handled by consistent hashing algorithms.

Author(s):  
Myungryun Yoo ◽  
Takanori Yokoyama

Purpose of the study:The real-time task scheduling on multiprocessor system is known as an NP-hard problem. This paper proposes a new real-time task scheduling algorithmwhich considers the communication time between processors and the execution order between tasks. Methodology:Genetic Algorithm (GA)with Adaptive Weight Approach (AWA) is used in our approach. Main Findings:Our approach has two objectives. The first objective is to minimize the total amount of deadline-miss. And the second objective is to minimize the total number of processors used. Applications of this study:For two objectives,the range of each objective is readjusted through Adaptive Weight Approach (AWA) and more useful result is obtained. Novelty/Originality of this study:This study never been done before.This study also wasprovided current information about scheduling algorithm and heuristics algorithm.


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


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