Enhancing the Job Scheduling Procedure to Develop an Efficient Cloud Environment using Near Optimal Clustering Algorithm

The evolution of IT led Cloud computing technology emerge as a new prototype in providing the services to its users on rented basis at any time or place. Considering the flexibility of cloud services, innumerable organizations switched their businesses to the cloud technology by setting up more data centers. Nevertheless, it has become mandatory to provide profitable execution of tasks and appropriate resource utilization. A few approaches were outlined in literature to enhance performance, job scheduling, storage resources, QoS and load distribution. Load balancing concept permits data centers to avert over-loading or under-loading in virtual machines that as such is an issue in cloud computing domain. Consequently, it necessitate the researchers to layout and apply a proper load balancer for cloud environment. The respective study represents a view of problems and threats faced by the current load balancing techniques and make the researchers find more efficient algorithms.

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Load balancing in Cloud Computing: Issues and Challenges

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i2.2350 ◽

2021 ◽

Vol 12 (2) ◽

pp. 3077-3084

Author(s):

K. Balaji , Et. al.

Keyword(s):

Cloud Computing ◽

Load Balancing ◽

Load Distribution ◽

Data Centers ◽

Job Scheduling ◽

Virtual Machines ◽

Cloud Services ◽

Cloud Environment ◽

Computing Technology ◽

Load Balancer

The evolution of IT led Cloud computing technology emerge as a new prototype in providing the services to its users on rented basis at any time or place. Considering the flexibility of cloud services, innumerable organizations switched their businesses to the cloud technology by setting up more data centers. Nevertheless, it has become mandatory to provide profitable execution of tasks and appropriate resource utilization. A few approaches were outlined in literature to enhance performance, job scheduling, storage resources, QoS and load distribution. Load balancing concept permits data centers to avert over-loading or under-loading in virtual machines that as such is an issue in cloud computing domain. Consequently, it necessitate the researchers to layout and apply a proper load balancer for cloud environment. The respective study represents a view of problems and threats faced by the current load balancing techniques and make the researchers find more efficient algorithms.

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A Cloud Intrusion Detection System Using Novel PRFCM Clustering and KNN Based Dempster-Shafer Rule

International Journal of Cloud Applications and Computing ◽

10.4018/ijcac.2016100102 ◽

2016 ◽

Vol 6 (4) ◽

pp. 18-35 ◽

Cited By ~ 4

Author(s):

Partha Ghosh ◽

Shivam Shakti ◽

Santanu Phadikar

Keyword(s):

Cloud Computing ◽

Intrusion Detection ◽

Intrusion Detection System ◽

Clustering Algorithm ◽

Detection System ◽

Cloud Environment ◽

Dempster Shafer Theory ◽

Computing Paradigm ◽

Rule Set ◽

Shafer Theory

Cloud computing has established a new horizon in the field of Information Technology. Due to the large number of users and extensive utilization, the Cloud computing paradigm attracts intruders who exploit its vulnerabilities. To secure the Cloud environment from such intruders an Intrusion Detection System (IDS) is required. In this paper the authors have proposed an anomaly based IDS which classifies an incoming connection by taking the deviation of it from the normal behaviors. The proposed method uses a novel Penalty Reward based Fuzzy C-Means (PRFCM) clustering algorithm to generate a rule set and the best rule set is extracted from it using a modified approach for KNN algorithm. This best rule set is used in evidential reasoning of Dempster Shafer Theory for classification. The IDS has been trained and tested with NSL-KDD dataset for performance evaluation. The results prove the proposed IDS to be highly efficient and reliable.

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