Refine your search
Collections
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Kanmani, P.
- Improving Data Access Performance in Cluster Based Ad-Hoc Networks
Abstract Views :159 |
PDF Views:3
Authors
Affiliations
1 Department of Computer Science and Engineering, K. S. Rangasamy College of Technology, Tamilnadu, IN
2 Department of Information Technology, K. S. Rangasamy College of Technology, Tamilnadu, IN
1 Department of Computer Science and Engineering, K. S. Rangasamy College of Technology, Tamilnadu, IN
2 Department of Information Technology, K. S. Rangasamy College of Technology, Tamilnadu, IN
Source
Wireless Communication, Vol 4, No 1 (2012), Pagination: 36-43Abstract
The objective of cooperative caching is to improve data availability, improve access efficiency and reduce query delay in mobile Ad-Hoc networks. Many types of cache replacement algorithms like LRU, LFU, LFRU, LRU-MIN and LFU-MIN are used to improve data accessibility and reduce query delay in cluster based cooperative caching in Mobile Ad-Hoc networks. But they have some limitations such as accessing remote information station via multi hop communication leads to longer query latency and causes high energy consumption, many clients frequently access the database server they cause a high load on the server and reduce the server response time .Multi hop communication causes the network capacity degrades when network partition occurs. The paper gives an overview of Cooperative Cache Management Techniques and caching policies and propose a new algorithm can be regarded as a LRFU-MIN (least recently frequently used information with minimal number of page replacements). It discover a data source which induces less communication cost of moving cache blocks into the most recently frequently used position and minimizes caching duplications between neighbor nodes. In this paper we utilize a cross-layer design approach to improve the performance of combined cooperative caching and prefetching schemes. The paper examines the performance using NS-2 simulation environments. The proposed LRFU-MIN enhances the performance of cross-layer cluster based cooperative caching in mobile Ad-Hoc networks when compared with LRU and LFU-MIN.Keywords
Adhoc Networks, Cooperative Caching, Clustering, Data Caching, Information Search.
- A Nonblocking Token Ring Based Checkpointing Algorithm for Distributed Mobile Computing Systems
Abstract Views :167 |
PDF Views:1
Authors
Affiliations
1 Deparment of Computer Science, Arignar Anna Government Arts College Attur, Salem Dt Tamil Nadu, IN
2 Department of MCA, K. S. Rangasamy College of Technology, Tiruchengode, Namakkal Dt, Tamil Nadu, IN
1 Deparment of Computer Science, Arignar Anna Government Arts College Attur, Salem Dt Tamil Nadu, IN
2 Department of MCA, K. S. Rangasamy College of Technology, Tiruchengode, Namakkal Dt, Tamil Nadu, IN
Source
Wireless Communication, Vol 1, No 2 (2009), Pagination: 116-120Abstract
Mobile computing introduces new flexibility such as continuous access to computing resources while the users travel.This facility raises new challenges such as fault tolerance in distributed mobile computing system. In this paper we present a non blocking token ring based checkpointing algorithm to tolerate the faults in the mobile computing environment. It is a single phase algorithm neither having the overhead of temporary checkpoints nor using dependency vector; and also it avoids the avalanche effect. Results shows that it outperforms two-phase algorithms.
Keywords
Checkpointing, Nonblocking, Token Ring.- A Nonblocking Token Ring Based Checkpointing Algorithm for Distributed Mobile Computing Systems
Abstract Views :187 |
PDF Views:4
Authors
Affiliations
1 Department of Computer Science, Arignar Anna Government Arts College, Attur, Salem Dt. Tamil Nadu, IN
2 Department of MCA, K. S. Rangasamy College of Technology, Tiruchengode, Namakkal Dt, Tamil Nadu, IN
3 Department of MCA, K. S. Rangasamy College of Technology, Tiruchengode, Namakkal Dt, Tamil Nadu, IN
1 Department of Computer Science, Arignar Anna Government Arts College, Attur, Salem Dt. Tamil Nadu, IN
2 Department of MCA, K. S. Rangasamy College of Technology, Tiruchengode, Namakkal Dt, Tamil Nadu, IN
3 Department of MCA, K. S. Rangasamy College of Technology, Tiruchengode, Namakkal Dt, Tamil Nadu, IN
Source
Networking and Communication Engineering, Vol 1, No 4 (2009), Pagination: 143-147Abstract
Mobile computing introduces new flexibility such as continuous access to computing resources while the users travel.This facility raises new challenges such as fault tolerance in distributed mobile computing system. In this paper we present a non blocking token ring based checkpointing algorithm to tolerate the faults in the mobile computing environment. It is a single phase algorithm neither having the overhead of temporary checkpoints nor using dependency vector; and also it avoids the avalanche effect. Results shows that it outperforms two-phase algorithms.
Keywords
Checkpointing, Nonblocking and Token Ring.- Personalized Ontology Based on Consumer Emotion and Behavior Analysis
Abstract Views :187 |
PDF Views:2
Authors
Source
Data Mining and Knowledge Engineering, Vol 6, No 1 (2014), Pagination: 17-20Abstract
This paper will document the relationship between the consumer and their behaviors. Using this technique the consumers can use the web to find the information about the product and services. Ontologism can be constructed manually using ontology but the process can be tedious. The integration of knowledge acquisition with machine learning facilitates research toward automating the ontology generation process. Many approaches have been investigated for generating ontology. These include Natural Language Processing (NLP) techniques association rule mining hierarchical clustering translation from relational databases and Formal Concept Analysis. However these techniques focus mainly on constructing concept hierarchies from text documents or relational databases. They can also be used to find groups of people with similar interests. A major problem of traditional association rule mining techniques is that each item in a transaction is considered only to either exist or not. Thus, the user's preference and interest in each transaction item cannot be precisely represented. Since the concepts of preference and interest are fuzzy data fuzzy logic can be applied. For example combine fuzzy association rule mining and case-based reasoning (CBR) to improve the quality of web access pattern prediction. The fuzzy rule set was found to perform better in prediction accuracy and rule coverage than traditional rule set.Keywords
Behavioral Tracking, Semantic Web, Knowledge Integration, Natural Language Processing.- Multi-Objective Fault Tolerance Model for Scientific Workflow Scheduling on Cloud Computing
Abstract Views :167 |
PDF Views:1
Authors
S. Anuradha
1,
P. Kanmani
2
Affiliations
1 Department of Computer Science, Shri Sakthikailassh Women’s college, Salem, Tamil Nadux, IN
2 Department of Computer Science, Thiruvalluvar Government Arts College, Namakkal, Tamil Nadu, IN
1 Department of Computer Science, Shri Sakthikailassh Women’s college, Salem, Tamil Nadux, IN
2 Department of Computer Science, Thiruvalluvar Government Arts College, Namakkal, Tamil Nadu, IN
Source
International Journal of Computer Networks and Applications, Vol 9, No 4 (2022), Pagination: 438-450Abstract
Cloud computing is used for large-scale applications. Therefore, a lot of organizations and industries are moving their data to the cloud. Nevertheless, cloud computing might have maximum failure rates because of the great number of servers and parts with a high workload. Reducing the false in scheduling is a challenging task. Hence, in this study, an efficient multi-objective fault detector strategy using an improved Squirrel Optimization Algorithm (ISOA) in cloud computing is proposed. This method can effectively reduce energy consumption, makespan, and total cost, while also tolerating errors when planning scientific workflows. To increase the detection accuracy of failures, the Active Fault Tolerance Mechanism (PFTM) is used. Similarly, the reactive fault tolerance mechanism (RFTM) is used for processor failures. The efficiency of the proposed approach is analysed based on various measurements and performance compared to other approaches.Keywords
VM Failure, Overloaded, Under Load, Squirrel Optimization Algorithm, Pro-Active Fault Tolerance, Reactive Fault Tolerance, Scheduling, Migration.Full Text
References
- S.M.Jaybhaye and Vahida Z. Attar, “A Review on Scientific Workflow Scheduling in Cloud Computing”, Proceedings of the 2nd International Conference on Communication and Electronics Systems (ICCES 2017) IEEE Xplore Compliant - Part Number: CFP17AWO-ART, ISBN: 978-1-5090-5013-0
- Bhaskar Prasad Rimal, Martin Maier, “Workflow Scheduling in Multi- Tenant Cloud Computing Environments”, IEEE Transactions on parallel and distributed systems , Vol 28, No. 1, Jan 2017, pp 290-304.
- G. Natesan and A. Chokkalingam, “Multi-Objective Task Scheduling Using Hybrid Whale Genetic Optimization Algorithm in Heterogeneous Computing Environment,” Wireless Personal Communications, 2019.
- G. Juve and E. Deelman, “Scientific Workflows in the Cloud,” Grids, Clouds and Virtualization, pp. 71–91, 2011
- S. Saeedi, R. Khorsand, S. Ghandi Bidgoli, and M. Ramezanpour, “Improved many-objective particle swarm optimization algorithm for scientific workflow scheduling in cloud computing,” Computers and Industrial Engineering, vol. 147, no,June, p. 106649, 2020
- Juve, Gideon, Ann Chervenak , EwaDeelman, ShishirBharathi, Gaurang Mehta, and Karan Vahi, “Characterizing and profiling scientific workflows”, Future Generation Computer Systems, Vol. 29, Issue 3 , 2013: 682-692.
- Fan Zhang, Junwei Cao, Kai Hwang,Keqin Li, and Samee U. Khan, “Adaptive Workflow Scheduling on Cloud Computing Platforms with Iterative Ordinal Optimization”, IEEE Transaction on cloud computing , Vol 3, No. 2, April/June 2015, pp 156-168.
- Tongyi Zheng and Weili Luo, “An Improved Squirrel Search Algorithm for Optimization”, Hindawi Complexity Volume 2019, Article ID 6291968, 31 pages [9] Yong Zhao, IoanRaicu, Shiyong Lu, Wenhong Tian, Heng Liu, Enabling scalable scientific workflow management in the Cloud”, Future Generation Computer Systems, 23 October 2014.
- Heyang Xu, Bo Yang, Weiwei Qi and Emmanuel Ahene, “A Multi-objective Optimization Approach to Workflow Scheduling in Clouds Considering Fault Recovery”, KSII Transations on internet and information system vol. 10, NO 3, Mar. 2016.
- Ahmad, Z.; Jehangiri, A.I Ala’anzy, M.A. Othman, M.Umar, A.I. “Fault-Tolerant and Data-Intensive Resource Scheduling and Management for Scientific Applications in Cloud Computing”, Sensors 2021, 21, 7238.
- Zhongjin Li, Jiacheng Yu, Haiyang Hu, Jie Chen, Hua Hu, Jidong Ge and Victor Chang, “Fault-Tolerant Scheduling for Scientific Workflow with Task Replication Method in Cloud”, The 3rd International Conference on Internet of Things, Big Data and Security (IoTBDS 2018), pages 95-104 ISBN: 978-989-758-296-7
- J. KokKonjaang and Lina Xu, “Multi-objective workflow optimization strategy (MOWOS) for cloud computing”, Journal of Cloud Computing: Advances, Systems and Applications, (2021) 10:11
- Yuandou Wang, Hang Liu, Wanbo Zheng, Yunni Xia, Yawen Li, Peng Chen, KunyinGuo, and Hong Xie, “Multi-Objective Workflow Scheduling With Deep-Q-Network-Based Multi-Agent Reinforcement Learning”, Special Section on Mobile Service Computing with Internet of Things, February 11, 2019.
- T. Prem Jacob, K. Pradeep, “A Multi-Objective Optimal Task Scheduling in Cloud Environment Using Cuckoo Particle Swarm Optimization”, Wireless Personal Communications · November 2019 DOI: 10.1007/s11277-019-06566-w.
- Amandeep Varma, SakshiKushal, “A hybrid multi-objective Particle Swarm Optimization for scientific workflow scheduling”, Parallel computing volume 62, February 2017, Pages 1-19.
- Neeraj Arora, Rohitash Kumar Banyal, “HPSOGWO: A Hybrid Algorithm for Scientific Workflow Scheduling in Cloud Computing”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 11, No. 10, 2020.