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Dhindsa, Kanwalvir Singh
- Hybrid Scheduling Algorithm for Efficient Load Balancing In Cloud Computing
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Authors
Affiliations
1 CSE & IT Deptt., BBSB Engineering College, Fatehgarh Sahib, Punjab, IN
2 CSE & IT Deptt., BBSB Engineering College, Fatehgarh Sahib, Punja, IN
1 CSE & IT Deptt., BBSB Engineering College, Fatehgarh Sahib, Punjab, IN
2 CSE & IT Deptt., BBSB Engineering College, Fatehgarh Sahib, Punja, IN
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International Journal of Advanced Networking and Applications, Vol 8, No 5 (2017), Pagination: 3181-3187Abstract
In cloud computing environment, various users send requests for the transmission of data for different demands. The access to different number of users increase load on the cloud servers. Due to this, the cloud server does not provide best efficiency. To provide best efficiency, load has to be balanced. The highlight of this work is the division of different jobs into tasks. The job dependency checking is done on the basis of directed acyclic graph. The dependency checking the make span has to be created on the basis of first come first serve and priority based scheduling algorithms. In this paper, each scheduling algorithm has been implemented sequentially and the hybrid algorithm (round robin and priority based) has also been compared with other scheduling algorithms.
Keywords
Closest Data Center, Optimized Response Time, Dynamic Load, Round-Robin Scheduling, Priority Based Scheduling.Full Text
References
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- Load Balancing in Cloud Computing Environment:A Comparative Study of Service Models and Scheduling Algorithms
Abstract Views :176 |
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Authors
Affiliations
1 CSE & IT Deptt., BBSB Engineering College, Fatehgarh Sahib, Punjab, IN
1 CSE & IT Deptt., BBSB Engineering College, Fatehgarh Sahib, Punjab, IN
Source
International Journal of Advanced Networking and Applications, Vol 8, No 6 (2017), Pagination: 3246-3252Abstract
Load balancing is a computer networking method to distribute workload across multiple computers or a computer cluster, network links, central processing units, disk drives, or other resources, to achieve optimal resource utilization, maximize throughput, minimize response time, and avoid overload. Using multiple components with load balancing, instead of a single component, may increase reliability through redundancy. The load balancing service is usually provided by dedicated software or hardware, such as a multilayer switch or a Domain Name System server. In this paper, the existing static algorithms used for simple cloud load balancing have been identified and also a hybrid algorithm for developments in the future is suggested.Keywords
Round-Robin Scheduling, Data Center, Priority Based Scheduling, Cloud Computing, Load Balancing.Full Text
References
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- Android Malware Detection in Official and Third Party Application Stores
Abstract Views :183 |
PDF Views:1
Authors
Affiliations
1 I.K Gujral Punjab Technical University, Punjab, IN
2 Baba Banda Singh Bahadur Engg College, Fatehgarh Sahib, Punjab, IN
1 I.K Gujral Punjab Technical University, Punjab, IN
2 Baba Banda Singh Bahadur Engg College, Fatehgarh Sahib, Punjab, IN
Source
International Journal of Advanced Networking and Applications, Vol 9, No 4 (2018), Pagination: 3506-3509Abstract
Android is one of the most popular operating system for mobile devices and tablets. The growing number of Android users and open source nature of this platform has also attracted attackers to target Android devices. This paper presents the static and dynamic analysis of the Android applications in order to detect malware. In this work, we have performed permission based and behavioural based filtering of Android applications with the help of malware analysis tools. Our results revel that 80% of the applications request for dangerous permissions. 13% applications consist of malicious activities. Most of the applications are interested in the device data like contact lists, IMEI, IMSI, SMS etc. These results clearly indicate the need for better security measures for Android apps.Keywords
Android Malware, Static Analysis, Dynamic Analysis, Permissions, Applications.Full Text
References
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- Efficient Task Scheduling using Load Balancing in Cloud Computing
Abstract Views :184 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib, Punjab, IN
1 Department of CSE, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib, Punjab, IN
Source
International Journal of Advanced Networking and Applications, Vol 10, No 3 (2018), Pagination: 3888-3892Abstract
Workflow scheduling is a challenging field in computing in which tasks are scheduled according to the user requirement and it becomes costly due to the quality of service demand by the user. Cloud environment has been deployed for this work so as to reduce the overall cost. To maintain & utilize resources in the cloud computing scheduling mechanism is needed. Many algorithms and protocols are used to manage the parallel jobs and resources which are used to enhance the performance of the CPU in the cloud environment. Particles swarm Optimization (PSO) and Grey Wolf Optimization (GWO) are used for effective scheduling. This work is based on the optimization of Total execution time and total execution cost. The results of the proposed approach are found to be effective in compare to existing methods. The particle swarm optimization is initialized by using Pareto distribution. TET and TEC illustrated the minimized cost and time by using the GWO to converge the decision of virtual machine. Thus the work concludes that GWO performs better in compare to existing BAT algorithm.Keywords
Particles Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Virtual Machine, BAT Algorithm.Full Text
References
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- Flow-Based Attack Detection and Defense Scheme against DDoS Attacks in Cluster Based Ad Hoc Networks
Abstract Views :164 |
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Authors
Affiliations
1 Dept. of RIC, I.K. Gujral Punjab Technical University, Kapurthala, Punjab, IN
2 Dept. of CSE, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib, Punjab, IN
3 Dept. of Computer Application, Guru Nanak Khalsa College, Yamuna Nagar, Haryana, IN
1 Dept. of RIC, I.K. Gujral Punjab Technical University, Kapurthala, Punjab, IN
2 Dept. of CSE, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib, Punjab, IN
3 Dept. of Computer Application, Guru Nanak Khalsa College, Yamuna Nagar, Haryana, IN
Source
International Journal of Advanced Networking and Applications, Vol 10, No 4 (2019), Pagination: 3905-3910Abstract
DDoS attacks in MANETs needs to be handled as early as possible so as to avoid them to reach the victim node. DDoS attacks are difficult to detect due to their features like varying attack intensity, large amount of packets etc. so it becomes necessary to distinguish and filter attack traffic in source or intermediate clusters. Here the cluster heads will uses flow based monitoring schemes to identify the suspicious behaviours of incoming traffic in each clusters. Cluster head constructs flows from the incoming traffic and computes normalized entropy for specific time windows. The normalized entropy is compared against threshold entropy to identify the presence of suspicious flows. Later packet rate of suspicious flow is calculated and compared against packet rate entropy to identify the suspicious flows. Later the suspicious flow information is shared with neighbouring cluster heads to further confirm the presence of DDoS attack or not. If DDoS attack is confirmed the packets related to suspicious flows will be discarded. The efficiency and accuracy of proposed attack detection algorithm is evaluated using some performance metrics.Keywords
Clustering, Distributed Denial of Service (DDoS) Attacks, Defense, Flow, MANETs.Full Text
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