Genetic-variable neighborhood search with thread replication for mobile cloud computing. Issue 5 (3rd September 2017)
- Record Type:
- Journal Article
- Title:
- Genetic-variable neighborhood search with thread replication for mobile cloud computing. Issue 5 (3rd September 2017)
- Main Title:
- Genetic-variable neighborhood search with thread replication for mobile cloud computing
- Authors:
- Singh, Rachhpal
- Abstract:
- Abstract: The resource-intensive resettlement procedure and inherent restrictions of the wireless medium obstruct the understanding of faultless implementation in mobile cloud computing (MCC) surroundings. In MCC, transfer of thread execution to high end servers allows the processing of those jobs which demand more resources on the mobile equipment. Hence, implementing the application with stumpy cost, least overhead and non-obtrusive relocation is a demanding research area in MCC. Many scheduling mechanisms have been proposed so far to balance the load between the given set of mobile servers, but it is found to be NP-Hard problem. Therefore, evolutionary techniques are required to balance the load among mobile servers. Genetic Algorithm (GA) has been verified to be fine by jumble up the key values, but it becomes unsuccessful to strengthen the exploration in the rising areas. In Variable Neighborhood Search (VNS), local exploration technique is implemented continually to evaluate optimistic outcomes in neighborhood to attain local best solution. But VNS is still prone to premature convergence traps only because of limited search capability. Therefore hybridization with non-global finding techniques may conquer the limitations and guide the dominant search mechanisms to some extent. The GA along with VNS using thread replication (GVNSTR) is implemented to set stability of non-local searching and local utilization for an evolutionary processing period and get the optimizedAbstract: The resource-intensive resettlement procedure and inherent restrictions of the wireless medium obstruct the understanding of faultless implementation in mobile cloud computing (MCC) surroundings. In MCC, transfer of thread execution to high end servers allows the processing of those jobs which demand more resources on the mobile equipment. Hence, implementing the application with stumpy cost, least overhead and non-obtrusive relocation is a demanding research area in MCC. Many scheduling mechanisms have been proposed so far to balance the load between the given set of mobile servers, but it is found to be NP-Hard problem. Therefore, evolutionary techniques are required to balance the load among mobile servers. Genetic Algorithm (GA) has been verified to be fine by jumble up the key values, but it becomes unsuccessful to strengthen the exploration in the rising areas. In Variable Neighborhood Search (VNS), local exploration technique is implemented continually to evaluate optimistic outcomes in neighborhood to attain local best solution. But VNS is still prone to premature convergence traps only because of limited search capability. Therefore hybridization with non-global finding techniques may conquer the limitations and guide the dominant search mechanisms to some extent. The GA along with VNS using thread replication (GVNSTR) is implemented to set stability of non-local searching and local utilization for an evolutionary processing period and get the optimized solution. … (more)
- Is Part Of:
- International journal of parallel, emergent and distributed systems. Volume 32:Issue 5(2017)
- Journal:
- International journal of parallel, emergent and distributed systems
- Issue:
- Volume 32:Issue 5(2017)
- Issue Display:
- Volume 32, Issue 5 (2017)
- Year:
- 2017
- Volume:
- 32
- Issue:
- 5
- Issue Sort Value:
- 2017-0032-0005-0000
- Page Start:
- 486
- Page End:
- 501
- Publication Date:
- 2017-09-03
- Subjects:
- Mobile cloud computing -- load balancing -- hybrid genetic-variable neighborhood search -- energy efficient -- genetic algorithm
Parallel computers -- Periodicals
Electronic data processing -- Distributed processing -- Periodicals
Computer algorithms -- Periodicals
004.35 - Journal URLs:
- http://www.tandfonline.com/toc/gpaa20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/17445760.2016.1188386 ↗
- Languages:
- English
- ISSNs:
- 1744-5760
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.441300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 2895.xml