TY - JOUR
T1 - Heuristic search based localization in mobile computational grid
AU - Sahu, Dinesh Prasad
AU - Singh, Karan
AU - Manju, Manisha
AU - Taniar, David
AU - Tuan, Le Minh
AU - Son, Le Hoang
AU - Abdel-Basset, Mohamed
AU - Long, Hoang Viet
PY - 2019/6/12
Y1 - 2019/6/12
N2 - In recent years, the number of cell phones in society has increased drastically and they are getting popular due to their computational ability and adaptability. Resource provisioning is important, but still remains NP-hard problem in mobile computational grid (MCG). Once the jobs are assigned to the MCG, the main challenge is how to identify the correct resource according to the job's requirement and use them to execute the sub-jobs. The heuristic methods such as Min-Min, Max-Min, and HEFT can be used to select appropriate resources from the MCG that is assigned for job execution. Since the computational nodes are static and mobile in nature, the performance of such heuristics is not as expected. Such heuristics suffers from low throughput and low speedup. The process of localization is used in a wireless sensor network with good results. The proposed model uses heuristics and localization process for optimizing the quality of service parameter localization, normalized speedup, and throughput in MCG, with the concept of grid nodes available in MCG. The observation shows significant improvement in the quality of service parameter localization, normalized speedup, and throughput in MCG. The proposed model HGLA and MIN-MIN, MAX-MIN, and HEFT are compared with respect to localization, speedup, and throughput. The results reveal that the proposed model shows better performance over MIN-MIN, MAX-MIN, and HEFT.
AB - In recent years, the number of cell phones in society has increased drastically and they are getting popular due to their computational ability and adaptability. Resource provisioning is important, but still remains NP-hard problem in mobile computational grid (MCG). Once the jobs are assigned to the MCG, the main challenge is how to identify the correct resource according to the job's requirement and use them to execute the sub-jobs. The heuristic methods such as Min-Min, Max-Min, and HEFT can be used to select appropriate resources from the MCG that is assigned for job execution. Since the computational nodes are static and mobile in nature, the performance of such heuristics is not as expected. Such heuristics suffers from low throughput and low speedup. The process of localization is used in a wireless sensor network with good results. The proposed model uses heuristics and localization process for optimizing the quality of service parameter localization, normalized speedup, and throughput in MCG, with the concept of grid nodes available in MCG. The observation shows significant improvement in the quality of service parameter localization, normalized speedup, and throughput in MCG. The proposed model HGLA and MIN-MIN, MAX-MIN, and HEFT are compared with respect to localization, speedup, and throughput. The results reveal that the proposed model shows better performance over MIN-MIN, MAX-MIN, and HEFT.
KW - HEFT
KW - localization ratio
KW - MAX-MIN
KW - MIN-MIN
KW - Mobile agent
KW - mobility
KW - resource allocation
KW - resource provisioning
KW - speed-up
UR - http://www.scopus.com/inward/record.url?scp=85068344787&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2019.2922400
DO - 10.1109/ACCESS.2019.2922400
M3 - Article
AN - SCOPUS:85068344787
SN - 2169-3536
VL - 7
SP - 78652
EP - 78664
JO - IEEE Access
JF - IEEE Access
M1 - 8735685
ER -