TY  - JOUR
T1  - Optimal Resource Discovery and Dynamic Resource Allocation Using
Modified Hierarchal Agglomerative Clustering Algorithm and Bi-Objective
Hybrid Optimization Algorithm
AU - Durgadevi, P. AU - Srinivasan, S. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 22
SP  - 4464
EP  - 4474
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.4464.4474
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.4464.4474
KW  - Resource allocation
KW  -resource discovery
KW  -hierarchal agglomerative clustering
KW  -artificial bee colony
KW  -cuckoo search
AB  - The fundamental motive of the resource allocation is to allot the available resource in the most
effective manner. It represents the programming of tasks and the resources essential to carryout them,
simultaneous taking extreme care with regard to the available resource and the time frame. The vital motive of
this investigation is to design a technique for optimal resource discovery and dynamic resource allocation. The
innovative technique encompasses two stages such as the resource discovery and resource allocation. For
resource discovery the innovative technique utilizes the Modified Hierarchal Agglomerative Clustering
Algorithm (MHAC). Based on the MHAC algorithm the suggested tree construction is produced. Thereafter
the resources are allocated by the hybrid optimization technique. In the innovative technique, we utilize the
Hybrid Artificial Bee Colony and Cuckoo Search algorithm (HABCCS). Here, the artificial bee colony is used
to optimize the tree construction path and the cuckoo search is utilized to modify the artificial bee colony
algorithm. The optimal path choice is the consequence of the hybrid optimization approach. The new-fangled
technique allocates the available resource based on the optimal path.
ER  -