چکیده (انگلیسی):

Cloud computing is a model that points at streamlining the on-demand provisioning of software, hardware
and data as services and providing end-users with flexible and scalable services accessible through the
Internet. The main objective of the proposed approach is to maximize the resource utilization and provide a
good balanced load among all the resources in cloud servers. Initially, a load model of every resource will
be derived based on several factors such as, memory usage, processing time and access rate. Based on the
newly derived load index, the current load will be computed for all the resources shared in virtual machine
of cloud servers. Once the load index is computed for all the resources, load balancing operation will be
initiated to effectively use the resources dynamically with the process of assigning resources to the
corresponding node to reduce the load value. So, assigning of resources to proper nodes is an optimal
distribution problem so that many optimization algorithms such as genetic algorithm and modified
genetic algorithm are utilized for load balancing. These algorithms are not much effective in providing
the neighbour solutions since it does not overcome exploration and exploration problem. So, utilizing the
effective optimization procedure instead of genetic algorithm can lead to better load balancing since it is
a traditional and old algorithm. Accordingly, I have planned to utilize a recent optimization algorithm,
called firefly algorithm to do the load balancing operation in our proposed work. At first, the index table
will be maintained by considering the availability of virtual servers and sequence of request. Then, load
index will be computed based on the newly derived formulae. Based on load index, load balancing
operation will be carried out using firefly algorithm. The performance analysis produced expected results
and thus proved the proposed approach is efficient in optimizing schedules by balancing the loads. The
average time obtained for the proposed approach is 0.934 ms.