TY  - JOUR
T1  - Implementation of Load Balancing Algorithm with Cloud Collaboration for Logistics
AU - Dubey, Shivani AU - Jain, Sunayana AU - Dahiya, Mamta 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 2
SP  - 507
EP  - 515
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.507.515
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.507.515
KW  - utilized
KW  -proposed DSBPalgorithm
KW  -load balancing algorithms
KW  -logistics information system
KW  -Cloud computing
KW  -applications
AB  - Cloud computing provides a facility of any data center at any location in the world. There are various
applications used in a centralized and distributed data center that suppliers and users can purchase, sell and
rent for their information and product accessing. The suppliers and user have no knowledge about where these
data centers are located and how they will be operated or maintained by using cloud collaboration. They only
know how to connect or use the applications of cloud to perform their jobs. Today, there is lot of demand of
cloud in various companies to establish their own data center. In logistics management, sharing of information
at different level by different logistics partners, users and suppliers is a big challenge. They all want that every
type of information should be shared in real time without any delay at minimum cost. For this, they need cloud
based load balancing approaches to control network traffic and overloading on the data center. Load balancing
is a distributed technique of workload for load balancing between two or more cloud servers. Load balancing
considers service providers management, high traffic and always be ready to reduce and balance peak load on
the server. Load balancing have always task to optimize resource use, virtual machine maintains data center
cost, maximize, throughput, minimize response time and minimize overload. There are so many load balancing
algorithms utilized to balance the load on the servers. In this study, we present technical review on different
load balancing algorithms.
ER  - 