Modeling a Fault Tolerant Control Mechanism for Cloud e-marketplaces using Raft Consensus Protocol (RCP)

Modeling a Fault Tolerant Control Mechanism for Cloud e-marketplaces using Raft Consensus Protocol (RCP)

Ige A.O.a, Akingbesote A.O.a, Oriola O.a, and Aranuwa F.O.a

aComputer Science Department, Adekunle Ajasin University, Akungba – Akoko, Ondo State, Nigeria

American Journal of Computer Sciences and ApplicationsThe evolution of marketplaces started from the traditional marketplace, the internet marketplace, the web service marketplace, the grid marketplace, before moving to cloud e-marketplace. The need to have rapid access to various service by different customers brought about cloud e-marketplaces. The goal of the cloud e-marketplace is to attract the biggest possible number of buyers while ensuring a reduced waiting time for customers and maximized profit for cloud service providers. Challenges like security, performance and fault tolerance are of great concern in the cloud market. While discussion on the issue of security and performance are ongoing, that of fault tolerance is yet to be fully addressed. Although some researchers have proposed the use of multiple servers in achieving the main idea of the cloud e-marketplace, different kinds of faults still affects the performance of cloud e-market. Balancing of providers’ cost and customers’ waiting time is still a major concern. Various techniques have been proposed in solving these problems. However, these techniques only work in a static environment where these servers can be faulty which may lead to long waiting time. We propose the use of Raft consensus protocol as our fault tolerant approach. We use the dynamic environment as against the already static approached already discussed in the literature. In the dynamic environment, two fault tolerant centers that are capable of surviving failure caused by server overload or congestion are used. These are primary and the reservoir centers. The Raft Consensus Protocol is used in both centers to coordinate the servers and make sure that each of the servers exist either as the leader, a candidate, or a as a follower. A waiting time counter algorithm is developed that directs customers request to the primary center when waiting time t<N, and to the reservoir center when waiting time t≥N. We set up our consumer arrival time, the service time is recorded and our N is set to 5 sec. Furthermore, the result of this research when compared to existing system using various performance metrics showed that the developed mechanism allowed optimal performance in the servers used for cloud e-marketplaces’ service delivery, thereby causing reduced waiting time and increased profit.

Keywords: marketplaces, cloud e-market, raft consensus protocol, waiting time, profit.

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Ige A.O., Akingbesote A.O., Oriola O., and Aranuwa F.O., Modeling a Fault Tolerant Control Mechanism for Cloud e-marketplaces using Raft Consensus Protocol (RCP). American Journal of Computer Sciences and Applications, 2019; 3:14


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