No abstract

No abstract

Several challenges address the existing e-Assessment systems, such as accurate evaluation, security and data privacy, performance, scalability etc. Our focus in this paper is on e-Assessment scalability and performance. We have developed a new SOA architecture of a cloud hosted e-Assessment system to achieve sustainable performance as a highly scalable and elastic solution. The proposed organization solution is based on three modules (subsystems): management module, reporting module, and assessment module. The built in logic enables an efficient environment where minimum resources will be utilized during exploitation. The proposed system organization ensures that the assessment module, as active subsystem for each assessment, will work with much smaller data compared to the centralized one. The cost model developed for this solution analysis this cloud based solution against the existing e-Assessment web application. Therefore, we expect that this solution will have several benefits, like overall cost reduction and better performance.

No abstract

Abstract-Cloud service providers offer their customers to rent or release hardware resources (CPU, RAM, HDD), which are isolated in virtual machine instances, on demand. Increased load on customer applications or web services require more resources than a physical server can supply, which enforces the cloud provider to implement some load balancing technique in order to scatter the load among several virtual or physical servers. Many load balancers exist, both centralized and distributed, with various techniques. In this paper we present a new solution for a low level load balancer (L3B), working on a network level of OSI model. When a network packet arrives, its header is altered in order to forward to some end-point server. After the server replies, the packet's header is also changed using the previously stored mapping and forwarded to the client. Unfortunately, the results of the experiments showed that this implementation did not provide the expected results, i.e., to achieve linear speedup when more server nodes are added.