Resource Discovery and Load Monitoring in Heterogeneous Grid Environment
The decentralized broker selects computational re- sources based on actual job requirements, job charac- teristics, and information provided by the resources.A client is a user who submit a job to the server node. A job refers the task which is to be carried out on computational grid. Then job submitted on sched- uler and scheduler will divide a job into smaller tasks and sends that tasks to the available resources.The grid deals with large scale and ever-expanding en- vironment which contains million of users and re- sources. For this reason, resource selection has been a challenging task. This paper presents a method that achieves efficient Grid resource discovery by form- ing and maintaining autonomous resource groups and then monitoring load by using Ganglia monitoring system.
The higher education institutions (HEIs) are engaging with multi modal delivery for its courses and diversifying teaching and learning strategies. The ::: reasons for multi modal delivery range from desire to increase enrolment to providing educational access to learners far and wide. In the university of the South ::: Pacific (USP), learners constitute a diverse demographic and equally diverse is the learners’ geographical context. However, there is a need to listen to learners’ voice in light of their changing learning needs. The study examines learners’ preference for learning environments with the aim to understand the reasons for their preference for a particular learning environment. The study has implications for all HEIs especially if they wish to engage learners from diverse backgrounds.