Trade-Offs Involved In Using Network Computers

Tradeoff Involved In Using Network Computers

Grid computing refers to the transformation of a computer infrastructure into an integrated system that supports resource sharing between different computers. The attained network computer allows for distribution of jobs to different smaller server components of a computer (Guo, Bi, Jiang & Long, 2015). In addition, possible points of failures within the network are greatly limited since the collapse of a single server does not interfere with the entire system; there are a couple of resources capable of picking up the load (Keerthika & Suresh, 2015). For effective operations of the networked computing systems there are certain standards of operations that must be attained. Deviation from the identified standards does not only affect the overall operation of the system but also had significant effects on the transparency of the resources to the users.

 

The major trade-offs of using grid computing as an organization’s standards entails the development of the grid standards and adhering to the best practices. A balance must be attained between developing an appropriate networked computers as well as enhancing the satisfaction of the users through adhering to the best practice guidelines. According to Keerthika and Suresh (2015) proper allocation and use of resources within the computational grid is mandatory to support proper sharing of resources. Similarly, the users wishing to make use of the resources have to attain maximum satisfaction in their usage. To achieve a balance, load balancing, smart optimization approaches, fairness based algorithms must be put in place. Guo, Bi, Jiang and Long (2015) have also pointed out that different approaches that  are based on optimization and brokering algorithms mechanisms are resolutions to improving the performance of the system and optimizing the use of resources in grid computing. On the other hand, adhering to the best practice standards ensures that user’s satisfaction is attained. As such, the major trade-offs involved in the use of grid computing concerns the attainment of a balance between a higher system performances and enhance user satisfaction.

Stand-alone computers that are mainly used by individuals at home differ largely from those operating in a grid. The major difference is observed in their location and ability to share information from within the computers. Moreover, the set-up, security features and benefits of a stand-alone computer also differ from a networked computer. According to Kaur and Rai (2014) networked computers have a domain security policy that applies to all the computers within the network. On the contrary, a stand-alone computer used at home has its own security management system to bar intruders. The applications in a stand-alone computer are available within its hard disk and do not allow for resource sharing with other computers. On the other hand, networked computers share resources such as files, disk drives and thus allows for sharing of information amongst users of the computers within the same network.

The benefits that can be attained from using a computer alone also differ from using the computer in a grid. When using a stand-alone computer, one is not required to have a distinct administrator, thus able to install programs and modify files (Kaur & Rai (2014). This benefit is not observed in case one uses a networked computer. Nevertheless, individuals using computers in a grid enjoys the benefit of not being involved in making updates or the management of files since they are carried out by the assigned administrator.

References

Guo, Z., Bi, S., Jiang, Y., & Long, Z. (2015). Mobile Network Computers Should be the Terminal of Mobile Communication Networks. Wireless Personal Communications85(4), 1895-1904.

Keerthika, P., & Suresh, P. (2015). A Hierarchical Load Balanced Fault tolerant Grid Scheduling Algorithm with User Satisfaction’. WSEAS Transactions on Computers14

Kaur, K., & Rai, A. K. (2014). A comparative analysis: Grid, cluster and cloud computing. International Journal of Advanced Research in Computer and Communication Engineering3(3), 5730-5734.