Round Robin scheduling algorithm is the most often used scheduling algorithm in timesharing systems as it is fair to all processes and is starvation free. But along with these advantages it suffers from some drawbacks such as more number of context switches, long waiting and long turnaround time. The main objective of this paper is to improve existing round robin algorithm by extending the time quantum in real time for candidate processes in such a manner that its fairness property is not lost. The proposed algorithm in this paper finds the remaining time of a process in its last turn and then based on some threshold value, decides whether its time quantum should be extended or not. A mathematical model has been developed to prove that the proposed algorithm works better than the conventional round robin algorithm. The result of experimental study also shows that the proposed improved version of round robin algorithm performs better than the conventional round robin algorithm in terms various performance metrics such as number of context switches, average waiting and turnaround time. General TermsScheduling, Round Robin Scheduling.

RFID (Radio Frequency IDentification) is recently becoming popular, and plays an important role in ubiquitous society due to its deploying convenience and economic efficiency. Furthermore, RFID nowadays comes into the spotlight as a technology to substitute the barcode system. RFID technology, on the other hand, is jeopardized from various attacks and problems preventing widespread RFID deployment. We focus ourselves on designing a secure and efficient protocol for authentication between tag and reader in a RFID system. There must be a trade-off between scalability and untraceability. However, we try to keep the constant computational time in back-end server regardless of the number of tags when designing an untraceable protocol.

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Today most of the personal and professional communication is done using the electronic media such as E-Mailing, SMS etc. But these all services also suffer from the problem of unwanted messages or the communicating information called Spam. The Spam Message can be an email virus, charity latter, commercial advertisement etc. But it affects the user time, memory and the attention. In this paper, a DCA based improved decision tree approach is suggested to identify the spam emails over the dataset. The work is implemented in integrated weka environment. The obtained result from the system shows the effective identification of spam mails over the dataset.

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