Predictable model using Spatio Temporal Suppression in LAN
- T.Priya
- D.Vivethitha
- P.R.Ragavi
cascaded suppression, Spatio temporal suppression, Greedy algorithm, Bayesian inference.
The project introduces the idea of reducing the communication cost and to recover the data which is failed and missing. In previous method it is implemented in wireless sensor network which is not efficient because it uses battery power that leads to increase the communication cost. To reduce the communication cost it uses suppression technique that use cascaded. Even though it reduces the communication cost but it is not efficient to recover the data that which is lost are missing. To overcome this problem and to reduce the energy that are consumed by the wireless sensor network it is implemented in LAN which uses cascaded suppression that uses both spatio and temporal technique to reduce the communication. It is efficient to reduce the communication but now the problem persist in handling the failure and to interpret the missing data previously it uses retransmission and time stamp mechanism in which it is not efficient so now it uses Bayesian inference and coding theory to recover the missing and failed data.
T.Priya, D.Vivethitha, P.R.Ragavi. "Predictable model using Spatio Temporal Suppression in LAN".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 1, pp.828-832, URL :https://rjwave.org/ijedr/papers/IJEDR1401149.pdf
Volume 2 Issue 1
Pages. 828-832