The main aim of this research work is to compress an image that is to remove the redundancies from
an image to such an extent that after decompression the image should be reasonably recognized. In this
approach the proposed, newly constructed multiscaling ancl mitiwavelet functions are used in multiwavelet
Lransform. This modified multiwavelet transforrn is implemented to achieve better image compression ancl decompression. We have also implemented otl'rer multiwavelet transforms such as GHM, df, se , Bih52S and
Cadrbal2 and compared tl're results with proposed modified multiwavelet transform. The results are compared
based on image compression parameters such-as entropy, redundancy, compression ratio, peak signal-to-1oise
ratio and mean square eiror' It is found that the results'of proposed modified multiwavelei transform is better
compared to other multiwavelet trar-rsformation technrques....
Among many solutions for reducing the energy consumptions of sensor nodes, scheduling the active and sleep cycles of sensor nodes is significantly important for Wireless Sensor Network (WSN). This solution allows a small number of sensors to be in active mode that also guarantees the coverage of the whole network area and all other sensors in inactive or sleep mode by turning their radio off. Recently, many node scheduling schemes have been proposed in the literature. However, most of the schemes are designed for static sensor nodes which are not feasible for the WSN applications where, mobility of sensors is significantly important. For instance, static node scheduling schemes cannot work in health monitoring and habitat monitoring since sensors attached to human body and animals are mobile. Moreover, most existing approaches only consider achieving energy efficiency but reducing end-to-end delay and collision probability is also important for the emergency real-time and many other applications.
Thus, this project introduces an efficient and coverage-based node activity scheduling scheme for Mobile WSN (MWSN) in terms of energy consumptions and end-to-end data transmission delay....