EFFICIENT DATA COLLECTION IN WIRELESS SENSOR NETWORKS WITH PATH-CONSTRAINED MOBILE SINKS

ABSTRACT   Recent work has shown that sink mobility along a constrained path can improve the energy efficiency in wireless sensor networks. Due to the path constraint, a mobile sink with constant speed has limited communication time to collect data from the sensor nodes. We propose a novel data collection scheme, called the Maximum Amount Shortest Path (MASP) that increases network throughput as well as conserves energy by optimizing the assignment of sensor nodes. MASP is formulated as an integer linear programming problem and then solved with the help of a genetic algorithm. A two-phase communication protocol based on zone partition is designed to implement the MASP scheme.

EXISTING SYSTEM Shortest Path Tree (SPT) used to choose subsink and relay data from members. It is possible that some subsinks with longer communication time with fewer members, implying that the mobile sink may collect less data than expected. Some subsinks with very short communication time with too many members the excess data traffic may result in oversaturated subsinks which are not able to transmit all data to the mobile sink in the limited communication duration. SPT method has low energy efficiency for data collection. Network throughput is also low. Network throughput depends on Data collection, number of members belongs to each subsink.

PROPOSED SYSTEM To improve amount of data collection and reduces energy consumption, we propose a novel data collection scheme, called the Maximum Amount Shortest Path (MASP) which increases the Network throughput and reduces the energy consumption. Based on the communication range of Mobile sink two parts, Direct Communication Area (DCA) called subsink which directly transmits data to mobile sink. Multihop Communication Area (MCA) called members which transmit data through subsink. MASP is assigned corresponding subsinks. MASP is to find optimized mapping between members and subsink to minimize energy consumption under some condition and data collection is maximized.

MODULES Assign Member and Subsinks Process of Assign Subsinks Process of Assign Member Genetic Algorithm Process Building Shortest Path Tree process Process of Fitness value calculation Process of Subsink Confirmation Data Collection Zone-Partition

SYSTEM ARCHITECTURE

SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS Processor : Any Processor above 500 MHz. Ram : 128Mb. Hard Disk : 10 Gb. Compact Disk : 650 Mb. Input device : Standard Keyboard and Mouse. Output device : VGA and High Resolution Monitor. SOFTWARE REQUIREMENTS Operating System : Windows 2000 and Above. Language : JDK 1.6 Data Bases : MS SQL Server 2005 Front End : Java Swing

CONCLUSION We proposed an efficient data collection scheme called MASP for wireless sensor networks with path-constrained mobile sinks. The mapping between sensor nodes and subsinks is optimized to maximize the amount of data collected by mobile sinks and balance the energy consumption. MASP has good scalability to support sensor networks with low density and multiple mobile sinks. Genetic algorithm and local search is presented to solve the MASP optimization problem.