Purpose and Justification of the project: 

The development of low-cost, low-power sensor networks has its potential impact in the development of Smart Sensor Networks, Power management, and Data dissemination protocols have been specifically designed for wireless sensor networks. Wireless sensor networks have become an important issue and have gained much attention in many research areas. In this Data Aggregation and Optimization to improve the Lifetime of Wireless Sensor Networks paper we discussed the Zigbee standard (IEEE 802.15.4) of Smart Sensor Networks describing its Architectural Framework, how it deployed power conservation techniques as specified in the IEEE 802.15.4 specification, Protocols, related issues and Applications. We have also discussed some of the wireless technologies like Blue tooth and Wi-Fi since Zigbee is such a wireless standard and compared the different aspects. 

Existing System:

  • The drawback of this approach is that it consumes the more power for the nodes on the minimum energy path, and if the nodes are failed to transmit data due to collision no other nodes take the job of the failed nodes.
  • Some few techniques are proposed to address this problem by studying the maximum lifetime routing problem. The problem focuses on the flow and transmission power to maximize the lifetime of the network, which is the time the first node in the network runs out of energy.


Presented an optimal routing and data aggregation scheme for maximizing the network Lifetime of sensor networks. By exploiting the special structure of the sensor networks and

Proposed some functions to overcome the non differentiability of optimization problem so that

The distributed solution is possible. The optimality conditions are derived and the distributed

Algorithm is designed accordingly.  This scheme significantly reduces the data traffic and improves the network lifetime. The distributed algorithm can converge to the optimal value efficiently.


  1. Convergence of the Distributed Algorithm
  2. Routing Model
  3. Data Aggregation Model 

Module Description: 

Convergence of the Distributed Algorithm

The aggregated data rate is normalized by obtaining the optimal value by the centralized MLR algorithm. The effectiveness of the distributed MLR algorithm can be observed from the normalized aggregated data rate at the sink node for various network sizes. 

Software Requirements

Java 1.4 or More


Windows 2000, XP

Hardware Requirements

Hard Disk             :           40GB and Above

RAM                                 :           256MB and Above

Processor               :           Pentium III and Above 

Future scope of Wireless sensors:

The overview of wireless sensor networks are describing about existing systems, working procedure and applications. Future scope of its is to determine reducing the cost and power consumption which can be highly useful in the future. 

This paper is written and submitted by sandeep k