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Multiresolution Data Integration using Mobile Agent in Distributed Sensor Networks
Abstract-
This project will provide the use of the mobile agent paradigm to improved infrastructure for data integration in distributed sensor network (DSN). For this We proposed mobileagent-based DSN to denote MADSN Here Instead of moving data to processing elements for data integration, as is typical of a client/server paradigm, MADSN moves the processing code to the data locations. This saves network bandwidth and provides an effective means for overcoming network latency, since large data transfers are avoided. Our major contributions are the use of mobile agent in DSN for distributed data integration between DSN and MADSN approaches.
System Analysis
Existing System
The Existing is DSN consists of a set of sensor nodes, a set of processing elements (PEs), and a communication network interconnecting
the various PEâ„¢s . One or more sensors is associated with one PE.
One sensor can report to more than one PE. A PE and its associated
sensors are referred to as a cluster.
Data are transferred from sensors to their associated PE(s) where the data integration takes place. Pes can also coordinate with each other to achieve a better estimation of the environment and report to higher level PEs. That is only the
lowest-level PEs are connected to the sensor nodes. Higher-level PEs
only connect to lower-level PEs, but not the sensor nodes.
Drawbacks Of Existing System
The client/server model is not appropriate for data
integration in DSNs.
First, the data integration at the server requires
data transfer from local sensor nodes. When the size of data file is
large and the number of sensor node is big, the network traffic can be
extremely heavy, resulting in poor performance of the system.
Second, suppose connection-oriented service is used (e.g., ftp application uses
protocol), the client/server model requires the network connection to
be alive and healthy the entire time a data transfer is taking place. If the
connection goes down, both the client and the server have to wait until
the connection is recovered to finish the data transfer and do further
analysis, which will affect the system performance as well.
Third, the client/server-based DSN cannot respond to the load changing in
real time. When more sensors are deployed, it cannot perform load
balancing without changing the structure of the network.

Advantages Of Proposed System
This project describes the use of the mobile agent paradigm to design an improved infrastructure for data integration in distributed sensor network (DSN).We use the acronym MADSN to denote the proposed mobile- agent-based DSN. Compared to the traditional client/server paradigm used in DSN, where data are moved from the client to the processing center, MADSN moves the processing code to the data locations. This saves network bandwidth and provides an effective means for overcoming network latency, since large data transfers are avoided.
Proposed system is sensor technology allow better, cheaper, and
smaller sensors to be used in both military and civilian applications,
especially when the environment is harsh, unreliable, or even adversarial.
A large number of sensors are usually deployed in order
to achieve quality through quantity.
On the other hand, sensors typically communicate through wireless networks where the network bandwidth is much lower than for wired communication. These issues bring new challenges to the design of DSNs.
First, data volumes being integrated are much larger. Second, the communication bandwidth for wireless network is much lower.
Third, the environment is more unreliable, causing unreliable network connection, noisy background, and increasing the likelihood of input data to be in faulty.
Network bandwidth requirement is reduced. Instead of passing large amounts of raw data over the network through several round trips, only the agent with small size is sent. This is especially important for real-time applications and where the communication is through low-bandwidth wireless connections.
Better network scalability. The performance of the network is not affected when the number of sensor is increased. Agent architectures that support adaptive network load balancing could do much of a redesign automatically .
Extensibility. Mobile agents can be programmed to carry taskadaptive
fusion processes which extends the capability of the system.
Stability. Mobile agents can be sent when the network connection is alive and return results when the connection is re-established. Therefore, the performance of MADSN is not much affected by the reliability of the network




Important problems related to MADSN design: the distributed data integration problem, and the optimum performance problem. We show that by applying multiresolution analysis at each sensor node instead of processing element, MADSN saves up to 90% of data transfer time. We analyze the conditions under which MADSN performs better than DSN and the conditions under which MADSN achieves its optimum performance. The conditions are determined by a set of parameters, and the most important ones include the network transfer rate, the overhead ratio between DSN and MADSN, and the total number of sensor nodes.
Modules:-
1.Processing Element
Processing Element is a mobile device, it requires data from sensor nodes For this PE will request a process from Agent Server for agent and processing element to communicate with each other, and for processing element to access agentâ„¢s private data buffer.

2.Agent Server
Agent Server adopts a new computation paradigm: data stay at the local site, while the integration process (code) is moved to the data sites. By transmitting the computation engine instead of data, MADSN offers Mobile Agent for this important benefits.
¢ Network bandwidth requirement is reduced. Instead of passing large amounts of raw data over the network through several round trips, only the agent with small size is sent. This is especially important for real-time applications and where the communication is through low-bandwidth wireless connections.
¢ Better network scalability. The performance of the network is not affected when the number of sensor is increased. Agent architectures that support adaptive network load balancing could do much of a redesign automatically .
¢ Extensibility. Mobile agents can be programmed to carry task adaptive fusion processes which extends the capability of the system.
¢ Stability. Mobile agents can be sent when the network connection is alive and return results when the connection is re-established. Therefore, the performance of MADSN is not much affected by the reliability of the network.

3. MobileAgent
Generally speaking, mobile agent is a special kind of software which can execute autonomously. Once dispatched, it can migrate from node to node performing data processing autonomously, while software can typically only execute when being called upon by other routines.

4. Agent Gateway
Agent Gateway is a way for access agent to each sensor mobile this gateway will provide rerouting of agents.

5. Data Integration
Using this module the mobile agent will bring information after agent execution from sensor device.
At each sensor site, what kind of data processing should be conducted and what integration results should be carried with the mobile agent.
Software needed :
Operating System Used : Windows NT
Technology Used :J2ME
Tool Used : Wireless Toolkit
Language Used : JAVA2.0