It is difficult to search for a node with known property when we are designing the distributed applications. Searching path in routing, determining resource in the service-oriented architectures (SOAs) and searching files in peer-to-peer (P2P) applications can all be cast as a search problem. To solve this search problem we suggested Random walk-based search algorithms in the dynamic systems such as mobile wireless networks. We can measure the effectiveness and the cost of a random walk-based search algorithm with the help of the excepted number of transmissions required before hitting the target. So, our main goal is to have a low hitting time.
The advantages of Random walk search are:
- higher adaptiveness to termination conditions
- has very good control over the search space
- Handles failures or voluntary disconnections of nodes efficiently.
In the context of routing protocols for MANET, examples of concrete exploitations of random walks in wireless networks are found.
In this project we will study about the effect of biasing random walk toward the target on the hitting time. A simple upper bound, which connects the hitting time to the bias level, is obtained for the walk running over a network with uniform node distribution. The result of this project is, the hitting time can be significantly reduced even by a modest bias level. A search protocol for mobile wireless networks is proposed in this project and results of this protocol are interpreted in the light of the theoretical study. We developed this project for unstructured wireless mobile networks.
- Data forwarding module
- Biased Rand-walk module
- Networking Module
- Link failure module
– are the main modules of this project.
Front End: Asp .Net 2.0.
Back End: SQL Server
Operating system: Windows XP Professional
Coding Language used: Visual C# .Net
Processor: Pentium IV 2.4 GHz or more
Hard Disk: minimum 40 GB HDD
RAM: 256 Mb RAM
Floppy Drive: 1.44 Mb or more
Monitor: 14” size VGA Color monitor
Mouse: 3 Button scroll/ wireless mouse
Keyboard: Minimum 108 keys