Clustering and Cluster-Based Routing Protocol for Delay-Tolerant Mobile Networks

   1.ABSTRACT :

          This reveals distributed clustering scheme and proposes a cluster-based routing protocol for Delay- Tolerant Mobile Networks (DTMNs). The basic idea is to distributively group mobile nodes with similar mobility pattern into a cluster, which can then interchangeably share their resources (such as buffer space) for overhead reduction and load balancing,aiming to achieve efficient and scalable routing in DTMN. Due to the lack of continuous communications among mobile nodes and possible errors in the estimation of nodal contact probability, convergence and stability become major challenges in distributed clustering in DTMN. To this end, an exponentially weighted moving average (EWMA) scheme is employed for on-line updating nodal contact probability, with its mean proven to converge to the true contact probability. Based on nodal contact probabilities, a set of functions including Sync(), Leave(), and Join() are devised for cluster formation and gateway selection. Finally, the gateway nodes exchange network information and perform routing. Extensive simulations are carried out to evaluate the effectiveness and efficiency of the proposed cluster-based routing protocol. The simulation results show that it achieves higher delivery ratio and significantly lower overhead and end-to-end delay compared with its non-clustering counterpart.

   2. EXISTING SYSTEM :

 

                  For intermittent connectivity among mobile nodes, especially under low nodal density and/or short radio transmission range, the Delay-Tolerant Network (DTN) technology  has been introduced to mobile wireless communications, such as ZebraNet , Shared Wireless Info-Station (SWIM) , Delay/Fault-Tolerant Mobile Sensor Network (DFT-MSN) , and mobile Internet and peer-to-peer mobile ad hoc networks –. DTN is fundamentally an opportunistic communication system, where communication links only exist temporarily, rendering it impossible to establish end-to-end connections for data delivery. In such networks, routing is largely based on nodal contact probabilities (or more sophisticated parameters based on nodal contact probabilities). 

                  Due to the lack of continuous communications among mobile nodes and possible errors in the estimation of nodal contact probability,convergence and stability become major challenges in distributed

clustering in DTMN.

  3.PROPOSED SYSTEM :

                                    To introduce clustering and cluster-based routing

in DTMN is the main criteria in this project. The basic idea is to let each mobile node to learn unknown and possibly random mobility parameters and join together with other mobile nodes that have similar mobility pattern into a cluster.

An exponentially weighted moving average (EWMA) scheme is employed for on-line updating nodal contact probability, with its mean proven to converge to the true contact probability. Based on nodal contact probabilities, a set of functions including Sync(), Leave(), and Join() are devised for cluster formation and gateway selection. Finally, the gateway nodes exchange network information and perform routing. Clustering has long been considered as an

effective approach to reduce network overhead and improve scalability. Various clustering algorithms have been investigated in the context of mobile ad hoc networks. We  proposes a DTN hierarchical routing (DHR) protocol to improve routing scalability. DHR is based on a deterministic mobility model, where all nodes move according to strict, repetitive patterns, which are known by the routing and clustering algorithms. We investigate distributed clustering and

cluster-based routing protocols for Delay-Tolerant Mobile Networks (DTMNs). The basic idea is to autonomously learn unknown and possibly random mobility parameters and to group mobile nodes with similar mobility pattern into the same cluster.

     We introduce our proposed clustering algorithm for DTMN,which undergoes the following steps. First, each node learns direct contact probabilities to other nodes. It is not necessary that a node stores contact information of all other nodes in network. Second, a node decides to join or leave a cluster based on its contact probabilities to other members of that cluster. Since our objective is to group all nodes with high pair-wise contact probabilities together, a node joins a cluster only if its pair-wise contact probabilities to all existing members are greater than a threshold γ . A node leaves the current cluster if its contact probabilities to some cluster members drop below ү. Load balancing is an effective enhancement to the proposed routing protocol. The basic idea is to share traffic load among cluster members in order to reduce the dropping probability due to queue overflow at some nodes. Sharing traffic inside a cluster is reasonable, because nodes in the same cluster have similar mobility pattern, and thus similar ability to deliver data messages.

  4.HARDWARE REQUIREMENTS:

•         System                : Pentium IV 2.4 GHz.

•         Hard Disk            : 40 GB.

•         Floppy Drive       : 1.44 MB.

•         Monitor                : 15 VGA Colour.

•         Mouse                 : Logitech.

•         Ram                     : 256 MB.

   5.SOFTWARE REQUIREMENTS:

•         Operating System       : - Windows XP Professional.

•         Front End                               : - Asp .Net 2.0.

•         Coding Language       : - Visual C# .Net.