Node Isolation Model In Unstructure P2p Networks Computer Science Essay

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ABSTRACT- This paper derived a general model of resilience for unstructured P2P networks under heavy-tailed user lifetimes and formally analyzed two age-dependent neighbor-selection techniques. Our results show that the proposed random-walk method may achieve any desired level of resilience without replacing neighbors as long as Pareto shape parameter 1 < α ≤ 2 and system size n and age T are sufficiently large. This indicates that P2P systems under proposed neighbor selection and very heavy-tailed lifetimes (i.e., α < 2) become progressively more resilient over time and asymptotically tend to an "ideal" system that never disconnects as users join the network. Future work includes derivation of residual lifetime distributions in finite systems under age-proportional neighbor selection and analysis of the limiting distribution of neighbor residual lifetimes under max-age selection as the number of sampled user's m→ ∞.

INTRODUCTION

RESILIENCE of P2P networks under random user arrival and departure (i.e., churn) has recently become an active research area[1]-[2], [3], [4]. One of the primary metrics of resilience is graph disconnection during which a P2P network partitions into several nontrivial sub graphs and starts to offer limited service to its users. However, as shown in [5], most partitioning events in well-connected P2P networks are single-node Isolations, which occur when the immediate neighbors of a node fail before is able to detect their departure and then replace them with other alive users. For such networks, node isolation

analysis has become the primary method for quantifying network resilience in the presence of user churn.

Traditional analysis of node isolation[8], [5] focuses on the effect of average neighbor- replacement delay, average user lifetime, and fixed out-degree on the resilience of the system. These results show that probability with which each arriving user is isolated from the system during its lifetime is proportional to, where. While this result is asymptotically exact under exponential user lifetimes and uniform neighbor selection, it remains to be investigated whether stronger results can be obtained for heavy-tailed lifetimes observed in real P2P networks [6], [7] and/or no uniform neighbor selection. We study these questions below.

2 EXISTING SYSTEM

In existing system, unstructured p2p network consider only exponential (mean time to failure) user lifetime and age-independent neighbor replacement. Unstructured P2P networks are single-node isolations, which occur when the immediate neighbors of a node fail before a node is able to detect their departure and then replace them with other alive users. Node isolated from network. So, communication problem occurs. Neighbor node unable to detect the failure previously.

We first build a generic isolation model that allows computation of with arbitrary accuracy for any completely monotone density function of residual lifetimes . This result is achieved by replacing the distribution of with a hyper-exponential distribution, which can be performed with any accuracy, and then solving the resulting Markov chain for the probability of absorption into the isolation state before the user decides to leave the system. While this model only admits a numerical solution through matrix manipulation, it allows very accurate computation of for very heavy-tailed cases when the exponential upper bound [18] is rather loose. The model is also necessary for studying isolation behavior of the various neighbor-selection strategies examined in later parts of the paper where simulations are impractical or impossible due to the small values of. The second part of this paper verifies the model of under uniform neighbor replacement and analyzes its performance for very heavy-tailed lifetimes (i.e.,). We show that, as the age of the system becomes infinite and shape parameter of Pareto user lifetime distribution approaches 1, the isolation probability decays to zero proportionally to , which holds for any number of neighbors and any search delay , implying that such systems may achieve arbitrary resilience without replacing any neighbors. In practice, however, is a fixed number bounded away from 1 (common studies suggest that is between 1.06 [6] and 1.09 [7]) and is finite, which cannot guarantee high levels of robustness without neighbor replacement.

PROPOSED SYSTEM

In proposed system, we consider heavy-tailed user lifetime for improving residual lifetime of chosen users and reducing probability of user isolation and graph partitioning from network. A joining node randomly selects alive users from the system and chooses the user with the maximal age. Random walk algorithms have been used to build unstructured P2P systems and replace failed links with new ones.

To obtain model , we approximate the tail of in (9) with its hyper-exponential equivalent in (10) and then compute by

applying Theorem 2 as in Section II-D. Fig. shows predicted by the model compared with simulations for Pareto lifetimes with exponential search delays, and two values of the derived result is very accurate and indeed shows inversely proportional dependency between the number of sampled users and . The impudence of on isolation probability for Pareto lifetimes is presented more clearly.

In systems that do not replace neighbors and, the limiting isolation probability in (11) is reduced along the corresponding curve in Fig. , i.e., proportionally to. Thus, for any finite , (11) does not qualitatively change its decay rate toward zero as a function of and leads to no novel discussion.

MODULES

4.1. Node information & Topology construction

In this module node information is for initializing the number of nodes, giving names to those nodes, initializing the port numbers for a particular node and provision of host name. In node information, node name and port number must be unique for each node. Host name must be given to run nodes in multiple systems. For topology construction we provide the links for the initialized nodes. We also provide cost to the various links. We check there is no multiple links for same set of nodes. Cost specification is given to all nodes. Each node in network has capable of sending and receiving information through their unique port number. Based on node information and topology construction, each node can calculate the available path and best path for message transmission.

4. 2. Node Isolation

A node which does not have any connection with any other in a network then that node is said to be isolate from network. In unstructured topology, nodes can randomly arrive and departure. When a node get departure, other nodes link gets disconnected. Network resilience is graph disconnection during which a P2P network partitions into several nontrivial sub graphs and starts to offer limited service to its users. Due to graph disconnection, isolated node cannot be able to communicate to other nodes in a network. Isolated node cannot make any communication with any other node in network. Message transmission is impossible with isolated node. When number of nodes gets isolated is high, and then end-end communication is poor.

4. 3. Random walk Algorithm

A new-neighbor selection strategy that is based on random walks over weighted directed graphs. In this module, node age is calculated by sum of weight of in degrees of each node and age is provided to each node.

Age=Σ Wi

When nodes get isolated, it selects the maximum node age and starts its offer to its users. Each login node also chooses maximum node age and joins in network for providing its services to increase its residual lifetime. Random walk on age-proportional graphs demonstrates that, for lifetimes with infinite variance, the system monotonically increases its resilience as its age and size grow. Using Random walk algorithm, P2P networks are single-node isolations, can be identified by immediate neighbors of a node to detect their departure and then replace them with other alive users.

4. 4. Message Transmission

In this module, message gets transmitted between the nodes .when node is isolated it selects random walk algorithm and chooses its neighbor and reconstruct the topology and message is transmitted in alternate path. The source node chooses the destination and passes the message using the method of random walk algorithm to avoid graph disconnection for sending its message in the best path available. Once the client completes its message and sends the message, the client gets the knowledge about the available paths and it also gets the information about the best path and the details regarding the particular path. When the destination system is isolated, it can receive message as isolated node. Then source can use random walk algorithm and resend the message using alternate path. Once the message reached the destination, source can receive the acknowledgement message from the destination.

5 CONCLUSION

This paper derived a general model of resilience for unstructured P2P networks under heavy-tailed user lifetimes and formally analyzed two age-dependent neighbor-selection techniques. Our results show that the proposed random-walk method may achieve any desired level of resilience without replacing neighbors as long as Pareto shape parameter and system size and age are sufficiently large. This indicates that P2P systems under proposed neighbor selection and very heavy-tailed lifetimes (i.e.,) become progressively more resilient over time and asymptotically tend to an "ideal" system that never disconnects as users join the network. Future work includes derivation of residual lifetime distributions in finite systems under age-proportional neighbor selection and analysis of the limiting distribution of neighbor residual lifetimes under max-age selection as the number of sampled users.