Dynamic Routing for Data Integrity

Dynamic Routing for Data Integrity and Delay Differentiated Services in Wireless Sensor Networks

ABSTRACT:

Applications running on the same Wireless Sensor Network (WSN) platform usually have different Quality of Service (QoS) requirements. Two basic requirements are low delay and high data integrity. These two requirements cannot be satisfied simultaneously. Existing system problems are being resolved using this project. In the previous projects high data integrity with low delay are not done at the same time, using this one we have overcome those issues.

Keywords: QoS, IDDR, WSN

INRODUCTION:

WSNs have two basic QoS requirements: low delay and high data integrity, leading to what are called delay sensitive applications and high-integrity applications, respectively. Generally, in a network with light load, both requirements can be readily satisfied. However, a heavily loaded network will suffer congestion, which increases the end to-end delay. This work aims to simultaneously improve the fidelity for high-integrity applications and decrease the end-to-end delay for delay-sensitive ones, even when the network is congested. We borrow the concept of potential field from the discipline of physics and design a novel potential based routing algorithm, which is called integrity and delay differentiated routing (IDDR). IDDR is able to provide the following two functions:

• Improve fidelity for high-integrity applications.
• Decrease end-to-end delay for delay-sensitive applications.

LITERATUR SURVEY

1. Most QoS provisioning protocols proposed for traditional ad hoc networks have large overhead caused by end-to-end path discovery and resource reservation. Thus, they are not suitable for resource-constrained WSNs. Some mechanisms have been designed to provide QoS services specifically for WSNs. Adaptive Forwarding Scheme (AFS) employs the packet priority to determine the forwarding behavior to control the reliability .LIEMRO utilizes a dynamic path maintenance mechanism to monitor the quality of the active paths during network operation and regulates the injected traffic rate of the paths according to the latest perceived paths quality.
2. It does not consider the effects of buffer capacity and service rate of the active nodes to estimate and adjust the traffic rate of the active paths. This will cause congestion and thus lead to many high integrity packets loss and large end-to-end delay for delay sensitive packets. Delay-sensitive packets occupy the limited bandwidth and buffers, worsening drops of high-integrity ones. High-integrity packets block the shortest paths, compelling the delay-sensitive packets to travel more hops before reaching the sink, which increases the delay. High-integrity packets occupy the buffers, which also increases the queuing delay of delay-sensitive packets.
3. This work aims to simultaneously improve the fidelity for high-integrity applications and decrease the end-to-end delay for delay-sensitive ones, even when the network is congested. We borrow the concept of potential field from the discipline of physics and design a novel potential based routing algorithm, which is called integrity and delay differentiated routing (IDDR). IDDR is able to provide the following two functions:
4. Improve fidelity for high-integrity applications. The basic idea is to find as much buffer space as possible from the idle and/or under-loaded paths to cache the excessive packets that might be dropped on the shortest path. Therefore, the first task is to find these idle and/or under loaded paths, then the second task is to cache the packets efficiently for subsequent transmission. IDDR constructs a potential field according to the depth1 and queue length information to find the under-utilized paths. The packets with high integrity requirement will be forwarded to the next hop with smaller queue length. A mechanism called Implicit Hop-by-Hop Rate Control is designed to make packet caching more efficient.
5. Decrease end-to-end delay for delay-sensitive applications. Each application is assigned a weight, which represents the degree of sensitivity to the delay. Through building local dynamic potential fields with different slopes according to the weight values carried by packets, IDDR allows the packets with larger weight to choose shorter paths. In addition, IDDR also employs the priority queue to further decrease the queuing delay of delay-sensitive packets.

EXISTING SYSTEM

Most QoS provisioning protocols proposed for traditional ad hoc networks have large overhead caused by end-to-end path discovery and resource reservation. Thus, they are not suitable for resource-constrained WSNs. Some mechanisms have been designed to provide QoS services specifically for WSNs.

• Adaptive Forwarding Scheme (AFS) employs the packet priority to determine the forwarding behavior to control the reliability.
• LIEMRO utilizes a dynamic path maintenance mechanism to monitor the quality of the active paths during network operation and regulates the injected traffic rate of the paths according to the latest perceived paths quality.

DISADVANTAGES OF EXISTING SYSTEM

• It does not consider the effects of buffer capacity and service rate of the active nodes to estimate and adjust the traffic rate of the active paths.
• This will cause congestion and thus lead to many high integrity packets loss and large end-to-end delay for delay sensitive packets.
• Delay-sensitive packets occupy the limited bandwidth and buffers, worsening drops of high-integrity ones.
• High-integrity packets block the shortest paths, compelling the delay-sensitive packets to travel more hops before reaching the sink, which increases the delay.
• High-integrity packets occupy the buffers, which also increases the queuing delay of delay-sensitive packets.

PROPOSED SYSTEM

• This work aims to simultaneously improve the fidelity for high-integrity applications and decrease the end-to-end delay for delay-sensitive ones, even when the network is congested. We borrow the concept of potential field from the discipline of physics and design a novel potential based routing algorithm, which is called integrity and delay differentiated routing (IDDR). IDDR is able to provide the following two functions:
• Improve fidelity for high-integrity applications. The basic idea is to find as much buffer space as possible from the idle and/or under-loaded paths to cache the excessive packets that might be dropped on the shortest path. Therefore, the first task is to find these idle and/or under loaded paths, then the second task is to cache the packets efficiently for subsequent transmission. IDDR constructs a potential field according to the depth1 and queue length information to find the under-utilized paths. The packets with high integrity requirement will be forwarded to the next hop with smaller queue length. A mechanism called Implicit Hop-by-Hop Rate Control is designed to make packet caching more efficient.
• Decrease end-to-end delay for delay-sensitive applications. Each application is assigned a weight, which represents the degree of sensitivity to the delay. Through building local dynamic potential fields with different slopes according to the weight values carried by packets, IDDR allows the packets with larger weight to choose shorter paths. In addition, IDDR also employs the priority queue to further decrease the queuing delay of delay-sensitive packets.

ADVANTAGES OF PROPOSED SYSTEM

IDDR inherently avoids the conflict between high integrity and low delay: the high-integrity packets are cached on the under loaded paths along which packets will suffer a large end-to-end delay because of more hops, and the delay-sensitive packets travel along shorter paths to approach the sink as soon as possible.

Using the Lyapunov drift theory, we prove that IDDR is stable.

Furthermore, the results of a series of simulations conducted on the TOSSIM platform demonstrate the efficiency and feasibility of the IDDR scheme.

IMPLEMENTATION

Service provider

In this module, the service provider will browse the data file, initialize the router nodes and then send to the particular receivers. Service provider will send their data file to router and router will select smallest distance path and send to particular receiver.

Router

The Router manages a multiple networks to provide data storage service. In network n-number of nodes are present (n1, n2, n3, n4, n5…). In a router service provider can view node details and attacked nodes. Service provider will send their data file to router and router will select smallest distance path and send to particular receiver. If any attacker is found in a node then router will connect to another node and send to particular user.

IDS Manager

In this module, the IDS Controller consists of two phases. If Integrity or Malicious Data is occurs in router then IDS controller is activated. In a first phase DNS packets, Net flow, Traffic filter and Fine-grained IDS client detection are present. Aim is that detecting all hosts within the monitored network that engage in IDS communications. We analyze raw traffic collected at the edge of the monitored network and apply a pre-filtering step to discard network flows that are unlikely to be generated by IDS applications. We then analyze the remaining traffic and extract a number of statistical features to identify flows generated by IDS clients. In the second phase, Coarse-grained IDS Integrity or Malicious Data detection, Fine-grained IDS client detection and Integrity or Malicious Data are present; our system analyzes the traffic generated by the IDS clients and classifies them into either legitimate IDS clients or IDS Integrity or Malicious Data.

Receiver (End User)

In this module, the receiver can receive the data file from the router. Service provider will send data file to router and router will send to particular receiver. The receivers receive the file by without changing the File Contents. Users may receive particular data files within the network only.

Attacker

Attacker is one who is injecting malicious data to the corresponding node and also attacker will change the bandwidth of the particular node. The attacker can inject fake bandwidth to the particular node. After attacking the nodes, bandwidth will changed in a router.

CONCLUSION

In this paper, a dynamic multipath routing algorithm IDDR is proposed based on the concept of potential in physics to satisfy the two different QoS requirements, high data fidelity and low end-to-end delay, over the same WSN simultaneously. The IDDR algorithm is proved stable using the Lyapunov drift theory. Moreover, the experiment results on a small test bed and the simulation results on TOSSIM demonstrate that IDDR can significantly improve the throughput of the high-integrity applications and decrease the end-to-end delay of delay sensitive applications through scattering different packets from different applications spatially and temporally. IDDR can also provide good scalability because only local information is required, which simplifies the implementation. In addition, IDDR has acceptable communication overhead.

REFERENCES

1. P. Levis, N. Lee, M. Welsh, and D. Culler, “TOSSIM: Accurate and scalable simulation of entire TinyOS applications,” in Proc. 1st Int. Conf. Embedded Networked Sensor Syst., 2003, pp. 126–137.
2. T. Chen, J. Tsai, and M. Gerla, “QoS routing performance in multihop multimedia wireless networks,” in Proc. IEEE Int. Conf. Universal Personal Commun., 1997, pp. 557–561.
3. R. Sivakumar, P. Sinha, and V. Bharghavan, “CEDAR: Core extraction distributed ad hoc routing algorithm,” IEEE J. Selected Areas Commun., vol. 17, no. 8, pp. 1454–1465, Aug. 1999.
4. S. Chen and K. Nahrstedt, “Distributed quality-of-service routing in ad hoc networks,” IEEE J. Selected Areas Commun., vol. 17, no. 8, pp. 1488–1505, Aug. 1999.
5. B. Hughes and V. Cahill, “Achieving real-time guarantees in mobile ad hoc wireless networks,” in Proc. IEEE Real-Time Syst. Symp., 2003.

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