Iaetsd quick detection technique to reduce congestion in

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Quick Detection Technique to Reduce Congestion in WSN M.Manipriya1, B.Arputhamary2, 1

M.Phil scholar, Department of computer science, Bishop Heber college(Autonomous), Trichirapalli-620 017 2 Asst.professor, Department of computer Applications, Bishop Heber college(Autonomous), Trichirapalli-620017 priyayehova@gmail.com arputhambaskaran@rediffmail.com

information via one to another node. Nodes are having limited storage space in terms of bandwidth, space, battery level, multi hop communication architecture in sensor networks since nodes send their data to a sink node for transmitting the packets. Sensor has been classified into two classes such as event driven and continuous dissemination.

According to the history of communication, sensor nodes are constrained in battery level and bandwidth. Current researches being focused on sensor networks to maximize the network life time.

The node delay and throughput are common issues in sensor networks, transmission of data require end-end delay must be acceptable range to the users, as delay decreases users meet Quality of Service (QoS) of the network. During this transmission tasks some nodes have low energy to transmit or some nodes are being inactive to send the packets, so that node can be waste the resources and also enhanced the congestion between the nodes which causes high delay and chance to get packet loss. In order to avoid this issue our proposed technique solves the congestion control, minimum delay by detecting inactive nodes during the transmission.

Abstract - Wireless Sensor Networks (WSNs) are employed for either continuous monitoring or event detection in the target area of interest. In event-driven applications, it is critical to report the detected events in the area and with sudden bursts of traffic possible due to spatially-correlated events or multiple events, the data loss due to congestion will result in information loss or delayed arrival of the sensed information. Congestion control techniques detect congestion and attempt to recover from packet losses due to congestion, but they cannot eliminate or prevent the occurrence of congestion.

Congestion avoidance techniques employ proactive measures to alleviate future congestion using parameters like queue length, hop count, channel conditions, and priority index. However, maintaining and processing such information becomes a significant overhead for the sensor nodes and degrades the performance of the network. This paper propose a congestion avoidance quick detection technique (QDT) that uses the queue buffer length of the sensor nodes to estimate the congestion and diffuse traffic to provide a congestionfree routing path towards the base station. This protocol provides event reporting, packet delivery ratio, by dynamically diffusing the traffic in the network using multiple forwarders in addition to backup forwarding.

Results show that our protocol significantly improves event reporting in terms of packet delivery ratio by avoiding congestion while diffusing the traffic effectively.

1.1 Congestion in WSN

Keywords: Wireless sensor network, node detection algorithm, reducing congestion.

Congestion is prejudicial to wireless device networks as a result of it lowers the out turn of the network by dropping a lot of packets containing crucial perceived info and reduces the time period of the network as a result of weakened energy efficiency at every device node, particularly for spatially-correlated events. With the buer of the device nodes close to full, there will invariably be traďŹƒc at the node for the information packets, w hich ends in exaggerated rivalry, exaggerated retran smissions weakened packet delivery magnitude rela tions, wireless device networks as a result of it lowers the outturn of the network by dropping a lot

I. INTRODUCTION Wireless sensor network is an emerging technology in research field; it is used to monitor health condition, temperature also used in military application, home applications, etc. Wireless sensors are also used in forest fire detection, inventory control, energy management, and so on.

There are thousands of nodes are being interconnected with one another the control station collects all data from each node and transmits the

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of packets containing crucial perceived info and reduces the time period of the network as a result of weakened energy efficiency at every device node, and exaggerated energy consumption. In event-driven applications, once there's an abrupt increase within the traffic, congestion would degrade the performance of the network by the loss of the event packets or the delayed arrival of the packets to the sink. Congestion control is not solely necessary to enhance the general outturn however additionally to elongate the network time period and improve the end-to-end outturn, referred to as accuracy level, by avoiding the packet loss as a result of congestion. Congestion being one among the largest problems for a device network, needs to be avoided to enhance the Quality of Service (QoS) in terms of outturn, packet delivery ratio, latency, and energy efficiency. Congestion management in WSN has been wide concerning police investigation the congestion within the network and dominant the congestion by adjusting the speed of the input traffic or prioritization of the info packets or load equalization among the device nodes. The traffic within the network is adjusted either hop-by-hop, at every device node, end to end rate adjustment at the supply nodes wherever the traffic is generated. While congestion management concentrates on sanctioning the network to live through packet loss due to the prevalence of congestion. Congestion rejection detects early cong estion or estimates for the congestion within the network and tries to forestall its prevalence. For example, in associate event-based approach, appropriate congestion rejection mechanism might help to sight the approaching congestion and react to matters before the particular collapse takes place. Congestion rejection is that the core thought for this paper model to proactively determine and alleviate congestion within the network and change the network to handle the longer term traffic.

Fetch Quickly. Akoijam Premita [4] et al. discussed on power efficient energy aware routing protocol for wireless sensor networks which occupied less energy and reduced the end to end delay.

Jayachandran [5] et al. explained fast data collection with reduced interference and increased life time they improved packet delivery ratio and saved the energy of the each node. Abhay Raman [6] et al. minimized the delay and maximized the life time of the network by reducing the delay from source to destination. Hao-Li Wang [7] et al. enhanced the scheme for quality of service was used to detect the inactive node bandwidth and energy. Navneet Kaur [8] elaborated load balancing technique in sensor network to distribute the packets it reduces packet loss. M. Vijayalakshmi et al., [9] proposed Clustering and Prediction techniques, which use temporal correlation among the sensor data, provide a chance for reducing the energy consumption of continuous sensor data collection. Thus it can achieve stability and prolongs network lifetime. G.Srinivasan et al., [10] analyzed in WSN congestion detection and congestion control is the major research areas. It is important to design protocols for controlling congestion.

Parveen Yadav et al.,[11] proposed new cluster based security architecture which starts from the initialization of the network. Safe path is not shortest but next alternative shortest path in mobile ad hoc network. R.Sumathi et al., [12] surveyed QoS Based Routing Protocols for Wireless Sensor Networks. Many QoS issues are focused in their work. The performance comparison of QoS based routing protocols such as SAR, MMSPEED, MCMP, MCBR, and EQSR has also been analyzed.

III. PROPOSED WORK Inactive node Inactive nodes are trying to get many benefits from the network to occupy battery or bandwidth.

An inactive node might not send the data Packets in a proper way. An inactive node can do any of the possible attack in the sensor network.

II. RELATED WORK Chieh-Yih Wan [1] et al. proposed a technique Congestion detection and avoidance in sensor networks significantly improves the performance of data dissemination applications such as directed diffusion by mitigating hotspots, and reducing the energy tax with low fidelity penalty on sensing applications. Sivapuja Srikanth Babu [2] et al. investigated that jamming avoidance for video traffic in wireless sensor networks they reduced packet drops at intermediate node. Further the cost of retransmission of dropped packets was significa ntly reduced. Pooja sharma [3] et al. tried to prolong the lifetime of wireless sensor network by congestion avoidance techniques. The techniques included congestion detection and avoidance, Event-to-Sink Reliable Transport, Pump Slowly,



It turns off the power when it does not have the communication with other nodes  It may not forward the packets to the exact destination node from source node  Inactive nodes are sending some packets and drop other packets.

Techniques to properly cope with inactive replication allocation approach perform traditional cooperative technique in terms of accessibility, cost and minimum delay.

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IV. NUMERICAL EXAMPLE

Process Send Request

The network is loaded such traffic converges towards the bottom station from different directions.

Traffic from these sources are sent at different rates. Table 1 show with backup forwarder and while not backup forwarder. Once backup forwarding utilized, additional packets are received in very shorter length than while exploitation backup. Though the packets get diffused through backup forwarders, the delay is less; as a result of the time taken for the packets to achieve the bottom station through backup forwarder is a smaller amount than the wait time for the potential forwarders once their queues are full.

Table 1: Backup forwarder

Checks for the available route

Is route available?

Yes

No

Forward Message

Save message in buffer & initiate route request

Without Backup

Stop

Figure 1: Flowchart of QDT function When data transmitted, it does not forward the reply request on the reverse route. The proposed algorithm will detect and solve the problem of inactive node over wireless sensor network we develop a quick detection algorithm that considers partial greediness and new replication allocation.

With Backup

No. Of Packets Sent

No. Of Packets Received

Delay (Secs)

No. Of Packets Received

Delay (Secs)

1500 2250 4500

1015 1555 2791

0.16 0.18 0.20

1302 1872 3171

0.14 0.15 0.12

The traffic diffusion approach to proactively avoiding congestion at the nodes makes our protocol deliver a lot of packets even with a high traffic hundreds.

In our proposed method, though every supply transmits a 100Kbps towards the bottom station, the speed controller at every node adjusts the packet loss rate at every hop level and reduces the particular packets generated.

Step 1: Initiate the process to send the packets Step 2: Identified the number of nodes and establish connection with each node Step 3: Checks for the available route in the path Step 4: If the route is available forward message to the other node { Select the path which is congestion free } Else if (Save message in buffer & initiate route request) { Select the alternative path } Else (select the other paths which is available) Step 5: If active node becomes as inactive node find the inactive node and correct the node error and retransmits the packet again from buffer itself Step 6: Repeat the step until selects the path Step 7: Stop to search

40000 30000 CTR

20000

QDA

10000 0

0

1

2

3

4

5

Figure 2: No. of packets delivered V. CONCLUSION This paper introduced quick detection algorithm aims to reduce the congestion level and minimum delay to enhance the network performance. This has been achieved by finding out inactive node which is present during the transmission. If there is any error occurred with inactive node it find and modify the error and send the data to next node from current node itself. Thus

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Journal of Mobile and Wireless Communications, Volume 4, 2013, pp. 174-181.

proposed algorithm can maintain with minimized congestion level among nodes in a sensor network and prolong the network life time and reduce the service disturbance. In wireless sensor network many algorithms have been used which have lot of advantages over other algorithms. Since quick detection algorithm add more nodes of other algorithm. By this method we can improve the QoS of WSN and reduce the congestion of the information and increase the range of sensor nodes.

[10] G.Srinivasan and S.Murugappan, “A survey of congestion control techniques in wireless Sensor networks”, International Journal of Information Technology and Knowledge Management, Volume 4, No.2, 2011, pp. 413-415.

[11] Parveen Yadav and Harish Saini, “An Alternative Path Routing Scheme for Intrusion Prevention in Wireless Network”, International Journal of Engineering and Innovative Technology, Volume 2, Issue 1, 2012, pp.

248-251.

REFERENCES [1] Chieh-Yih Wan, Shane B. Eisenman, Andrew T. Campbell, “Congestion Detection and Avoidance in Sensor Networks”, Proceedings of SenSys’03, pp. 266-279, 2003.

[12] R.Sumathi and M.G.Srinivas, “A Survey of QoS Based Routing Protocols for Wireless Sensor Networks”, J Inf Process Syst, Vol.8, No.4, 2012, pp. 589-602.

[13] C. Basaran, K. Kang, and M. H. Suzer. Hop-by-hop congestion control and load balancing in wireless sensor networks, IEEE Conference on Local Computer Networks, 2010.

[2] Sivapuja Srikanth Babu, R. Konda Reddy, P. Eswaraiah, Supriya Sivapuja, Srikar Babu S.V, “Jamming Avoidance for Video Traffic in Wireless Sensor Networks, International Journal of Emerging Trends & Technology in Computer Science, volume 2 , Issue 2, pp. 293-297, 2013.

[14] M. M. Bhuiyan, I. Gondal, and J. Kamruzzaman.

CAM: Congestion avoidance and mitigation in wireless sensor networks, IEEE Vehicular Technology Conference, 2010.

[3] Pooja sharma, Deepak tyagi, Pawan bhadana, “A Study on Prolong the Lifetime of Wireless Sensor Network by Congestion Avoidance Techniques”, International Journal of Engineering and Technology, Volume 2, Issue 9, pp. 4844-4849, 2010.

[15] J. B. Helonde, V.Wadhai, V. Deshpande, and S. Sutar,”EDCAM: Early detection congestion avoidance mechanism for wireless sensor network”, International Journal of Computer Applications, 2010.

[4] Akoijam Premita, Mamta Katiyar, “A Review on Power Efficient Energy- Aware Routing Protocol for Wireless Sensor Networks”, International Journal of Engineering Research & Technology, Volume 1, Issue 4, pp. 1-8, 2012.

[16] K. K. Sharma, H. Singh, and R. B. Patel, “A reliable and energy efficient transport protocol for wireless sensor network”, Global Journal of Computer Science and Technology, 2010.

[5] Jayachandran. J, Ramalakshmi. R, “Fast Data Collection with Reduced Interference and Increased Life Time in Wireless Sensor Networks”, International Journal of Research in Engineering & Advanced Technology, Volume 1, Issue 2, pp. 1-5, 2013.

[17] P. Sharma, D. Tyagi, and P. Bhadana, “A study on prolong the lifetime of wireless sensor network by congestion avoidance techniques”, International Journal of Engineering and Technology, 2010.

[6] Abhay Raman, Ankit Kr. Singh, Abhishek Rai, “Minimizing Delay And Maximizing Lifetime For Wireless Sensor Networks With Anycast”, International Journal of Communication and Computer Technologies, Volume 1, No 26, Issue 4, pp. 96-99, 2013.

[7] Hao-Li Wang, Rong-Guei Tsai, Long-Sheng Li, “An Enhanced Scheme in Controlling Both Coverage and Quality of Service in Wireless Sensor Networks”, International Journal on Smart Sensing and Intelligent Systems, Volume 6, No 2, pp. 772-790, 2013.

[8] Navneet Kaur, “Review on Load Balancing in Wireless Sensor Network”, International Journal of Advanced Research in Computer Science and Software Engineering , Volume 3, Issue 5, pp. 1044-1047, 2013.

[9] M. Vijayalakshmi, V. Vanitha, “Cluster based adaptive prediction scheme for energy efficiency in wireless sensor networks”, International Research

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