Characterization of Wireless Sensor Networks for Traffic & Delay

Dattatray S. Waghole Vivek S. Deshpande Department of Information Technology Department of Information Technology MIT College of Engineering MIT College of Engineering Pune, India Pune, India dattawaghole10@gmail.com vsd.deshpande@gmail.com Abstract: - The sensor network is a collection of different sensor nodes. At a moments of information transfer in the sensor network. Data packets should be transmitted via different nodes to the sink node. Wireless sensor network have a Throughput, energy, Reliability, congestion and delay are the different quality of services or parameters. For the reliable data packets transmission in the network require reliability as well as less traffic or congestion in the network. To manage E to E delay or latency in the network requires control the transfer of data packet, path and traffic in the network. For reliable communication, packets will be sending from redundant path if there exists traffic problem. If in the network given huge amount of data packet to node then at that instance created many times traffic problem or congestion. so here improve all these problems. Delay problem solve the transmission problem. In this paper analyse & characterize the traffic and delay. This paper shows the better performance of routing protocols with comparisons & which protocol take a minimum delay with better Average Packet delivery Ratio(PDR) for reliable communication in wireless sensor network.

Keywords: Delay, Wireless sensor network, Wireless, Packet delivery ratio (PDR), Routing protocols.

I. INTRODUCTION

Delay, Reliability, Energy, Throughput, Congestion are the some quality of Services in Wireless Sensor Network. In the Wireless Sensor network having minimum weighted many sensor nodes which are connected each other in network.[1] It will be used in any environment. Wireless sensor network perform various node to sink communication activity with the help of different path through link. [2] When complex condition occurs in transmission of the data from transmitter node to sink node. Sometimes congestion will be arrives in transmission due to heavy traffic, then at that instance network change the path that means it will be use redundant path for reach to sink node.[3][4] Wireless sensor network has few resources in memory, energy, and bandwidth and computation power.

Wireless sensor node is limited in consumption power, energy as well as capacities. Global ID not has in the sensor node in wireless Sensor network. Every node in sensor network consist three subsystem including sensor, communication and processing subsystem.[5]The sensor nodes enable to self allocate their routing as well as power of Transmission to increase network availability . Minimize delay is the primary goal for the wireless sensor network.[6]

Wireless sensor network having one more concept is scheduling delay i.e. time required for receive the message sink nodes from all nodes. WSN is a revolutionary technology. [7] Hard energy rate or Delay constraints change the principle of fundamental design. The communication in wireless sensor network nodes shows the packet delay in the network, that means Transmission Delay and deterministic queuing delay. [8][9][10] The trace or detection of traffic or congestion refers to identify of easy incident(event),which events creates the traffic or congestion in the sensor network.[11][14] by using various combinations of parameters various protocols identify the traffic or congestion within the sensor network. The size of buffer and information packet is very important in simulation of network. [15]

Figure1.Basic structure of WSN

Wireless sensor network

Sink Node Analyzer

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As shown in Figure 1 Wireless sensor network contain distributed sensor nodes in the network. One node near from the sink node in the wireless sensor networks i.e. one hope away from the sink node connected to the Sink node for hop by hop communication. Above figure shows the collection of different nodes in the WSNs. one node should be connected with sink node & analyser analyse the performance of the network for characterization of WSNs for different Quality of services.

II. LITERATURE SURVEY Delay and reliability in information transfer in the sensor network at a transmission node to sink node. It is important for successfully data transmission without drop and loss of data packets within transmission. Many times data transmitted in the network, it will be lost in the network at the moment of transmission of information at a transmission node to sink node. Then it will be lost the reliability, energy, power as well as time in network. In the wireless sensor network end to end delay is more important quality of service for data transmission to sink node. In the wireless sensor network many routing protocols of Quality of Services have concentrate or give value or import ants for the end –to-end delay guarantees. Junyoung Heo proposed EARQ Wireless industrial sensor network (WISN) in wireless sensor network with consideration of new requirement real time, reliable delivery and delay. It provides the actual time, credible sending of information without drop as well as lost packet while considering energy awareness. Only on the basis of neighbouring node estimate the latency, energy, and path credibility to the sink node. Most important part is to achieve the reliability, if source of packets sends then it send redundant packet via redundant path. EARQ is suitable application due to capability of energy, efficient, actual-time, credible communication. [1] In WISN information sense or capture from the node must be transfer to the sink. But the weak point is lost information may reason of denial so delayed packet may be useless. Actual time communication are agreeable in WISN, because fault toleration or tolerance, it is a major advantage of WISN. EARQ endue a easy approximate of the less latency, given the sensor node and radio range [1][4][6]. Chi-Stunk Cheng proposed in DADCNS Delay aware information or data packet structure of network for wireless sensor network is proposed. Main aim of given network structure is minimize the Delay in the collection of data packets of wireless sensor network. The most important aim is verify the characteristics of Delay aware data collection in wireless sensor network. For minimize delay in the network and for reduce traffic in the network divert the path of sending data packets from different nodes to sink node. The one good advantage in DADCNS is it control the traffic and minimizes delay from network without increasing nodes to base station [2]. Abraham O. Fapojuwo proposed in the QBCDCP controlled base station. In the route selection method the parameters supports by adding latency and parameters of bandwidth. Analytical and discrete-incident methods of

simulation evaluate the QBCDCP in the term of E to E Delay or latency & energy consumption [3].

III. RESULT ANALYSIS

Our simulation scenario includes one sink node with 30 sensor nodes. IEEE 802.11(MAC) & IEEE 802.15.4(ZigBee) MAC protocol is used .Packet size 50 bytes. Ad-hoc On Demand Protocol i.e. AODV & Dynamic Source Routing Protocol i.e. DSR is used. Reporting Rate 10bytes/s (0.1) is used for this simulation.

Figure2. Average E to E delay as a function of topology. Figure2 shows performance analysis of Average E to E Delay of AODV, DSDV & DSR protocols for Random, Grid &Chain topology. AODV gives very poor performance as compared to DSDV & DSR protocols. But DSDV protocol gives better performance as compared to other protocols. DSR protocol gives performance better than AODV but poor than DSDV protocol so it is Average protocol.

Figure3. Average PDR As a function of topology.

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Figure3. Depicts that Performance analysis of Average Packet Delivery Ratio (PDR) of AODV, DSDV & DSR protocol for Random, Grid & Chain topology. AODV protocol shows drastically better results than DSDV & DSR Protocol. But DSDV protocol gives drastically poor performance for PDR than AODV & DSR protocol’s Protocol gives Average good performance as compare to other protocols i.e. better than DSDV but slightly poor than AODV.

Figure4.Performance analysis of AODV & DSR protocol for MAC. Refer figure 4 for Performance of both AODV &DSR protocol for 802.15.4 is better than 802.11 MAC. Because average end-to-end delay for MAC 802.15.4 is drastically decrease than 802.11 MAC.

Figure5. Average end-to-end delay As a function of Node density for MAC. Figure5 conclude that when node density increases respectively then Average End-to-End Delay for AODV protocol gives better performance as compared to DSR

protocol. DSR protocol has a very poor performance when node density increases respectively.

Figure6.Average Packet Delivery Ratio functions of Node Density for MAC 802.11. Figure6. of Average PDR v/s Node Density shows that Average PDR for DSR gives drastically better performance as compare to AODV protocol when node density increase respectively. AODV protocol gives not better but Average good PDR for MAC 802.11

IV. CONCLUSION AND FUTURE WORK

The Characterization of Traffic & Delay of WSNs shows that DSDV gives minimum Average E to E delay or latency as compared to AODV & DSR protocol .DSR protocol gives better performance than 80% AODV & 20% DSDV protocol. Drawback of DSDV is it gives drastically poor performance for average PDR.Comparison between the 802.11 & 802.15.4 routing protocol. 802.15.4 Shows better performance than 30% AODV & 10% DSR for Average E to E Delay or latency as compared to 802.11. In case of Node Density, when number of node density increases serially, the Average E to E Delay performance of AODV protocol is better than DSR protocol & Average PDR of DSR protocol is better than AODV Protocol. This paper shows that Average E to E Delay of DSDV protocol & 802.15.4 are less and Average PDR of DSR Protocol is drastically increases as compare to other protocols. In future work we should be compare this results with SMAC.TMAC & other more routing Protocols. V. REFERENCES

[1] Junyoung H., Jiman H., and Yookun C., IEEE EARQ:” Energy Aware Routing for Real-Time and Reliable Communication in WISN”, IEEE Transaction Industrial Informatics, Volume.5, Num.1, FEB 2009. [2 ] C. Cheng, Member, IEEE, C. K. Tse, Fellow, IEEE, and Francis C.M.L., Senior Member, IEEE, “A Delay-Aware Data Collection Network Structure for Wireless

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