On improvement of performance for transport protocol using sectoring sche

Uploaded on


More in: Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads


Total Views
On Slideshare
From Embeds
Number of Embeds



Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

    No notes for slide


  • 1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 275 ON IMPROVEMENT OF PERFORMANCE FOR TRANSPORT PROTOCOL USING SECTORING SCHEME IN WSN Wategaonkar D.N., Deshpande V.S. (Senior IEEE Member) Department of Information Technology, MITCOE, Pune, India, Department of Information Technology, MITCOE, Kothrud, Pune, India, ABSTRACT A wireless sensor network (WSN) consists of spatially disseminated self-governing sensors to examine physical or ecological situation. In WSN the delivery of all sending packet is important. In transport layer reliable message delivery and congestion control are significant factors. The aptitude of the network is to ensure reliable data transmission in a state of continuous change of network structure. This paper focuses on sectoring scheme which incorporates the logical sectors in existing WSN. Finally the proposed scheme is compare for its performance against QoS parameters. Keywords: Wireless Sensor Networks, Transport Layer Protocols, Reliability, Clustering, Sectoring. I. INTRODUCTION 1.1 Wireless Sensor Networks It consists of sensor nodes disseminated in small or large environmental areas. These self-sufficient Sensors used to monitor physical or environmental conditions, such as Motion, Pressure, Sound, Temperature or pollutants and to cooperatively pass their data through the network to a destination location. The more modern networks are bi-directional, enabling also to control the activity of the sensors. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and consumer application, such as industrial process monitoring and control, machine health monitoring, so on. The WSN is built of "Sensor nodes" – from a few to several hundreds or even thousands, where each node is connected to one (or sometimes several) sensor nodes [1]. Each such sensor network node has typically several parts: a radio transceiver with an external or internal antenna, a microcontroller, an electronic circuit for interfacing with the sensors and an energy source, usually a Battery. A sensor node might vary in size from that of a shoebox down to the size of a grain of dust, although functioning "motes" of genuine microscopic dimensions have yet to be created. The cost of sensor nodes is similarly variable, ranging from hundreds of dollars to a few pennies, depending on the complexity of INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), pp. 275-281 © IAEME: www.iaeme.com/ijcet.asp Journal Impact Factor (2013): 6.1302 (Calculated by GISI) www.jifactor.com IJCET © I A E M E
  • 2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 276 the individual sensor nodes. Size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and communications bandwidth. WSNs have several distinctive features like Sensor nodes have limited resources, Low computational capability, Small memory, Low wireless communication bandwidth and a limited, usually no rechargeable battery [2]. 1.2 Significance of Reliability The necessitate for reliability in a sensor network is resolutely deprived upon the particular application the sensor network is used for. Consider a sensor network deployed to sense the incidence of destructive gases in an engaged building, with the sink having the aptitude of mattering queries demonstrating what specific gas the sensors should attempt to detect [3]. Given the nature of the application, it is totally serious that a query update reaches the sensors in a reliable manner. Fig.1 Structure of WSN However, any sensor network that is deployed to cater to a critical application will require mechanisms to ensure reliable delivery of information from the sink to the sensors. Besides delivery of queries, reliability will also be required when control software is downloaded to upgrade the sensors. By using upstream and downstream message is carried out in wireless sensor network .For upstream communication, the sender is a sensor node and receiver is a sink node and in reverse order, downstream is work [4]. Figure-1 shows the basic scenario of wireless sensor network, with some sensor node and sink node. When event is occurs i.e. target node send their packets to sink node with some route. II. RELATED WORK 2.1 Clustering - Clustering is an excellent method which can be used for topology generation. The advantages of clustering are transmit aggregated data to the data sink to reducing number of nodes taking part in transmission, Useful energy consumption, Scalability for large number of nodes, Reduces communication overhead for both single and multi hop [5]. Clustering is a technique that can be used to organize sensors in a wireless sensor network. In clustering, nodes can be partitioned into a number of small groups called clusters. Each cluster has a coordinator, known as a cluster head, and a number of member nodes [6]. These member nodes communicate only to their cluster heads to transmit observed readings.
  • 3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 277 Fig.2 Clustering scheme used in WSN Figure 2 shows clustering scheme used in WSN. Nodes are divided in different clusters. In each cluster there is one cluster head that collects the packets from the nodes of that cluster. 2.2 Hadi Jamali Rad [16] insisted Diversity techniques have been proposed to provide a wireless network with reliable and power efficient communications [1, 2]. However, tiny sensor nodes cannot accommodate multiple antennas and hence the implementation of MIMO-based communications in a wireless sensor network (WSN) requires cooperation among sensor nodes. These sensor nodes can be considered as a virtual MIMO (V-MIMO) unit. Moreover, in large WSNs, multihop communications are used instead of long-haul transmission to reduce high energy consumption due to exponentially increase in path-loss with the distance between source and sink of information. In multihop networks, there are several sections (also can be called clusters) between the source and the sink nodes. Thus, the multihop sections closer to the sink should not only transmit their own information but also relay the information of other sections. So, the closer the section to the sink is, the higher energy it consumes and hence the sooner it dies [5]. Therefore, minimizing the total energy consumption of these multihop networks results in dying of closer sections to the sink, which itself reduces the lifetime of the network. This motivated us to mathematically derive the optimum sectoring (section sizes) of a multihop cooperative WSN to maximize its lifetime. In a typical multihop cooperative WSN, the network will be triggered by an event whose information should be collected by a local V-MIMO unit and then be transmitted by that unit to a sink. If the sink is far from the event, the information should be forwarded to the sink by a multihop-based routing manner. 2.3 Abin John Joseph [17] proposed Hexagonal Sectored Shortest Path Routing Algorithm (HSSPRA) which allows clusters to be formed with nodes from different sectors so that every non CH node can join the nearest CH irrespective of which sector they belong to. The BS is located away from the network. All the nodes in the network are homogenous. All nodes have equal energy at the start. All nodes have their positions fixed and cannot move. The position of BS is also fixed. All nodes know the location of every node and BS. This will result in minimum energy usage for the transmission of data from member nodes to CH and thus result in better energy efficiency. Cluster head selection is done with the help of a weight equation which takes into account the remaining energy and degree of the node. This helps in load balance. The advantages of it are clusters generated as node speed increased, only one iteration against repeated iterations, each node one message, robust against synchronization errors, can be used for environmental monitoring and battlefield applications
  • 4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 278 2.4 Aries Kusdaryono [18] introduce an enhanced clustering method based on well proven clustering schemes and the basic mechanism of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) but they improve the performance of network lifetime - by choosing the leader node, which sends final data to the base station, considering not only the energy transmission but the energy level as well. To reduce the energy dissipation, they also introduce two modes of operation - ON and Standby. Our scheme starts with the initialization phase in which each node sends data of energy level and location to the base station. The base station computes the values and sends a message to each node. The next step is the formation phase. In this phase we organize clusters with ID of nodes and ID of cluster heads first and then build the energy layer’s level. Finally, the leader node which will send the final aggregated data to the base station is determined. The final step is the transmission phase, where all nodes will send data to a designated node. The advantage of this algorithm is balanced cluster forming, low message overhead, Uniform & non-uniform node distribution, inter cluster communication explained. III. PROPOSED WORK 3.1 Sectoring- Sectoring is done by Base Station. Optimum number of sectors is found out by the BS depending on the size of the network. Equal hexagon shaped clusters are formed. BS will give a sector ID to each node which is permanent. Sectoring is only done once in the network and is permanent throughout the lifetime of the network. When event is occurred at that time whatever nodes are near to that event are get activated and they are responsible for transferring data from event to sink. At that time unnecessarily energy of nodes which are far away from the event occurred is get used .To avoid this, here, some sectoring scheme is made towards the nodes and wherever the event is occurred the nodes which are there in that sector are only alive others are in sleep mode and head of that sector collecting packets from other nodes which are near to the event .Though sector head is near to the sink end to end delay get reduced. This gives the more reliability. This proposes sectoring scheme to improve reliability for sector based wireless sensor network. In order to improve reliability, sensing region is separated into sectors and initial node of sector, which is near to the sink called as a sector head. In figure 3, suppose at first sector, event is occurred i.e. node number 6, then nodes which are near to the event occurred node they pass the information to the sector head 1(SH 1) and then sector head pass information to the sink node. So simultaneously other sectors are in sleep mode if there is no event occurred. Fig.3 Sectoring scheme used in WSN
  • 5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 279 IV. PERFORMANCE ANALYSIS 4.1 Simulation Model and Environments To support a wide range of simulations, our simulation code was implemented around NS-2 simulator. Our simulation models a network of 100 sensor nodes. General CSMA is used as MAC protocols and two-ray model is for propagation models. In the scenario Area of Sensor Field used is 1000*1000. Topology Used is Hierarchical. Size of the packet is 512 Bytes. Transmission Range of sending packets per second is 550. Number of sensor nodes used for taking reading is 40. Medium-access control protocol used for implementation is IEEE 802.11.Buffer occupancy to store all packets is 50.Routing protocol used is AODV (Ad hoc On-Demand Distance Vector). Simulation Time need for evaluation is 40 sec. 4.2 Simulation Results Fig.4 Comparison for Packet Delivery Ratio Figure 4 shows comparison between with and without sectoring approach for PDR. Graph shows that with-sectoring scheme gives more PDR than without-sectoring scheme because in this scheme chances of congestion are less. As in each sector less number of sensor nodes is situated and because if this less number of traffic flows. Fig.5 Comparison for Routing overhead
  • 6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 280 Figure 5 shows comparison between with and without sectoring approach for Routing overhead. Graph shows that with-sectoring scheme gives less routing overhead. As numbers of nodes are very precise in each sector so finding the neighbor is very easy and hence routing performance is improved. Fig.6 Comparison for Average delay Figure 6 shows comparison between with and without sectoring approach for Routing overhead. Graph shows that with-sectoring scheme gives less delay. Using sectoring scheme nodes are divided in different sectors. As less numbers of sensor nodes are situated in each sector, finding neighbor is easy task and hence transfer packets from source to destination need less time. Fig.7 Comparison for Average energy consumed Figure 7 shows comparison between with and without sectoring approach for Routing overhead. Graph shows that Energy consumption for with-sectoring scheme is less. As routing overhead is less, delay is less; chances of congestion are less because of all this factor energy consumption is also less.
  • 7. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 281 CONCLUSION The obtainable work, which impact on sinks to extensively enlarge the lifetime of the sensor network through the use of sectoring scheme. The proposed sectoring method gives more reliability i.e. 57 % with less routing overhead i.e. 31.7, delay i.e. 1.4ms and minimum energy consumption i.e. 69 mJ. The sectoring scheme provides 50% improvement in packet delivery ratio, almost 100 % routing overhead and delay decreases than random scheme. According to results sectoring scheme is superior to random scheme. REFERENCES [1] Enam R.N., Imam M., Qureshi R.I. (2012) International Conference on Collaboration Technologies and Systems, Denver, Colorado, USA, 4, 157-163. [2] Farizah Y., Ismail N.N., Ariffin S.H. , Shahidan A.A. , Fisal, S.K. Syed-Yusof, (2011) International Journal of Engineering Science Invention, Skudai, Malaysia , 2(5), 26-29. [3] Sandip Kumar C., Tumpa P., Sipra D. B. (2011) International Conference on Information Networking, Barcelona , 3, 58 - 63. [4] Yan G. , Yucheng S. , Han H. , Tong Y. (2011) International Conference on Wireless Communications and Signal Processing, Nanjing, 2, 1 – 6. [5] Akbari, F, Yaghmaee M.H. (2010) fifth International Symposium on Telecommunications, Tehran, 1, 470 – 475. [6] Ahmed A. (2011) Journal of Wireless Sensor Network, Online, 3(3), 106-113. [7] Zhan-Bo S., Yuan-ming W. (2009) International Conference on Apperceiving Computing and Intelligence Analysis, Chengdu, 3, 26-30. [8] Sunil K., Zhenhua F., Fei H.,Yang X. (2009) Journal Wireless Communications & Mobile Computing, online, 9(10), 1301-1311. [9] Alper B., Ozgur B. A. (2009) Conference on Wireless Communications & Networking, Budapest, 1-6. [10] Isik M. T., Ozgur B. A. (2009) IEEE Journal of Communications Magazine, USA, 47(8), 92-99. [11] Jin-Young C. , Sung-Min J., Young-Ju H., Tai-Myoung C. (2008) Second International Conference on Sensor Technologies and Applications, Cap Esterel, 366- 371. [12] Wategaonkar D.N., Deshpande V.S. (2013) International Journal of Wireless Communication, ISSN: 2231-3559 & E-ISSN: 2231-3567, 3(1), 47-50. [13] Wategaonkar D.N., Deshpande V.S. (2013), Patent published on “Sectoring Approach for Separation of Sensor Nodes in Various Sectors to Achieve Reliability”, Number: 231/Mum/2013 A. [14] H. Rad, B. Abolhassani, M. Abdizadeh (2010), Wireless Sensor Network, 2(12), 905- 909. [15] Abin J. J., U.Hari (2013), International Journal of Engineering Research & Technology, Tamil Nadu, 2(5), 1249-1252. [16] Aries K. , Kyung O. L. (2011) , Journal of Information Processing Systems, Korea, 7(1), 29-42. [17] S.R.Shankar and Dr.G.Kalivarathan, “Feasibility Studies of Wireless Sensor Network and its Implications”, International Journal of Electrical Engineering & Technology (IJEET), Volume 4, Issue 2, 2013, pp. 105 - 111, ISSN Print : 0976-6545, ISSN Online: 0976-6553. [18] Revathi Venkataraman, K.Sornalakshmi, M.Pushpalatha and T.Rama Rao, “Implementation of Authentication and Confidentiality in Wireless Sensor Network”, International Journal of Computer Engineering & Technology (IJCET), Volume 3, Issue 2, 2012, pp. 553 - 560, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.