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1 INTERNATIONAL JOURNAL OF ADVANCES IN COMPUTING AND INFORMATION TECHNOLOGY An international, online, open access, peer reviewed journal Volume 2 Issue 2 April 2013 Research Article ISSN Copyright by the authors - Licensee IJACIT- Under Creative Commons license 3.0 ABSTRACT Design and load balancing of a novel routing protocol for UWSN Shashank Yadav, Kusum Gupta,Ajay SinghYadav SRM University NCR CAMPUS, Ghaziabad doi : /ijacit The beautiful and mystical ocean remains one of the most unexplored and inaccessible regions on earth. Underwater sensor networks are envisioned to enable applications for oceanographic data collection, pollution monitoring, and onshore exploration, disaster prevention. This paper introduces a novel routing protocol for underwater sensor networks and a proposed method for load balancing. Node deployment and Location Identification is also discussed for underwater environment Energy is one of the most important factor for sensors because this is very difficult to change the battery Load balancing is one of the most important issue discussed in this paper. Keywords: Load balancing, UWSN, Sensor networks. 1. Introduction One major application of sensor networks is in the investigation of complex and uninhabited under water surfaces; such sensor networks are called the Underwater Wireless Sensor Networks (UWSN). The novel networking paradigm of UWSN is facing a totally different operating environment than the ground based wireless sensor networks. This introduces new challenges such as huge propagation delays, and limited acoustic link capacity with high attenuation factors. Underwater Sensor Networks (UWSNs) are proposed as a means for oceanic observation, offering new capabilities such as real time monitoring, remote configuration, and improved robustness. Underwater sensor networks are envisioned to enable applications for oceanographic data collection, pollution monitoring, and onshore exploration, disaster prevention. Self -organize an autonomous network which can adapt to the characteristics of the ocean environment. This paper is divided by six sections. In section 1given a basic introduction of UWSN, section 2 is related to the basic properties of acoustic communication. In section 3 provide the overview of and architecture of UWSN, section 4 is shown the load balancing mechanism. And section 5show the simulation and results, finally give the conclusion of the paper in section Applications of UWSN The applications of UWSN are vast and may vary from short term to long term applications and systems. The short term systems are usually associated with the quick exploration tasks, for example, an investigation around ship wreckage, while the long term system is usually used in monitoring and environmental data gathering. Received on March 2013, Published on April

2 1. Ocean sampling networks 2. Environmental monitoring 3. Under sea explorations 4. Disaster prevention 5. Distributed tactical surveillance 6. Mine reconnaissance 2. Related work and literature survey Acoustic communications depend on many factors such as path loss, noise, multi-path, Doppler spread, and high and variable propagation delay. All these aspects establish the temporal and spatial variability of the acoustic channel. The available bandwidth of the underwater acoustic channel is very limited and it s depending on both range and frequency. In long-range systems and short- range system these factors lead to low bit rates. In addition, the communication range is reduced as compared to the terrestrial radio channel. 2.1 Basics of Acoustic Communication Acoustic communications depend on many factors such as path loss, noise, multi-path, Doppler spread, and high and variable propagation delay. All these aspects establish the temporal and spatial variability of the acoustic channel. The available bandwidth of the underwater acoustic channel is very limited and it s depending on both range and frequency. In long-range systems and short- range system these factors lead to low bit rates. In addition, the communication range is reduced as compared to the terrestrial radio channel. 2.2 Architecture of UWSN There are many underwater sensor networks architecture possible. The communication architectures introduced here are used as a basis for discussion of the challenges associated with underwater acoustic sensor networks. The underwater sensor network topology is an open research issue in itself that needs further analytical and simulative investigation from the research community. 2.3 Communication Architecture The architecture of on-line system can be identified with one of three broad categories 1. Two-Dimensional Static Network, 2. Three-Dimensional Static Network 3. Three-Dimensional Static Network with Mobile AUVs. 2.4 Two Dimensional Static Sensor Networks The first category of UWSNs is very similar to the GBSNs where the sensor nodes are lying at almost the same level of elevation as the name indicates, i.e. the sensor nodes are lying on the bottom of the ocean or anchored to the ocean bed. Underwater sensor nodes are interconnected to one or more underwater sinks (uw-sinks) by means of wireless acoustic links. UW - sinks, as shown in figure 3.1, are network devices in charge of relaying data from the ocean bottom network to a surface station. Shashank Yadav et al 18

3 Figure 1: Architecture of Two- Dimensional Static UWSN A different approach can be to anchor sensor devices to the bottom of the ocean. In this architecture, depicted in Figure 3.2, each sensor is anchored to the ocean bottom and equipped with a floating buoy that can be inflated by a pump. Figure 2: Architecture of Three-Dimensional Static UWSN AUVs can function without tethers, cables or remote control, and therefore they have a multitude of applications in oceanography, environmental monitoring, and underwater resource study. Previous experimental work has shown the feasibility of relatively inexpensive AUV submarines equipped with multiple underwater sensors that can reach any depth in the ocean. Hence, they can be used to enhance the capabilities of underwater sensor networks in many ways. Shashank Yadav et al 19

4 Figure 3: Architecture of Three Dimensional with Mobility UWSN. 2.5 Design and load balancing Load Balancing about distributing the network's load evenly among the nodes. The weight factor computes the probability of connecting to a node based on its hop-distance and number of children (load) when energy level is constant. Calculate the minimum weighting factor for each node. 2.6 Routing Algorithms Here the node broadcast data in upper hemisphere. The communication range of a node is assumed to be uniform in all directions, which means it covers a sphere where the node is the center with a range radius proportional to its transmission power. The important assumption is the symmetrical property of the channel i.e. if a node A is able to hear node B, then node B can hear also node A. Nodes are fixed in a location using anchors or buoys which means no movement is assumed, since the adopted architecture for UWSNs is the Static Three- Dimensional one. The architecture, as mentioned earlier, is widely used in long term applications such as ocean sampling and environmental monitoring. However, some relative movement is expected but it is unlikely to affect the constructed routes or the operation of the routing algorithm. 3. Algorithm Step 1: A node will broadcast connection request in upper hemisphere. (Because our goal is to send the data from node to sink) Step 2: It will receive ACK from the node who is interested for the connection. (Only interested node) Step 3: (Received ACK should have three fields) Node will calculate minimum weight factor w by using the formula. Shashank Yadav et al 20

5 weigt factor w = (e l )/E Node will evaluate the interested nodes for connections by the comparing the calculated value of on the behalf of these (Load, distance, energy) factors of all nodes and connect accordingly. (If any ACK has directly comes from the sink then it will directly connected to the sink) Step 4: It will send ACK to the selected node in step 3. Step 5: node will transmit data to the node to which it got connected. Step 6: node will wait for ACK of that data PKT which was sent. Step 7: If ACK is received in time T then go to step 6. Step 8: If no ACK, go to step Minimum Weight Calculation (for Load Balancing) In this algorithm, three fields are necessary for calculation of weight to each node. We know that the effect of load is exponential and assume the hop distance is linear. Load l: No. of nodes transmitting data to this interested node. Hop-Distance h: no. of hops between node and sink. Energy level E: energy saved at particular node. weigt factor w = 4. Simulation and result (e load op distence)/energy This chapter will present the results from simulations conducted on the proposed Routing algorithms and give a brief analysis of the result.show the effect and relationship between load, hop-distance and energy level of node. 4.1 Load Balancing By using the equation of weight factor, generate the graph between Load and hop-distance when energy is constant. And check the weight factor at different hop distance. Shashank Yadav et al 21

6 weight factor Design and load balancing of a novel routing protocol for UWSN Table 1: Weighting factor when energy is constant hopdistance1 hopdistance2 hopdistance3 hopdistance Load Figure 4: Graph between no. of children (Load) and hop-distance when energy is 1 (100%). Figure 4 shows that relational ship between Load (no. of children) and weight factor. When load increases then the value of weight factor is also increase. Load increases exponentially while the effect of hop distance is linear. At the hop distance 1, when load 1 then the value of weight factor is 2.718, at load 2 weight factor 7.389, at load 3 weight factor and when load is 4 then weight factor is This result shows that if 10.6 loads increased then its effect is exponential. As an example, Node 400 had about 46 children connected, but using the weight factor, it now supports only 19 children. However, other nodes have to share this load, which in this case is taken up by Node 361 which is supporting 26 children instead of a zero as per the previous distribution. Shashank Yadav et al 22

7 Before using the Weight factor (No Load Balancing) Figure 6: Number of Children and Load Balancing In figure 6 shows that load is divided equally all the nodes on the behalf of their weight factor. It has previously explained that weight factor decides on the three main factors, like energy level, hop distance and load. These factors decide that whose node can bear maximum load on the node with efficient manner. After using the Weight factor (With Load Balancing) Figure 7: Number of Children and Load Balancing All the nodes are sending their packets hop by hop to the sink, while these nodes have to relay those packets on behalf of the entire network. The relaying task cost these nodes more energy than any other node in the network, which makes them die earlier than others. As a result of that, the life span in the network is limited by this group of nodes, regardless of the load balancing scheme used in the network. Shashank Yadav et al 23

8 5. Conclusion This work targeted the implementation of routing layers in UWSNs. The design requirements were imposed mainly because of the different working environment of UWSNs. In this paper a new algorithms is proposed for underwater sensor networks communication mechanisms and load balancing. There are three main factors like energy level, hop distance and load (no. of children). The weight factor computes the probability of connecting to a node based on its hop-distance and number of children (load) when energy level is constant. Calculate the minimum weighting factor for each node with using different factors. When Node will be select minimum weight factor it means that node will select that parent who has maximum energy level, minimum load and minimum hop distance. It means that those node has minimum weight factor will be select as a parent so load will be balanced at each node. When all the nodes are sending their packets hop by hop to the sink, while these nodes have to relay those packets on behalf of the network if the entire network has balanced load at each node then packet can easily arrives from one hop to another hop and there will no more traffic at any single node because load will be distributed. Due to the load balancing, the performance of entire networks will be increased. 6. References 1. F. Akyildiz, D. Pompili and T. Melodia, (2004), Challenges for efficient communication in underwater acoustic sensor networks, SIGBED Review, 1, pp E. M. Sozer, M. Stojanovic and J. G. Proakis, (2000), Underwater acoustic networks, Oceanic Engineering, IEEE Journal of, 25, pp J. Partan, J. Kurose and B. N. Levine, (2006), A survey of practical issues in underwater networks," in WUWNet '06: Proceedings of the 1st ACM International Workshop on Underwater Networks, pp J.Heide mann, W.Ye, J.Wills, A.Syed, and Y.Li. Research, (2006), Challenges and Applications for Underwater Sensor Networking, IEEE Wireless communication and Networking Conference, April J.H.Cui, J. Kong, M.Gerla, and S.Zhou, (2006), Challenges: Building Scalable Mobile Underwater Wireless Sensor Networks for Aquatic Applications. IEEE Network, Special Issue on Wireless Sensor Networking, 20(3), pp F.S ch ill, U.R.Zi mme r, an d J.Trump f. Visible, (2004), Spectrum Optical Communication and Distance Sensing for Underwater, Application s. In Proc. Australasian Conf. Robotics and Automation, May Shashank Yadav et al 24

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