A Real-Time MATLAB based GUI for node placement and a shortestpath alternate route path algorithm in Wireless Sensor Networks

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1 International Journal for Science and Emerging ISSN No. (Online): Technologies with Latest Trends 7(1): (2013) ISSN No. (Print): A Real-Time MATLAB based GUI for node placement and a shortestpath alternate route path algorithm in Wireless Sensor Networks Chetan Chugh* and Ramneek Singh** *A.P. (Department of Electronics and Communication Engg.) DAV Institute of Engg & Tech. **A.P. (Department of Electronics and Communication Engg.) DAV Institute of Engg & Tech. Jalandhar, Punjab, India. (Received 15 April 2013 Accepted 19 April 2013) Abstract: This paper gives a concise pictorial view of wireless sensor node deployment in Matlab. Wireless Sensor Networks (WSNs) have been widely considered as one of the most important technologies for the twenty first century. Enabled by recent advances in microelectronic mechanical systems (MEMS) and wireless communication technologies, tiny, cheap, and smart sensors deployed in a physical area and networked through wireless links and the Internet provide unprecedented opportunities for a variety of civilian and military applications, for example, environmental monitoring, battle field surveillance, and industry process control.this paper provides the path between source and destination nodes for efficient data delivery. The malicious nodes have been selected on manual basis. The alternate shortest route has been found using Dijstra algorithm. Also, an algorithm for public key cryptography i.e. RSA algorithm has been implemented to prevent the nodes from intrusion attacks. Keywords: Wireless sensor networks, RSA, Dijstra, GUI, MATLAB, Intrusion. 1. Introduction to Wireless sensor networks. Wireless Sensor Networks (WSNs)[1] have been widely considered as one of the most important technologies for the twenty-first century. Enabled by recent advances in microelectronicmechanical systems (MEMS) and wireless communication technologies, tiny, cheap, and smart sensors deployed in a physical area and networked through wireless links and the Internet provide unprecedented opportunities for a variety of civilian and military applications, for example, environmental monitoring, battle field surveillance, and industry process control. Distinguished from traditional wireless communication networks, for example, cellular systems and mobile ad hoc networks (MANET), WSNs have unique characteristics, for example, denser level of node deployment, higher unreliability of sensor nodes, and severe energy, computation, and storage constraints, which present many new challenges in the development and application of WSNs. 1.1 Network Characteristics A WSN typically consists of a large number of low-cost, low-power, and multifunctional sensor nodes that are deployed in a region of interest. These sensor nodes are small in size, but are equipped with sensors, embedded microprocessors, and radio transceivers, and therefore have not only sensing capability, but also data processing and communicating capabilities. They communicate over a short distance via a wireless medium and collaborate to accomplish a common task, for example, environment monitoring, battlefield surveillance, and industrial process control. Compared with traditional wireless communication networks, for example, cellular systems and MANET, sensor networks have the following unique characteristics and constraints:

2 12 Chugh and Singh Dense Node Deployment. Sensor nodes are usually densely deployed in a field of interest. The number of sensor nodes in a sensor network can be several orders of magnitude higher than that in a MANET. Battery-Powered Sensor Nodes. Sensor nodes are usually powered by battery. In most situations, they are deployed in a harsh or hostile environment, where it is very difficult or even impossible to change or recharge the batteries. Severe Energy, Computation, and Storage Constraints. Sensor nodes are highly limited in energy, computation, and storage capacities. Self-Configurable. Sensor nodes are usually randomly deployed without careful planning and engineering. Once deployed, sensor nodes have to autonomously configure themselves into a communication network. Application Specific. Sensor networks are application specific. A network is usually designed and deployed for a specific application. The design requirements of a network change with its application. Unreliable Sensor Nodes. Sensor nodes are usually deployed in harsh or hostile environments and operate without attendance. They are prone to physical damages or failures. Frequent Topology Change. Network topology changes frequently due to node failure, damage, addition, energy depletion, or channel fading. No Global Identification. Due to the large number of sensor nodes, it is usually not possible to build a global addressing scheme for a sensor network because it would introduce a high overhead for the identification maintenance. Many-to-One Traffic Pattern. In most sensor network applications, the data sensed by sensor nodes flow from multiple source sensor nodes to a particular sink, exhibiting a many-to-one traffic pattern. Data Redundancy. In most sensor network applications, sensor nodes are densely deployed in a region of interest and collaborate to accomplish a common sensing task. Thus, the data sensed by multiple sensor nodes typically have a certain level of correlation or redundancy. 1.2 Sensor Node Structure A sensor node [2] typically consists of four basic components: a sensing unit, a processing unit, a communication unit, and a power unit, which is shown in Fig1. The sensing unit usually consists of one or more sensors and analog to digital converters (ADCs). The sensors observe the physical phenomenon and generate analog signals based on the observed phenomenon. The ADCs convert the analog signals into digital signals, which are then fed to the processing unit. The processing unit usually consists of a microcontroller or microprocessor with memory, which provides intelligent control to the sensor node. The communication unit consists of a short range radio for performing data transmission and reception over a radio channel. The power unit consists of a battery for supplying power to drive all other components in the system. In addition, a sensor node can also be equipped with some other units, depending on specific applications. For example, a global positioning system (GPS) may be needed in some applications that require location information for network operation. All these units should be built into a small module with low power consumption and low production cost. Fig 1. Sensor Node 2. Introduction to Dijstra Algorithm Dijkstra's algorithm [11], conceived by Dutch computer scientist Edger Dijkstarin is a graph search algorithm that solves the single-source shortest path problem for a graph with non negative edge path costs, outputting a shortest path tree.

3 Chugh and Singh 13 This algorithm is often used in routing. For a given source vertex (node) in the graph, the algorithm finds the path with lowest cost (i.e.the shortest path) between that vertex and every other vertex. It can also be used for finding costs of shortest paths from a single vertex to a single destination vertex by stopping the algorithm once the shortest path to the destination vertex has been determined. For example, if the vertices of the graph represent cities and edge path costs represent driving distances between pairs of cities connected by a direct road, Dijkstra's algorithm can be used to find the shortest route between one city and all other cities. 3. Graphical User Interface (GUI) implementation of sensor nodes in MATLAB. The graphical user interface [12] for access to sensor nodes has been implemented in MATLAB. The nodes have been randomly deployed with number of nodes limited to 10. The source node and the destination nodes are to be chosen using drop-down menus available in GUI. The graphical user interface shows the data path between source and destination nodes tracing various nodes, the actual trace path being determined by Dijkstra's algorithm. The interface also features a drop-down menu to manually select the malicious node. Malicious stands for a node which is compromised i.e. being attacked by an intruder. Also a malicious node could also be called a failure node which has been unable to function due to various reasons including environmental factors etc. The GUI also shows the public-key cryptography implemented on the numbering of nodes. If the node 2 sends the data to node 7, the numbering of nodes have been encrypted to show for example node 29 sending the data to node 34. The intermediate nodes numbering is also encrypted using RSA algorithm. In this way, the intruder will not be able to trace the actual data path if he/she wants to disrupt the data path from node 2 to node 7. Such a secure mechanism prevents any kind of compromise against data security. 4. Applying Dijstra algorithm for route discovery. The Dijkstra's algorithm is used to find the shortest route between source and destination nodes. The Dijkstra's algorithm is implemented in steps as shown below. 4.1 Steps for Dijkstra's algorithm Let the node at which we are starting be called the initial node. Let the distance of node Y be the distance from the initial node to Y. Dijkstra's algorithm will assign some initial distance values and will try to improve them step by step Assign to every node a tentative distance value: set it to zero for our initial node and to infinity for all other nodes. Mark all nodes unvisited. Set the initial node as current. Create a set of the unvisited nodes called the unvisited set consisting of all the nodes except the initial node. For the current node [6], consider all of its unvisited neighbors and calculate their tentative distances. For example, if the current node A is marked with a tentative distance of 6, and the edge connecting it with a neighbor B has length 2, then the distance to B (through A) will be 6+2=8. If this distance is less than the previously recorded tentative distance of B, then overwrite that distance. Even though a neighbor has been examined, it is not marked as "visited" at this time, and it remains in the unvisited set. When we are done considering all of the neighbors of the current node, mark the current node as visited and remove it from the unvisited set. A visited node will never be checked again; its distance recorded now is final and minimal. If the destination node has been marked visited (when planning a route between two specific nodes) or if the smallest tentative

4 14 Chugh and Singh distance among the nodes in the unvisited set is infinity (when planning a complete traversal), then stop. The algorithm has finished. Set the unvisited node marked with the smallest tentative distance as next "current node" and go back to step 3. The Flowchart for Dijstra algorithm is shown in figure.2 because it is assumed that only the key is known to the receiver. Incase of RSA algorithm, both the plaintext and the cipher-text are integers between 0 to (n-1) for some n. The steps for RSA algorithm are Step 1 : Select two prime nos p & q Step 2 : Calculate n as product of p & q, i.e. n=pq Step 3 : Calculate m as product of (p-1) & (q-1) i.e. m = (p-1)(q-1) Step 4 : Select any integer e<m such that it is co-prime to m, i.e gcd(e,m) =1 Step 5 : Calculate d such that de mod m = 1, i.e. d = e -1 mod m Step 6: The public key is {e,n) The private key is {d,n} 6. Results and discussions The Graphical user interface for wireless sensor nodes has been developed. The figure below shows the snapshot for a network consisting of 10 nodes in MATLAB. Fig 2. Flowchart for Dijkstra's algorithm. 5. Applying RSA algorithm for public key encryption. The RSA algorithm is used to implement public key cryptography. This is done on numbering of nodes. i.e node 2 data destined for node 7 is being spoofed as if node 29 is sending data to node 32. RSA algorithm uses two different keys: Public Key-Known to every communicating entity in the network. Private Key:-Known uniquely to the user. Generally, the receiver's public key is used for encrypting information and is sent to the receiver who decrypts it by his unique private key (known only to him). This ensures confidentiality Figure 3: Wireless sensor network of 10 nodes Also shown is the drop down menus for selecting source and destination nodes. The below figure depicts the data path from source to destination nodes selected by applying Dijkstra's algorithm. The data is sent from node 3 to node 5 via node4.

5 Chugh and Singh 15 networks: a survey." Network Protocols and Algorithms 2.2 (2010): Habib, Asif. "Sensor network security issues at network layer." Advances in Space Technologies, ICAST nd International Conference on. IEEE, Figure 4 : Data path using Dijkstra's algorithm Another figure shows the implementation of RSA algorithm. The nodes have been renumbered i.e node 3 has been encypted to node 66, node 4 to node 93,node 5 to node 110. Figure 5: RSA encryption result 6. Conclusion This work has successfully created a graphical user interface for wireless sensor networks. Also the manual selection of source node, destination node and malicious nodes provide an insight of best short route algorithm for data delivery. Also, the RSA algorithm running in the backend provides a good means to prevent the nodes/path from intrusion.the work contributes sufficiently towards creating a user friendly environment for network users. 7. References 1. Mulligan, Raymond, and Habib M. Ammari. "Coverage in wireless sensor 3. Aschenbruck, Nils, et al. "A security architecture and modular intrusion detection system for WSNs." Networked Sensing Systems (INSS), 2012 Ninth International Conference on. IEEE, Haiyun Luo, Petros Zerfos, Jiejun Kong, Songwu Lu, Lixia Zhang, Selfsecuring Ad Hoc Wireless Networks, IEEE ISCC (IEEE Symposium on Computers and Communications) 2002, Italy. 5. Du, Wenliang, Lei Fang, and Ning Peng. "Lad: Localization anomaly detection for wireless sensor networks." Journal of Parallel and Distributed Computing66.7 (2006): Pires Jr, Waldir Ribeiro, et al. "Malicious node detection in wireless sensor networks." Parallel and Distributed Processing Symposium, Proceedings. 18th International. IEEE, Curiae, D-L., et al. "Malicious node detection in wireless sensor networks using an autoregression technique." Networking and Services, ICNS. Third International Conference on. IEEE, Panos, Christoforos, Christos Xenakis, and Ioannis Stavrakakis. "A Novel Intrusion Detection System for MANETs." Security and Cryptography (SECRYPT), Proceedings of the 2010

6 16 Chugh and Singh International Conference on. IEEE, Yi, Ping, Yue Wu, and Jianhua Li. "Malicious node detection in Ad Hoc networks using timed automata." Wireless, Mobile and Sensor Networks, 2007.(CCWMSN07). IET Conference on. IET, Atakli, Idris M., et al. "Malicious node detection in wireless sensor networks using weighted trust evaluation." Proceedings of the 2008 Spring simulation multiconference. Society for Computer Simulation International. 11. Musznicki, Bartosz, Mikolaj Tomczak, and Piotr Zwierzykowski. "Dijkstra-based localized multicast routing in Wireless Sensor Networks."Communication Systems, Networks & Digital Signal Processing (CSNDSP), th International Symposium on. IEEE, Abuarqoub, Abdelrahman, et al. "Simulation Issues in Wireless Sensor Networks: A Survey." SENSORCOMM 2012, The Sixth International Conference on Sensor Technologies and Applications