Honey-Bee Mating based Bound Time Approach for Energy minimization in Wireless Sensor Networks
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(IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010 Honey-Bee Mating based Bound Time Approach for Energy minimization in Wireless Sensor Networks J Senthilkumar Dr.R.Lakshmipathi Assistant Professor/IT Professor/EEE Sona College of Technology St.Peters Engineering College Salem, Tamilnadu, INDIA Chennai, Tamilnadu, INDIA firstname.lastname@example.org email@example.com V.Mohanraj Y.Suresh Assistant Professor/IT Assistant Professor/IT Sona College of Technology Sona College of Technology Salem, Tamilnadu, INDIA Salem, Tamilnadu, INDIA firstname.lastname@example.org email@example.com Abstract—In Wireless Sensor Network, dynamic cluster based energy efficient communication models and protocols that are routing protocol approach is widely used. Such practiced designed for specific applications and topologies. approach, quickly depletes the energy of cluster heads and induces the execution of frequent re-election algorithm. This LEACH (Low Energy Adaptive Clustering Hierarchy) is repeated cluster head re-election algorithm increases the number one of the most referenced protocols in the sensor networks of advertisement messages which in turn depletes the energy of area ,,. In LEACH and other routing protocols, when overall sensor network. Here, we proposed the Bound Time and current cluster head changes due to self destruction or energy Honey Bee Mating Approach (BT-HBMA) that reduces the loss, increases the overhead, in turn leading to higher energy cluster set up communication overhead and elects the stand by consumption. This is one of the worrying drawbacks. A node in advance for current cluster head which has the capability possible solution which is proposed in this paper is the use of to withstand for many rounds the bound time to reduce set-up communication overhead. During this bound time, sensor nodes receive advertisement Our proposed BT-HBMA method uses the Honey bee mating messages and from this, node determines multi-route for behaviour in electing the stand by node for current cluster head. transmission and consider only the message with the minimum This approach really outperforms the other methods in achieving number of hops and stand by cluster heads are elected. reduced number of re election and maintaining high energy nodes between the rounds. The rest of the paper is organized as follows. In Section II, we review the related work. In Section III, describes Honey bee Keywords- Cluster based Routing; Wireless sensor network; structure and modeling. The proposed method of BT –HBMA Honey Bee mating; Bound Time algorithm for cluster formation is described in Section IV. In Section V, We presented the Simulation results. Finally Section VI, concludes the paper. I. INTRODUCTION II RELATED WORK Wireless Sensor Networks (WSNs) are formed by a set of nodes that gather information and forward it to a sink. They Hierarchical or Cluster –based routing, originally proposed are formed by small, inexpensive and resource limited devices in wire line networks, are well-known techniques with special that can interact with the environment and communicate in a advantages related to scalability and efficient communication. wireless manner with other devices  WSNs present a new As such, the concept of hierarchical routing is also utilized to challenge research problem due to their high flexibility to perform energy efficient routing in WSNs. In a hierarchical support several real-world applications. The core operation of architecture, higher nodes can be used to process and send the wireless sensor network is to collect and process data at the information while low energy nodes can be used to perform network nodes, and transmit the necessary data to the base the sensing in the proximity of the target. This means that station for further analysis and processing. Due to large creation of Clusters and assigning special tasks to cluster- network size, limited power supply, and inaccessible remote heads can greatly contribute to overall system scalability, environment, the WSN-based protocols are different from the lifetime, and energy efficiency. traditional wireless protocols .Currently there are several 134 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010 Hierarchical routing is an efficient way to lower energy nest, lay the eggs, and feed the larvas. The first group of consumption within a cluster and by performing data broods is reared alone until they take over the work of the aggregation and fusion in order to decrease the number of colony. Subsequently, division of labor takes place and the transmitted messages to the base station. queen specializes in egg laying and the workers in brood care . Heinzelman introduced a hierarchical clustering Another founding method is called “swarming” in which a algorithm for sensor networks, called Low Energy Adaptive new colony is founded by a single queen or more, along with a Clustering Hierarchy(LEACH). LEACH is a cluster based group of workers from the original colony. protocol, which includes distributed cluster formation. The operation of LEACH is split into two phases, the set-up phase A colony of bees is a large family of bees living in one and steady state phase. During the set-up phase, the clusters bee-hive. A bee hive is like a big city with many “sections of are created and cluster heads are elected. LEACH randomly selects a few sensor nodes as cluster-heads and broadcast an the town”. The queen is the most important member of the advertisement message to the entire network declaring that hive because she is the one that keeps the hive going by they are the new cluster heads. Every node receiving the producing new queen and worker bees. With the help of advertisement decides to which cluster they wish to belong approximately 18 males (drones), the queen bee will mate with based on the signal strength of the received message. The multiple drones one time in her life over several days. The sensor node sends a message to register with the cluster-head sperm from each drone is planted inside a pouch in her body. of their choice. Based on a TDMA approach, the cluster head She uses the stored sperms to fertilize the eggs. Whether a assigns the time slot to registered node for sending the data. honeybee will become a queen, a drone, or a worker, During the steady-state phase, sensor nodes can start depends on whether the queen fertilizes an egg. Since she is transmitting data to their respective cluster-head. The cluster the only bee in the colony that has fully developed ovaries, head applies aggregation functions to compress the data before the queen is the only bee that can fertilize the egg. Queens and transmission to the sink. After a predetermined period of time workers come from fertilized eggs and drones from spent on the steady-state phase, the network enters the set-up unfertilized eggs. phase again and starts a new round of creating clusters. Only the queen bee is fed “royal jelly,” which is a milky- Although LEACH is able to increase the network lifetime, white colored jelly-like substance. “Nurse bees” secrete this there are still a number of issues about the assumptions used in nourishing food from their glands, and feed it to their queen. this protocol. LEACH assumes that all nodes can transmit with The diet of royal jelly makes the queen bee bigger than any enough power to reach the base station if needed and that each other bees in the hive. A queen bee may live up to 5 or 6 node has computational power to support different MAC years, whereas worker bees and drones never live more than 6 protocols. Therefore, it is not applicable to networks deployed in larger regions. It also assumes that nodes always have data months. There are usually several hundred drones that live to send, and nodes located close to each other have correlated with the queen and worker bees. Mother nature has given the data. It is not obvious how the number of the predetermined drones just one task which is to give the queen some sperm. cluster-head is going to be uniformly distributed through the After the mating process, the drones die. As the nights turn network. Therefore, there is the possibility that the elected colder and winter knocks the door, the drones still in the hive cluster head will be concentrated in one part of the network. are forced out of the hive by worker bees. It is a sad thing, but Hence, some nodes will not have any cluster heads in their the hive will not have enough food if the drones stay. area. Queens represent the main reproductive individuals which Lindsey and Raghavendra, proposed an enhancement are specialized in eggs laying . Drones are the fathers of the over LEACH protocol. The protocol, called Power-Efficient colony. They are haploid and act to amplify their mothers’ Gathering in Sensor Information Systems (PEGASIS), is a genome without altering their genetic composition, except near optimal chain –based protocol. It achieved the through mutation. Workers are specialized in brood care and performance through the elimination of the overhead caused sometimes lay eggs. Broods arise either from fertilized or by dynamic cluster formation and through decreasing the unfertilized eggs. The former represent potential queens or number of transmissions and reception by using data workers, whereas the latter represent prospective drones. aggregation. Although the clustering overhead is avoided, still The mating process occurs during mating-flights far from requires dynamic topology adjustments. the nest. A mating- flight starts with a dance where the drones This paper provides a protocol with the same underlying follow the queen and mate with her in the air. In a typical benefits as LEACH and PEGASIS and reduces the number of mating-flight, each queen mates with seven to twenty drones. set-up messages required which in turn increases the network lifetime. In each mating, sperm reaches the spermatheca and accumulates there to form the genetic pool of the colony. Each III HONEY-BEE COLONY STRUCTURE time a queen lays fertilized eggs, she retrieves at random a mixture of the sperms accumulated in the spermatheca to A honey-bee colony typically consists of a single egg fertilize the egg. Insemination ends with the eventual death of laying long-lived queen, anywhere from zero to several the drone, and the queen receiving the “mating sign.” The thousand drones (depending on the season) and usually queen mates multiple times but the drone inevitably only once. 10,000 to 60,000 workers . The colony can be founded in These features make bees-mating the most spectacular mating two different ways. In “independent founding” the colony among insects. starts with one or more reproductive females that construct the 135 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010 A. Honey-bees modeling head changes. These changes are due to cluster head failures The mating–flight may be considered as a set of transitions in or when its energy level approaches a certain threshold value. a state-space (the environment) where the queen moves During the bound-time, sensor node receives single multi- purpose message and from this the node starts to determine between the different states in some speed and mates with the the following 1) possible routes from the cluster head to sensor drone encountered at each state probabilistically. At the start node 2) learns the minimum number of hops to reach the of the flight, the queen is initialized with some energy content selected cluster head.3) Stand by nodes are chosen for next to and returns to her nest when her energy is within some current cluster head. Hence, this single multi-purpose threshold from zero or when her spermatheca is full. advertisement message can be used for both reducing the set- In developing the algorithm, the functionality of workers is up communication overhead and fault tolerant, thus makes our restricted to brood care and therefore, each worker may be protocol more energy efficient. represented as a heuristic which acts to improve and/or take care of a set of broods (i.e., as feeding the future queen with The operation of the proposed routing protocol can be split royal jelly). A drone mates with a queen probabilistically into two phases: the role determination phase and the data using an annealing function as: transfer phase B. Role Determination Phase exp − ∆( f ) s (t ) Prob (Q, D) = (1) During this phase, cluster heads are selected and clusters are formed. At the start up, base station randomly selects some desired percentage of nodes as cluster heads and broadcasts where Prob (Q, D) is the probability of adding the sperm of selected information to the network. On receiving the drone D to the spermatheca of queen Q (that is, the probability broadcasted information, each node checks its status whether of a successful mating); ∆( f ) is the absolute difference it has been selected as cluster head or not. If yes, it starts a between the fitness of D (i.e.ƒ(D)) and the fitness of Q(i.e. f new cluster formation by broadcasting an advertisement (Q)); and S(t ) is the speed of the queen at time t. It is message. Otherwise, it forwards the message to its neighbors. apparent that this function acts as an annealing function, Every cluster head creates an advertisement message which where the probability of mating is high when both the queen is has the number of hops count to zero and broadcast it to its still in the start of her mating–flight and therefore her speed is neighbors. If a node already belongs to another cluster for high, or when the fitness of the drone is as good as the which the number of hops to reach the current belonging queen’s. After each transition in space, the queen’s speed, cluster is less than newly received broad cast then it ignores S(t), and energy, E(t), decay using the following equations: the received message. The bound time of a node starts when it accepts an S (t + 1) = a × S (t ) (2) advertisement message. When the bound-time is still valid, the node caches the received message and waits for other possible E (t + 1) =E (t)-γ (3) advertisement. In this way, it collects all possible alternative paths to chosen cluster head. All the sensor nodes consider the Where a is a factor ∈ [0, 1] and γ is the amount of energy message with minimum number of hops count (shortest route) reduction after each transition. Thus, an Honey-Bees Mating as the best route. When route fails, an alternate route can be Optimization (HBMO) algorithm may be constructed with the immediately used without delays or degradation of QoS.When following five main stages : the bound-time reaches zero, a route is established with 1) The algorithm starts with the mating–flight, where a queen shortest route and increases the number of hops count by one in the retained message and broadcasts it to its nearby nodes. (best solution) selects drones probabilistically to form the spermatheca (list of drones). A drone is then selected from After bound time expires, all sensor nodes who receive the the list at random for the creation of broods. advertisements message are candidate for stand by node to 2) Creation of new broods (trial solutions) by crossoverring their respective cluster head. All the sensor nodes who the drones’ genotypes with the queen’s. expressed their willingness are collected in the stand by node 3) Use of workers (heuristics) to conduct local search on list and stored in the cluster head. This stand by node list is broods (trial solutions). used as input to our proposed Honey mating algorithm which 4) Adaptation of workers’ fitness based on the amount of is discussed in next section. In the meantime, data transfer improvement achieved on broods. phase is started for conducting data transfer in the network. 5) Replacement of weaker queens by fitter broods. The current energy of the current cluster head is polled in every round time. When the current cluster head energy is depleted to near specified threshold energy level, our proposed IV. PROPOSED METHOD Honey Bee Mating algorithm is triggered to find the best stand by node for current cluster head from the stand by node list. A. Bound Time (BT) Routing Protocol When current cluster head about to dead completely, the best stand by node selected using our approach replaces the current The main objective of our BT approach is to minimize the cluster head. This newly elected cluster head can withstand for set-up communication overhead, whenever current cluster many rounds and there by reduces the number of re-election. 136 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010 Honey-bee mating behavior discussed in section III is equivalently mapped to our proposed BT-Honey Bee mating algorithm in electing the stand by cluster head as shown in figure 1 & figure 2. Trial Stand by Select at Random .. Nodes using Objective Function Next Best Node Best Node List List Exchange of nodes between Best node Mating using the and Next Best Fitness function Node List Apply local search Replace the current on best node list cluster head with the using heuristic elected node function Figure 2. Honey Bee Mating Approach 4. Mating is done through exchange (crossover) between Best Figure 1. Real Honey Bee Mating Approach Node and Next Best Node List based on the fitness function which depends on the closeness to the sink node (if selected).The new best node list are broods. Our fitness function is based on the closeness of stand by node from other C. Honey Bee Mating Algorithm. nodes if it is selected as new cluster head. In cluster, calculates the distance of each node to its cluster-head (if selected) based on number of hops. The lesser the distance the higher the 1. After the Bound time expires, Cluster head collects the probability that the node will become cluster head. The nodes who expressed willingness to act as stand by node and number of hops between i and j node is calculated as follows creates the node list called Trial Stand by node List. No_of_hops (i, j) = 2. Before the start of next step, current energy of nodes in the Min stand by node list are examined and nodes having less energy → are discarded from the stand by node list. A − > 1 .. n 3. From the Standby Node List, Best Node and Next Best j−1 Node List are created using the objective function. The Best node List and Next best node list is equivalent to queen and ( ∑ ( no_ of _ hopsi, I A1 ) + no_ of _ hopsIAK, IA(k+1) ) (5) drones respectively. Our objective function is based on the k=1 remaining energy of stand by nodes. Obviously, the higher the enrgy,the higher the probability that the node will become cluster head. A− > 1..n = Number of Alternative path between i and j node. The remaining energy is calculated as IA1 = 1st Intermediate node in the A th Alternative path to Ec node j Er = (4) Ei K varied from 1st node to j-1 (previous node in reaching jth node) node. Where Ec is the current energy and Ei is the initial energy. 137 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010 5. Perform a local search on the Best Node List by applying the hardware. Sensors are modeled using a pool of the heuristic function which depends on the distance between cluster head [if selected] and base station. The lesser the concurrent, communicating threads. Individual sensors are distance, less power is needed to transmit and receive the able to: data.. Such nodes are having higher probability to become the 1) Gather and process data from a model environment cluster head. This local search gives the best solution. .2) Locate and communicate with their nearest neighbours 6. In case of re-election, current cluster-head is replaced by 3) Determine whether they are operating correctly and new cluster -head which is selected in step 5. act accordingly to alter the network topology in case of faulty nodes being detected. When the cluster round time is over or energy level approaches a threshold, the current cluster head hands the Separate interfaces gather information from the network and main role to new elected cluster head . With a single flooding display it on the graph pane or the chart pane, where to cluster members, the new cluster head continues its main individual data can be plotted during the simulation. This role without the need for further communication. partitioning allows us to experiment with different ways of processing individual node data into information D. Data Transfer Phase The second phase is called data transfer or steady state Using the SenSor Plus framework, we implemented phase. In this phase, data transfer is started as soon as bound the proposed algorithm. For our simulation, we gave all the time expires. This phase is identical to steady state phase nodes an initial supply of energy and ran the protocol until it proposed in LEACH.The steady state is broken into frames converged. For our Experiments, we created a 100-node where nodes send their data to the cluster-head at most once network, where the nodes are scattered randomly on 600×600 per frame during their allocated transmission slot which grid, such that no two nodes share the same location. In our scheduled by TDMA. Once the cluster- head receives all the data, it performs data aggregation and forwards the final data simulation, we considered the initial simulation parameter and to the base station. its values as shown in Table I. TABLE I SIMULATION PARAMETERS V SIMULATION RESULT Our proposed algorithm is implemented and completely Parameter Value Motivation studies using the simulation tool called SenSor Plus. This is Initial Energy 1J Standard energy value used for an in- house sensor network simulator. SenSor  is a batteries in most sensor nodes. realistic and scalable Python based simulator that provides a workbench for prototyping algorithms for WSN. It Broadcast size 11 bit Assume that the sensor is consists of a fixed API, with customizable internals. Each packet broadcasting an ID of 11 bits. simulated sensor node runs in its own thread and Routing Size 11 bit Assume that the sensor is routing communicates using the same protocols as its physical Packet packets of size 11 bits counterpart would be. This enables experimentation with different algorithms for managing the network topology, simulating fault management strategies and so on, within Our proposed BT-HBMA methods outperforms the other the same simulation. SenSor Plus is an extension of Sensor methods such as LEACH, PEGASIS in achieving reduced with an added interface between the simulation number of re election and maintains high energy nodes environment and different hardware platforms, for between the rounds. According to Table II, it is clear that our example the Gumstix  platform. SenSor Plus bridges honey bee mating approach selects the best stand by node between Sensor and the Gumstix to allow applications which can withstand for more rounds compare to other implemented within the simulator to be ported directly on to methods. 138 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010 No of Re election Vs Rounds in Cluster 1 200 180 160 No of Re election 140 120 PEGASIS 100 LEACH 80 BT-HBMA 60 40 20 0 50 100 150 200 250 300 350 400 450 500 550 No of Rounds in cluster 1 Figure3 No of Re election Vs No of Rounds in cluster 1 TABLE II NUMBER OF REELECTION BETWEEN THE ROUNDS IN CLUSTER1 According to table III, the average energy of nodes in the Number of Re-election in Cumulative cluster 1 is fair in our approach compared to other methods. Cluster 1 Manner The figure 4 shows that average energy of nodes in cluster 1 in terms of Joules between the numbers of rounds (Number of LEACH PEGASIS BT-HBMA Rounds) TABLE III AVERAGE ENERGY OF NODES IN CLUSTER1 BETWEEN THE ROUNDS 150 21 27 11 Average energy of nodes in cluster1 250 32` 39 19 Cluster 1 (Joules) 350 41 48 27 (Number of 450 51 59 36 Rounds) LEACH PEGASIS BT-HBMA 550 63 72 49 150 0.97 0.95 0.982 250 0.95 0.93 0.962 By this approach, we can reduce the total number of re 350 0.84 0.81 0.895 election that likely to happen in the network if other methods are followed. This also implicitly achieves excellent data 450 0.752 0.69 0.842 transfer phase. The Figure 3 depicts that our proposed method outperforms the other methods in reducing the number of re- 550 0.593 0.43 0.712 election. 139 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010 Average Energy Vs Number of rounds in Cluster 1 1.2 1 Average Energy (Joules) 0.8 BT-HBMA 0.6 LEACH 0.4 PEGASIS 0.2 0 150 250 350 450 550 Number of Rounds Figure 4 Average Energy of nodes in cluster 1 Vs No of Rounds in cluster 1 Our proposed BT-HBMA method, each cluster head and its respective members are having higher average energy even REFERENCES after the 550 rounds. The other methods decay energy because of the more number of re election.  I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: a survey,” Computer Networks, vol. 38, no. 4, VI. CONCLUSIONS 393– 422, 2002.  D. Estrin, D. Culler, K. Pister, and G. Sukhatme, “Connecting the physical world with pervasive networks,” IEEE Pervasive This paper provides a better solution to reduce the number Computing, 59–69, January-March 2002. of re-elections by selecting the best stand by node in advance  W.B Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy- for current cluster head. Our proposed BT-HBMA is Efficient Communication Protocol for Wireless Microsensor Networks,” equivalently mimics the Honey Bee Mating Behaviour of Real In the Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS '00), January 2000. Honey Bees. We have applied the Honey mating behaviour for  A.Manjeshwar and D.P. Agarwal, “TEEN: a routing protocol the first time in the stand by node selection of Wireless sensor for enhanced efficiency in wireless sensor networks,” In the 1st network. This Honey bee mating inspired approach is International Workshop on Parallel and Distributed Computing Issues in effectively used to choose the best stand by node from Wireless Networks and Mobile Computing, April 2001. multiple available solutions. Our proposed BT-HBMA method  M. Ye, C. Li, G. Chen, and J. Wu. Eecs: An energy efficient c is accurately finds the best stand by node from available Trial lustering scheme in wireless sensor networks. In Performance, stand by node list. The stand by node choosen as best solution Computing, and Communications Conference, 2005. IPCCC 2005. in our approach withstands for many rounds and improves 24th IEEE Interna tional, pages 535– 540, April 2005. over all data transfer rate as well as maintains fair average  S. Lindsey and C. Raghavendra, “PEGASIS: Power-Efficient Gathering energy in the Wireless Sensor Network. Our simulation results in Sensor Information Systems,” IEEE Aerospace Conference Proceedings, 2002, vol. 3, no. 9-16, 1125-1130. shows that there is reduction in number of re election  M. Hammoudeh. Robust and energy efficient routing in wire less conducted in the network compared to the existing methods sensor networks. Master's thesis, University of Leicester, 2006. like LEACH and PEGASIS. In future, we would like to apply  R.F.A. Moritz and E.E. Southwick, Bees as Superorganisms, Springer, our BT-HBMA to different Wireless Sensor Network Layouts Berlin, Germany (1992). for improving the scalability factor. 140 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 5, August 2010  H.H. Laidlaw and R.E. Page, Mating designs. In: T.E. Rinderer, Editor, Y.Suresh received his ME Applied Electronics from Anna Bee Genetics and Breeding, Academic Press Inc., New York, NY University, Chennai in 2004. He is working as Assistant (1986), pp. 323–341. professor in IT Department of Sona College of Technology and  H.A. Abbass, Marriage in honey-bee optimization (MBO): a pursuing PhD degree in Anna University, Chennai. He is active haplometrosis polygynous swarming approach, in: The Congress on in the research area of Computer Netoworks, Data mining, Evolutionary Computation (CEC2001), Seoul, Korea, May 2001, 2001, control system and Mobile computing. pp. 207–214.  O. Bozorg Haddad, A. Afshar, M.A. Mariño, Honey bees mating optimization algorithm (HBMO); a new heuristic approach for engineering optimization, in: Proceeding of the First International Conference on Modeling, Simulation and Applied Optimization (ICMSA0/05), Sharjah, UAE, 1–3 February 2005.  S. Mount, R. Newman, and E. Gaura. A simulation tool for system Conference and Trade Show, 3:423, May 2005.  Gumstix.com. Gumstix way small computing, 2007. [Online; accessed 26-March-2007]. AUTHORS PROFILE J.Senthilkumar received his ME Applied Electronics with Distiction from Anna University, Chennai in 2004. He is working as Assistant professor in IT Department of Sona College of Technology and pursuing PhD degree in Anna University, Chennai. He is active in the research area of Wireless Sensor Networks, Mobile computing and Data mining. Dr.R.Lakshmipathi received his BE from College of Engineering, Anna University, India, in 1971, the ME and PhD in Electrical Engineering from College of Engineering, Anna University, India in 1973 and Indian Institute of Technology (IIT), Chennai in 1979, respectively. He has 36 years of teaching experience at UG degree level out of which 10 years in PG degree level. He worked as principal in Govt. College of Engineering and held the various prestigious posts like Dean, Regional Research Director , Chairman for board of BE exams, Member of Academic auditing committee, AICTE, University and State Govt. expert committee member. He is currently a professor of Electrical Engineering, St. Peters Engineering College (Deemed University), Tamilnadu. His research interest includes Electrical power semi conductor drives, Signal processing and Web Mining. V.Mohanraj received his ME Computer science and Engineering from Anna University, Chennai in 2004. He is currently working as Assistant professor in IT department of Sona College of Technology. He is pursuing PhD degree in Anna University, Chennai. His research area includes web mining, database and intelligent system. 141 http://sites.google.com/site/ijcsis/ ISSN 1947-5500