A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor Network

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A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor Network

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A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor Network

  1. 1. IEEE Title:A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor NetworkModified Title:Random Coverage of Cluster in WSN using Energy aware routing protocolObjective of the project:To improve the lifetime and to maximize the energy consumption in wireless sensor networkAbstract A cluster-based wireless sensor network (WSN) where each sensor node takes turn to becluster head. The main function of the cluster head is to oversee the communication within andbetween clusters while the remaining sensor nodes are involved in sensing of the surroundingenvironment. We address the sensor utilization problem where non-cluster head nodes in acluster make decision to whether to be active and join the sensing process. The decision is basedon the remaining energy of a sensor, and a performance criterion. Here, we use the probabilitythat given point in the cluster is covered by at least N sensors. By using a probabilistic model, itcan be analytically calculated. Since only the high energy and necessary sensors are used, the Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  2. 2. energy consumption can be greatly decreased. Using energy aware routing protocol overallenergy usage and lifetime can be improved.Literature review:1. A Survey on Routing Protocols and Challenge of Holes in Wireless Sensor Networks: Extensive usage of wireless sensor networks is the reason of development of manyrouting protocols. In this paper, the working of few routing protocols has been discussed, whichare energy aware and some of them also provide reliability in data transmission. Performance ofvarious protocols has been presented through simulation results that have been reported byleading researchers for the purpose of their comparison. The challenges faced by wireless sensornetworks are also discussed in the paper. These challenges (i.e. coverage holes, routing holes,jamming holes, black/sink holes and worm holes) effect the performance of routing protocols.2. An Energy Aware Routing Protocol with Sleep Scheduling for Wireless SensorNetworks: Wireless Sensor Networks (WSNs) consist of a large number of small and low costsensor nodes powered by small batteries and equipped with various sensing devices. Usually, formany applications, once a WSN is deployed, probably in an inhospitable terrain, it is expected togather the required data for quite some time, say for years. Since each sensor node has limitedenergy, these nodes are usually put to sleep to conserve energy, and this helps to prolong the Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  3. 3. network lifetime. There are two major approaches to sleep scheduling of sensor nodes, viz. (i)random (ii) synchronized. Any sleep scheduling scheme has to ensure that data can always berouted from source to sink. In this paper, we propose a novel approach for sleep scheduling ofsensor nodes using a tree and an energy aware routing protocol which is integrated with theproposed sleep scheduling scheme. The tree is rooted at the sink node. The internal nodes of thetree remain awake and the leaf nodes are made to sleep. This provides an assured path from anynode to the sink node. The tree is periodically reconstructed considering the remaining energy ofeach node with a view to balance energy consumption of nodes, and removes any failed nodesfrom the tree. The proposed approach also considerably reduces average energy consumptionrate of each node as we are able to put more number of nodes to sleep in comparison to otherapproaches. Additional fault-tolerance is provided by keeping two paths from each node towardsthe sink. Extensive simulation studies of the proposed routing protocol has been carried out usingCastalia simulator, and its performance has been compared with that of a routing protocol, calledGSP, which incorporates sleep scheduling using random approach. The simulation results showthat the proposed approach has longer network lifetime in comparison to that provided by GSP,and the energy consumption of nodes is also balanced. Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  4. 4. 3. A QoS-geographic and energy aware routing protocol for Wireless Sensor Networks: Recent technological advances in miniaturization and wireless communication have madeWireless Sensor Networks an active research field. The increasing number of multimedia andreal-time applications for Wireless Sensor Networks has led to a growing interest in Quality ofService for this category of networks. In this paper, we propose a QoS-geographic and energyaware routing protocol for Wireless Sensor Networks. The proposed protocol performsadmission control, accounts for bandwidth requirements and considers the sensors residualenergy while taking routing decisions. The protocol also optimizes the delay of carried flows byadopting a selective forwarding approach based on sensor location.4. Distributed Deployment Schemes for Mobile Wireless Sensor Networks to EnsureMultilevel Coverage: One of the research issues in wireless sensor networks (WSNs) is how to efficientlydeploy sensors to cover an area. In this paper, we solve the k-coverage sensor deploymentproblem to achieve multi-level coverage of an area I. We consider two sub-problems: k-coverageplacement and distributed dispatch problems. The placement problem asks how to determine theminimum number of sensors required and their locations in I to guarantee that I is k-covered andthe network is connected; the dispatch problem asks how to schedule mobile sensors to move tothe designated locations according to the result computed by the placement strategy such that theenergy consumption due to movement is minimized. Our solutions to the placement problem Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  5. 5. consider both the binary and probabilistic sensing models, and allow an arbitrary relationshipbetween the communication distance and sensing distance of sensors. For the dispatch problem,we propose a competition-based and a pattern-based schemes. The former allows mobile sensorsto bid for their closest locations, while the latter allows sensors to derive the target locations ontheir own. Our proposed schemes are efficient in terms of the number of sensors required and aredistributed in nature. Simulation results are presented to verify their effectiveness.5. Random coverage with guaranteed connectivity: joint scheduling for wireless sensornetworks: Sensor scheduling plays a critical role for energy efficiency of wireless sensor networks.Traditional methods for sensor scheduling use either sensing coverage or network connectivity,but rarely both. In this paper, we deal with a challenging task: without accurate locationinformation, how do we schedule sensor nodes to save energy and meet both constraints ofsensing coverage and network connectivity? Our approach utilizes an integrated method thatprovides statistical sensing coverage and guaranteed network connectivity. We use randomscheduling for sensing coverage and then turn on extra sensor nodes, if necessary, for networkconnectivity. Our method is totally distributed, is able to dynamically adjust sensing coveragewith guaranteed network connectivity, and is resilient to time asynchrony. We present analyticalresults to disclose the relationship among node density, scheduling parameters, coverage quality, Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  6. 6. detection probability, and detection delay. Analytical and simulation results demonstrate theeffectiveness of our joint scheduling methodSYSTEM ANALYSES:Existing System:Source Dependent Broadcasting ProtocolsProposed System: A broadcasting node uses existing source dependent broadcasting protocols to select a set of forwarding nodes to cover all its 2-hop neighbors. Then, it adjusts its transmission power to reach its furthest forwarding node. The node determines whether its current forwarding nodes as well as transmission power are able to cover all its immediate neighbors. If yes, it continues to broadcast the message. Otherwise, it attempts to find additional forwarding nodes to reach those uncovered neighbors or simply extends its current transmission power to reach the furthest uncovered neighbor. Variable Transmission Power Protocols. Power law model Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  7. 7. o Precv = Ptx / rn Enhanced PABLO Enhanced Inside-Out Power Adaptive Approach (E-INOP)Algorithm :Dominant Pruning (DP) Protocol : The earliest deterministic broadcasting protocols. A node that receives a broadcastmessage from source node and selects a minimum number of forwarding nodes from Network tocover all nodes. The greedy algorithm is adopted to select forwarding nodes from the network tocover all nodes.1) Node v establishes the set B(u; v) and U(u; v) using N(N(v)), N(u), and N(v): U(u; v) = N(N(v)) �N(u) � N(v) B(u; v) = N(v) � N(u) Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  8. 8. 2) Node v then executes the greedy algorithm to select forwarding nodes from B(u; v) to coverall nodes in U(u; v).Total Dominant Pruning (TDP) Protocol TDP is more effective than DP in reducing redundant broadcasting but it incursadditional overhead in piggybacking each data message with a list of 2-hop neighbors of thesenders.The TDP algorithm is: 1) Node v establishes the set B(u; v) and U(u; v) using N(N(v)) and N(N(u)): U(u; v) = N(N(v)) �N(N(u)) B(u; v) = N(v) �N(u) 2) Node v then executes the greedy algorithm to select forwarding nodes from B(u; v) tocover all nodes in U(u; v).Partial Dominant Pruning (PDP) Protocol PDP algorithm does not require additional overhead, like TDP. Instead of just excludingnodes in network. the 2-hop neighbor set to be covered. Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com
  9. 9. The PDP algorithm is summarized below:1) Node v establishes the set B(u; v) and U(u; v) using N(N(v)), N(u), N(v), and N(N(u) N(v)): U(u; v) = N(N(v))�N(u)�N(v)�N(N(u)N(v)) B(u; v) = N(v) � N(u)2) Node v then executes the greedy algorithm to select forwarding nodes from B(u; v) to coverall nodes in U(u; v). Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com

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