Barrier Coverage For Wireless Sensor Network

Wireless sensor network (WSN) is a special self-organized ad-hoc networkconsisting of a number of tiny sensor devices with low processing power, lowcommunication capacity, and limited buffer capacity. Each device has sensing,processing and wireless communication capabilities, which enable it to gather usefulinformation about the environment, to generate report messages and deliver messagesto the base station. Wireless sensor networks widely used in military, industrial, civil,etc. is currently an active research area. Sensing coverage is one of the fundamentalproblems in wireless sensor networks, which reflects the quality of service (QoS) ofmonitoring provided by the entire sensor network. Space resources of wireless sensornetwork can be optimized allocation by coverage. This dissertation focuses on thebarrier coverage based on monitoring (wireless sensor network) and anti-monitoring(moving target) in wireless sensor network. The former is to address how to cover themoving target, while the latter is to consider how to provide better QoS of monitoring.The major contributions of the dissertation are as follows:(1) Firstly, based on anti-monitoring, the moving target subjected to traversal timeconstraint how to across enemy sensor networks field was studied. The most existingtraversal algorithms based on breadth-first-search are difficulty to satisfy apre-determined time constraint value. Motivated by this reason, a traversal model isconstructed and a heuristic approximately optimization algorithm (kSP-LAHTP) isproposed in this dissertation. The algorithm makes the continuous path problemdomain to a discrete one by Voronoi diagram. By using exposure and traversal time asthe path (trajectory) performance metric, the algorithm combines the linear aggregatedrouting mechanism to find the optimal path. It makes the moving target can traversethe enemy sensor networks field. And the traversal time from the source to thedestination is less a given threshold. Theoretically and experimentally, it is concludedthat the proposed algorithm is able to solve the traversal path problem with timeconstraint. The proposed algorithm (kSP-LAHTP) is able to find a traversal path closerto the optimum with parameter k increasing.(2) Secondly, the moving target subjected to trajectory length constraint how toacross the enemy sensor networks field was studied. In practical applications, due tosome majeure reasons (such as: energy consumption), the target must take into account the length of the trajectory, because long trajectory will undoubtedly consume moreresources. When target move forward with uniform speed, the trajectory length cantranslate into time. When target move forward with uneven speed, the trajectory lengthcan’t translate into time. Thus we can’t search the trajectory with length constraint bythe kSP-LAHTP algorithm. For the reason, utilizing grid and label setting routingmechanism, an approximate optimization approach was proposed for finding traversaltrajectory of target. The algorithm can calculate the approximate optimal trajectory ofintelligent target with a constraint on the trajectory length, where the trajectory lengthfrom start to destination is less than special threshold. Theoretical analysis andextensive experiments results show that the proposed scheme is able to find theapproximate minimal exposure trajectory with constraints and improve accuracy of thetrajectory by increase order of grid.(3) The issue on how to achieve weak barrier coverage based on directionalsensing model was studied in the dissertation. At present, most of the existing weakbarrier coverage schemes are based on omni-directional sensing model. However, itcan be known that only a sector of sensing region is required to construct barrier.Therefore, omni-directional sensing model will result in waste of energy formaintaining the sensing capability over the remainder of the sensing region. Motivatedby the reason, based on directional sensing model, we analysis the probability of thesensor network successfully accomplished weak barrier coverage and the probability ofthe gap is less than size of the target. And we propose a weak barrier coverage heuristicalgorithm. The algorithm translate the weak barrier coverage problem into linecoverage problem by projecting sensors’ coverage regions on boundary of region,while the barrier can exist the gaps which smaller than a given size. The performanceof the proposed scheme was evaluated and compared with that of the omni-directionalsensing scheme. The results show that the proposed directional sensing schemeachieved weak barrier coverage is better than the omni-directional sensing scheme, andthe number of activated node will decrease with size of target increasing.(4) The issue on the (strong) barrier coverage based on data fusion was studied.Wireless sensor networks usually construct barrier coverage for detecting travel targetwhen sensor random development in a belt region. And sensors scheduling algorithm isused to alleviate the energy limitation problem of sensor in sensor networks. However,most of current researches are based on disk sensing model, and don’t consider thecollaboration between sensor nodes, which will result in waste of sensor nodes.Therefore, in this paper, based on probabilistic sensing model, we construct virtual sensor by information fusion scheme that fuse sensing measurements of two sensors,which can significantly improve coverage region. Based on the theories, a barriercoverage preserving configuration algorithm is proposed. The algorithm providescontinuous barrier coverage for the whole region by divide-and-conquer approach,which can reduce the communication overhead. Moreover, the redundancy nodes arescheduled to sleep for reducing energy consumption and prolonging the networklifetime. Analysis and experiment results show that the algorithm outperforms thebarrier coverage preserving configuration scheme based on information non-fusionsensor, on the number of barrier and network lifetime, etc.(5) Finally, the issue on k-connected barrier coverage based on probability modelwas studied. Barrier coverage and network connectivity are two important properties ofwireless sensor networks deployed in belt region. However, most of the previousworks addressed only one kind of the two issues: coverage or connectivity alone.Moreover, many previous works on coverage and connectivity are based on the diskmodel, which can’t fully utilize the sensing and communication capacity of sensors.For these reasons, we analysis the relationship between barrier coverage and s-tconnectivity and proposed a distributed algorithm (k-CBC) for maintaining bothk-barrier coverage and s-t connectivity (refer to as k-connected barrier coverage) underprobabilistic model. The proposed algorithm is more suitable for real environmentsthan other protocols that assume sensing and communication regions (ranges) are diskswith a fixed radius around sensors. The performance of the proposed scheme wasevaluated and compared with other schemes. Compared with other algorithm based ondisk model, our scheme can provide the controllable quality of k-connected barriercoverage and the number of active nodes by detection probability threshold, falsealarm probability threshold, and packet deliver rate threshold.In summary, our goal is improve the barrier coverage performance and enhancingthe quality of barrier coverage. This dissertation studies the barrier coverage based onanti-monitoring and monitoring respectively, which has practical value and theoreticalsignificance for advancing the research and practicability of barrier coverage.