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Target tracking is crucial to many applications in wireless sensor networks (WSNs). Existing tracking schemes used in WSNs can basically be classified two categories, clustering and predicting. Considering network clustering consumes much energy for limited-energy WSNs, a predicting target tracking scheme is proposed called MC-MPMC (measurement compensation-based mixture population Monte Carlo) which tracks the target based on predicted locations in this work. Adaptive mixture PMC model for generating proposals varying from each iteration is proposed to guarantee sampling diversity. And also, extra measurements or observations generating method is introduced to compensate missed prediction locations or false estimations, avoiding tracking behavior degradation. Firstly, samples drawn from the proposals of next iteration can be generated by a mixture method to avoid sample degeneracy. Secondly, sample weights are jointly computed based on adaptive fusion of compensation measurement and true measurements. Thirdly, HTC method is combined to MC-MPMC scheme to decrease energy consumption in WSNs. Then, the proposed method is verified through comprehensive experiments about tracking error, delay and consumption predictions. Moreover, performance comparisons of MC-MPMC with other tracking schemes are also proposed. [ABSTRACT FROM AUTHOR]

Localization is crucial to many applications in wireless sensor networks (WSNs) because measurement data or information exchanges happened in WSNs without location information are meaningless. Most localization schemes for mobile WSNs are based on Sequential Monte Carlo (SMC) algorithm. These SMC-based methods often suffer from too many iterations, sample impoverishment and less sample diversity, which leads to low sampling and filtering efficiency, and consequently low localization accuracy and high localization costs. In this paper, we propose an improved range-free localization scheme for mobile WSNs based on improved Population Monte Carlo localization (PMCL) method, accompanying with Hidden Terminal Couple scheme. A population of probability density functions is proposed to approximate the distribution of unknown locations based on a set of observations through an iterative importance sampling procedure. Behaviors are enhanced by adopting three improved methods to increase accuracy, enhance delay and save cost. Firstly, resampling, with importance weights, is introduced in PMCL method to avoid sample degeneracy. Secondly, twofold constraints, constraining the number of random samples in initialized step and constraining valid observations in resampling step, are proposed to decrease the number of iterations. Thirdly, mixture perspective is introduced to maintain the diversity of samples in resampling weighted process. Then, localization error, delay and consumption, especial delay, are predicted based on the statistic point of view, which takes mobile model of RWP into account. Moreover, performance comparisons of PMCL with other SMC-based schemes are also proposed. Simulation results show that delay of PMCL has some superiorities to that of other schemes, and accuracy and energy consumption is improved in some cases of less anchor rate and lower mobile velocity. [ABSTRACT FROM AUTHOR]

Since the successful release of the IEEE 802.15.4 standard, a great convenience is offered to applications in low-power and low-rate wireless sensor networks (WSNs) which almost touch upon all aspects in our surrounding circumstances. For time-critical applications, we use a modified Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) mechanism called Linear Increase Backoff (LIB) to enhance the performance of packet delay, but not compromise the metrics of energy efficiency and throughput. An accurate and comprehensive Markov model is used to analyze the characteristics of our LIB scheme predicting packet delay, energy consumption and throughput of unsaturated, unacknowledged IEEE 802.15.4 networks in which the unsaturated state is dependent on the traffic condition rather than the depiction by a predetermined length. Simulation results are consistent with the predictions of this model. We also compare the performance of LIB with that of several mechanisms according to the optimal parameters selected from operating point, and find that packet delay is obviously superior to that of other schemes, while energy efficiency and throughput are superior to others for large number of nodes and high traffic arrivals. [ABSTRACT FROM AUTHOR]

With the hasteful development of ocean economy and the increasing exploiture of ocean resources, offshore water is contaminated seriously. Ocean ecological environment is unprecedentedly faced to threat and destruction. Moreover, the desire for aquatic and marine products is increasing consumedly according to people’s health attention rising. It is extremely urgent to establish and maintain low-cost and high-efficient transmission and localization schemes for real-time large-scale aquaculture surveillance systems. Localization scheme IMDV-hop (Intermittent Mobile DV-hop) embedded in WLS (weighted least square) method, accompanying with HTC (Hidden Terminal Couple), is proposed in this work for the purpose of environment surveillance, object localization for early warning, rescue operations, and restructuring plan, etc. Two critical parameters, correction coefficient kc and weighted coefficient wNx,i, are introduced into IMDV-hop scheme for large-scale aquaculture monitoring and localization mobile sensor systems to evaluate the influence on localization behaviors, and subsequently guarantee localization accuracy and time-critical performance. And localization error, delay, and consumption are predicted by comprehensive NS-2 simulations. Besides, performance comparisons of IMDV-hop scheme with other DV-hop-based schemes and MCL-based scheme are also proposed. Analysis and comparison results show that delay behavior of IMDV-hop is improved largely relative to other schemes, while accuracy and energy consumption performance is improved in some cases of more node density and lower mobile velocity. [ABSTRACT FROM AUTHOR]