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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]

Studies of the IEEE 802.15.4 Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) scheme have been received considerable attention recently, with most of these studies focusing on homogeneous or saturated traffic. Two novel transmission schemes-OSTS/BSTS (One Service a Time Scheme/Bulk Service a Time Scheme)-are proposed in this paper to improve the behaviors of time-critical buffered networks with heterogeneous unsaturated traffic. First, we propose a model which contains two modified semi-Markov chains and a macro-Markov chain combined with the theory of M/G/1/K queues to evaluate the characteristics of these two improved CSMA/CA schemes, in which traffic arrivals and accessing packets are bestowed with non-preemptive priority over each other, instead of prioritization. Then, throughput, packet delay and energy consumption of unsaturated, unacknowledged IEEE 802.15.4 beacon-enabled networks are predicted based on the overall point of view which takes the dependent interactions of different types of nodes into account. Moreover, performance comparisons of these two schemes with other non-priority schemes are also proposed. Analysis and simulation results show that delay and fairness of our schemes are superior to those of other schemes, while throughput and energy efficiency are superior to others in more heterogeneous situations. Comprehensive simulations demonstrate that the analysis results of these models match well with the simulation results. [ABSTRACT FROM AUTHOR]