Review Article

Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review

Table 1

Previous survey of wireless sensor localization.

ReferenceTaxonomy Comparison parametersYears

[18]APIT, DV-hop, multihop, centroid, gradientNode density, cost, accuracy, overhead, scalability2015
[27]Types of sensors, types of mobility, measurement errorsLocation accuracy, deployment cost, location context, quality and cost of smartphone, and measurement errors2015
[28]Static landmark and static node, mobile landmark and static node, static landmark and mobile node, mobile landmark and mobile nodeLocalization accuracy, coverage, time, landmark density, node density, energy consumption2013
[29]Static (range-free, range-based), mobile (robotic, MCL, range-based)(Centralized, distributed), dimensional analysis, simulator, (range-free, range-based), scalability, communication radius2013
[30](range-based, range-free), (anchor-based, anchor-free), (distributed, centralized)accuracy, hardware cost, computation cost, and communication cost2012
[31]Geometrical techniques, multidimensional scaling, stochastic proximity embedding convex, and nonconvex optimization and hybridAccuracy, coverage, complexity, scalability, robustness, and cost2012
[32]Proximity-based localization, one-hop localization and multihop localizationWithout comprehensive comparison2012
[33]Target/source localization and node self-localizationNon-line-of-sight, energy-constrained network, tradeoff between localization performance and energy consumption, cooperative node localization, and localization in heterogeneous network2012
[16]Beacon-based distributed localization, relaxation-based distributed localization, the Coordinate system stitching-based localization, and hybrid localizationObjective (centralized, distrusted), description, accuracy, computation cost2010
ProposedRange-based, range-free, and hybrid. Range-free (localization accuracy, communication cost, and computation cost)Velocity, anchor and normal node density, degree of irregularity, size of sample area, number of messages, and message size 2016