Geographic Routing Resilient to Location Errors

Abstract

Abstract-Geographic routing is an attractive option for large scale wireless sensor networks (WSNs) because of its low overhead and energy expenditure, but is inefficient in realistic localization conditions. Positioning systems are inevitably imprecise because of inexact range measurements and location errors lead to poor performance of geographic routing in terms of packet delivery ratio (PDR) and energy efficiency. This paper proposes a novel, low-complexity, error-resilient geographic routing method, named conditioned mean square error ratio (CMSER) routing, intended to efficiently make use of existing network information and to successfully route packets when localization is inaccurate. Next hop selection is based on the largest distance to destination (minimizing the number of forwarding hops) and on the smallest estimated error figure associated with the measured neighbor coordinates. It is found that CMSER outperforms other basic greedy forwarding techniques employed by algorithms such as most forward within range (MFR), maximum expectation progress (MEP) and least expected distance (LED). Simulation results show that the throughput for CMSER is higher than for other methods, additionally it also reduces the energy wasted on lost packets by keeping their routing paths short.

Location-Based Routing Protocols for Wireless Sensor Networks: A Survey

“…The energy conditioned mean square error algorithm (ECMSE) [96] is the extension work of a similar energy-optimal forwarding choice in the case of the error-robust (CMSER) algorithm [97] and adopts the theoretical energy model [98]. ECMSE is designed for WSN applications in need of efficient, location error-coping geographic routing.…”

Location error resilient geographical routing for vehicular ad‐hoc networks

“…While taking routing decisions, MER considers error probability and the information of the nodes near the border of the transmission range of the transmitting node. The conditioned mean square error ratio (CMSER) routing decision is based on the largest distance to destination, and on the smallest statistical error characteristic associated with the measured candidate nodes coordinates [24]. The energy constrained mean square error (ECMSE) [25] algorithm is an extension of CMSER.…”

“…However, a GPS receiver has some inherent localization error, up to ±10 to 30݉ [13]. The probability distribution of location error is taken as Gaussian, similar to the models in [23], [24]. In a two dimensional plane, let a relay vehicle ܸ have the true location ܸ ‫ݔ(‬ , ‫ݕ‬ ) and the estimated location ܸ ‫ݔ(‬ ᇱ , ‫ݕ‬ ᇱ ) where ‫ݔ‬ ᇱ = ‫ݔ‬ + ߝ , ‫ݕ‬ ᇱ = ‫ݕ‬ + ߝ .…”

“…After obtaining the information about neighbouring vehicles, source vehicle ܸ creates its routing table, and evaluates objective function associated with each neighbouring vehicle ܸ as expressed by (24) ‫ܨܱ‬ = ‫ܼ‪൫‬ܧܵܯ‬ መ ൯ * ܻ (24) where, ܻ represents the distance between ܸ and the destination vehicle. The source vehicle ܸ selects a neighbour vehicle as NFV (ܸ ேி ) with minimum ‫ܨܱ‬ .…”

Energy Efficient Geographic Routing Robust Against Location Errors

“…The present work aims to minimize such a tradeoff and to facilitate a higher packet delivery ratio (PDR) than similar geographic routing techniques, while still being energy efficient. This is achieved through a novel proposal entitled energy conditioned mean square error algorithm (ECMSE) which, similarly to the forwarding method in [5], makes use of statistical assumptions of Gaussianly distributed location error and Ricianly distributed distances between sensor nodes. In addition it makes use of an energy efficient feature proposed by [3], which includes information about the energy cost of the forwarding decision.…”