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

Kumar, Arun; Shwe, Hnin Yu; Wong, Kai Juan; Chong, Peter Han Joo

doi:10.4236/wsn.2017.91003

Cited by 74 publications

(26 citation statements)

References 85 publications

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“…The candidate parents for n np CP np are a set of neighboring nodes of n np , such that they satisfy the conditions (1,2), such that: ∀ n i ∈ N np , ∃n p ∈ CP np 1.…”

Section: Definitionmentioning

confidence: 99%

“…Second, each node must be aware of its direct neighbor node's location. Third, the source node must be aware of the destination node's location [1]. The localization of WSNs is a very crucial issue; many methods have been proposed to get the node's location, and most of these proposed methods supposed that only a small proportion of sensor nodes, called anchor (beacon) nodes, are location-aware through a global positioning system (GPS), because of the high cost and energy consumption of GPS.…”

Section: Introductionmentioning

confidence: 99%

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PDTR: Probabilistic and Deterministic Tree-based Routing for Wireless Sensor Networks

Ghoul

Djaidja

et al. 2020

Sensors

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This paper proposed a "Probabilistic and Deterministic Tree-based Routing for WSNs (PDTR)". The PDTR builds a tree from the leaves to the head (sink), according to the best elements in the initial probabilistic routing table, measured by the product of hops-count distribution, and transmission distance distribution, to select the best tree-paths. Each sender node forwards the received data to the next hop via the deterministic built tree. After that, when any node loses of its energy, PDTR updates the tree at that node. This update links probabilistically one of that node's children to a new parent, according to the updated probabilistic routing table, measured by the product of the updated: Hops-count distribution, transmission distance distribution, and residual energy distribution at the loss of e energy. By implementing the control parameters in each distribution, PDTR shows the impact of each distribution in the routing path. These control parameters are oriented by the user for different performances. The simulation results prove that selecting the initial best paths to root the packets via unicast, then improving the tree at the node with loss of energy by rooting the packets via anycast, leads to better performance in terms of energy consumption and network lifetime. of 22positions, through other localization technologies [2,3]. Other proposed WSN localization technologies are based on different measurement techniques such as the time-of-arrival (TOA), angle-of-arrival (AOA), and received signal strength indicator (RSSI) [4][5][6][7]. Later,in [8,9], the cooperative localization technology was developed for hybrid networks containing mobile and static sensors. Recently,in [10], the authors proposed a centralized expectation maximization-based passive localization technology for asynchronous receivers (EMplLaR). Being aware of the nodes' location allows the use of many power control techniques to reduce energy consumption.Data forwarding toward the sink via deterministic protocols may cause quick energy depletion for some nodes, due to the sender node's forwarder unique choice, which causes a topology disruption, thus a quick network death. Meanwhile, the probabilistic routing approach came with the improvement, such that each sensor has to select its forwarder from a set of its candidates according to their routing probabilities, based on its neighborhood knowledge, thus providing a longer network lifetime.From the existing probabilistic and deterministic protocols, we concluded that to minimize the energy consumption and prolong the network lifetime, the protocol should depend on three factors. Reference [11] proposed a Hop-based Routing Protocol based on an Energy Efficient Minimum Spanning Tree for WSN. From the simulation results, it was proved that the proposed protocol improved the network in terms of energy consumption and lifetime extension, hence the importance of the hop-count factor. Article [12] also considered this factor in the presented protocol called (STDD). The authors in [13] showed tha...

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“…The candidate parents for n np CP np are a set of neighboring nodes of n np , such that they satisfy the conditions (1,2), such that: ∀ n i ∈ N np , ∃n p ∈ CP np 1.…”

Section: Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

PDTR: Probabilistic and Deterministic Tree-based Routing for Wireless Sensor Networks

Ghoul

Djaidja

et al. 2020

Sensors

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“…These protocols include Flooding [12], Voronoi (Voronoi diagram based geo-casting protocol) [12], LBM (Location-Based Multicast) [13], GAMER (Geocast Adaptive Mesh Environment for Routing) [14]. Geo-GRID [15], URAD (Unicast Routing with Area Delivery) [16] and TORA (Temporally Ordered Routing Algorithm) [17].…”

Section: Geocast Protocolsmentioning

confidence: 99%

Hybrid Geo-Location Routing Protocol for Indoor and Outdoor Positioning Applications

Mushtaq¹,

Alandjani²,

Abbasi³

et al. 2019

IJACSA

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Internet of Things (IoT) essentially demands smart connectivity and contextual awareness of current networks with low power and cost effective wireless solutions. Routing is the backbone of the system controlling the flow of transmission. This work demonstrates a collation between performance investigations of a location-based routing protocol Geocast Adaptive Mesh Environment for Routing with contextual information collected from Global Positioning System (GPS) and Framework for Internal Navigation and Discovery (FIND) respectively. The systems are evaluated based on various metrics i.e. Accuracy, Packet Delivery Ratio and Packet Overhead by means of Network Simulator (NS-2). FIND shows enhanced performance in most cases as compared to GPS for indoor and outdoor environments. The results of this research can be deployed in different areas such as in-building navigation, hospital patient tracking, Smart City context aware service provisioning and Industry 4.0 deployments.

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“…The authors in [36] developed an energy efficient cluster based routing protocol that considers both the network topology and current energy levels of the sensor nodes. The protocol makes the sensor network scalable by assigning unique Identification Number (ID) to each of the sensor nodes which helps in reducing the communication overhead and thereby increasing the network lifetime.…”

Section: Energy Efficient Clustering Scheme With Self-organized Id Asmentioning

confidence: 99%

Clustering Algorithms of Wireless Sensor Networks: A Survey

Riaz¹

2018

IJWMT

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In the recent few years the research on Wireless Sensor Networks (WSN) and its variants have risen enormously. The researchers all across the globe are trying to develop a routing protocol that is energy efficient and provides adequate security level in data communication. One of the techniques the researchers use is Clustering of the sensor network. This technique inherently consumes less energy during data communication as the nodes have assigned a dedicated task to perform. A total of 35 clustering algorithms / protocols have been surveyed and comparison of these protocols based on the metrics like heterogeneity, clustering method, size of the cluster etc. have been presented. 42Clustering Algorithms of Wireless Sensor Networks: A Survey Clustering Algorithms' & Protocols For WSNThe WSN algorithms and protocols can be categorized in several different ways. In this paper we have categorized the clustering algorithms / protocols of WSN on the basis of probabilistic and non-probabilistic protocols and are described below: A. Probabilistic ProtocolsIn probability based clustered routing protocols each sensor node at the time of deployment is assigned with probability that how often that sensor node will likely to be selected as CH during the CH election process. The assigned probability of the senor node serves as the basic criterion for CH selection.The WSN algorithms and protocols are described below: Low Energy Adaptive Cluster Hierarchical (LEACH) ProtocolThe authors in [8] proposed a well-known cluster centered routing protocol known as Low Energy Adaptive Cluster Hierarchical (LEACH) routing protocol. In LEACH after every round the energy level of the current Cluster Head (CH) is checked and if its energy is drained and below the threshold value then based on the probabilistic theory new CH will be selected. The responsibilities of the CH are to be rotated or shared among the sensor nodes of the network. This rotation of CH responsibility stabilizes the consumption of energy of network nodes such that no node will be overwhelmed. Stable Election Protocol (SEP)Temporary-DEEC Clustering Algorithms of Wireless Sensor Networks: A Survey 45 The authors in [21] developed a protocol that is multilevel clustering protocol explicitly designed for heterogeneous WSNs. In this protocol, a procedure for the selection of CH is established on the ratio of remaining energy of the sensor node which is being evaluated for the role of CH with that of the average network energy. In this protocol the authors have initially considered two levels of energy and three levels i.e. the nodes distributed in the sensor network are of two / three energy levels or possess different amounts of energy. Later on, a generic solution for multi-level energy level solution was figured out. Each node of the network must have knowledge of energy levels of all the nodes present in sensor network. For CH select the average network energy is required that is inherently more energy consuming. This protocol forms the varying number of clusters after...

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

Cited by 74 publications

References 85 publications

PDTR: Probabilistic and Deterministic Tree-based Routing for Wireless Sensor Networks

PDTR: Probabilistic and Deterministic Tree-based Routing for Wireless Sensor Networks

Hybrid Geo-Location Routing Protocol for Indoor and Outdoor Positioning Applications

Clustering Algorithms of Wireless Sensor Networks: A Survey

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