Stochastic Routing in Wireless Sensor Networks

Sivrikaya, Fikret; Geithner, Thomas; Truong, Cuong; Khan, Manzoor Ahmed; Albayrak, Şahin

doi:10.1109/iccw.2009.5208012

Cited by 16 publications

(12 citation statements)

References 11 publications

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“…Probabilistic Geographic Routing (PGR) proposed in [5] assigns probabilities to each candidate node using residual energy and backward link reliability. Distributed Heuristic Algorithm (DHA) [6] assigns forwarding probabilities to the sender's neighbor nodes according to the distance between the sender and the sink, the maximum distance between the sender and each of its neighbor nodes as well as the distance between each neighbor node and the sink. The probability assignment scheme in DHA changes as packets get closer to the sink while in PGR the probability assignment is uniform along the routing path.…”

Section: Related Workmentioning

confidence: 99%

FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks

Liu

Wang

Hawbani

et al. 2020

IEEE Trans. on Mobile Comput.

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In wireless sensor networks, routing protocols with immutable network policies lacking the flexibility are generally incapable of maintaining effective performance due to the complicated and rapidly changing environment situations and application requirements. The proposed "Flexible Routing Computing Approach (FRCA)" is a novel distributed and probabilistic computing approach capable of modifying or upgrading routing policies on the fly with low cost, which effectively enhances the routing flexibility. FRCA models the routing metric as a forwarding probability distribution for routing decisions. This model depends on three elements, the physical quantities collected at sensor nodes, the built-in base math functions, and the routing parameters. These elements are all user-oriented and can be specified to implement multifarious complicated network policies meeting different performance requirements. More significantly, through distributing routing parameters from the sink to end nodes, operators are allowed to adjust network policies on the fly without interrupting the network services. Through extensive performance evaluation studies and simulations, the results demonstrate that routing protocols designed based on FRCA could achieve better performance compared to its state-of-the-art counterparts regarding network lifetime, energy consumption, and duplicate packets as well as ensure high flexibility during network policies modification or upgrade.

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Section: Related Workmentioning

confidence: 99%

FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks

Liu

Wang

Hawbani

et al. 2020

IEEE Trans. on Mobile Comput.

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“…Distributed Heuristic Algorithm (DHA) was presented in [30]. DHA is a probabilistic scheme based on three distances parameters to select the forwarder nodes, the distance between the sender node and the sink, the distance between the forwarder node and the sink, and the maximum distance between the sender node and the sink.…”

Section: Related Workmentioning

confidence: 99%

“…This may cause quick energy depletion, which can result in the loss of some nodes and a loss of part of the network.In [28], the authors proposed a probabilistic scheme based on the node degree and link loss to increase the reliability of selective forwarding. The authors in [29] presented a Probabilistic Geographic Routing (PGR) that uses only local information, link reliability, and residual energy to probabilistically forward data after selecting a candidate's nodes and assigning these probabilities to these candidates.Distributed Heuristic Algorithm (DHA) was presented in [30]. DHA is a probabilistic scheme based on three distances parameters to select the forwarder nodes, the distance between the sender node and the sink, the distance between the forwarder node and the sink, and the maximum distance between the sender node and the sink.…”

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confidence: 99%

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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“…In the unicast mode, if a sensor operates correctly, it must choose only one of its neighbour sensors to send packets. The chosen probabilities are different and defined as routing probabilities [17]. This research assumes that routing probability of each sensor has been specified initially.…”

Section: Probabilistic Wireless Sensor Networkmentioning

confidence: 99%

Probabilistic Congestion of Wireless Sensor Networks: a Coloured Petri Net based Approach

Le¹,

Cao²,

Phuc³

et al. 2017

CAE

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Analysing probability properties on Coloured Petri Nets (CPNs) model is one of a favorite topic on system verification recently. This paper focuses on verifying congestion probability on Wireless Sensor Networks (WSNs) which is modelled by CPN. Actually, WSNs are the collection of sensors. A WSN topology is formed by the interaction among sensors via Wi-Fi connections. However, sensors can be consider as unsteady devices when working in the harsh environment due to limited processing capacity, non-replacement battery, etc. Hence, each sensor needs to attach a reliable probability so that users can know the probability of reaching the sink of data. Such probabilities are added into the transitions in our CPN probability model before checking congestion. Whole verifying process introduces also in order to emphasize the purpose of this paper via a straight example.

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Stochastic Routing in Wireless Sensor Networks

Cited by 16 publications

References 11 publications

FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks

FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks

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

Probabilistic Congestion of Wireless Sensor Networks: a Coloured Petri Net based Approach

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