Adaptive routing in wireless sensor networks: QoS optimisation for enhanced application performance

Hammoudeh, Mohammad; Newman, Robert

doi:10.1016/j.inffus.2013.02.005

Cited by 141 publications

(73 citation statements)

References 19 publications

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“…The HCRAFM is very accurate and effective in handling the fuzzy issues that are hard to quantify [5]. In view of the difficulties in quantify the qualitative variables of WSN with mathematical language, the robustness of the network was roughly categorized into four levels in the evaluation: extra-high, high, middle and low.…”

Section: Overviewmentioning

confidence: 99%

“…The algorithm divides the network nodes into several clusters according to certain rules, such that each cluster contains a cluster head and a plurality of member nodes [4]. The overall closeness between cluster head and member nodes serves as the hallmark feature of the corresponding cluster [5]. The cluster head is selected from all nodes in the cluster by evaluating the residual energy of each node.…”

Section: Introductionmentioning

confidence: 99%

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Routing Algorithm of Wireless Sensor Network and Robustness Analysis Based on Fuzzy Mathematics

et al. 2017

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Abstract-In order to reduce the energy consumption and enhance the robustness of wireless sensor network (WSN), this paper proposes a hierarchical clustering routing algorithm based on fuzzy mathematics (HCRAFM). To make a comprehensive analysis of WSN, it is also necessary to detect the robustness of the network. Facing the multiple random variables, the traditional robustness detection models assume that all nodes have the same weight, making it impossible to quantify the analysis indices or obtain accurate results. Thus, the fuzzy mathematics theory was introduced to the WSN robustness detection, forming a fuzzy comprehensive evaluation method. The simulation results show that the HCRAFM strikes a load balance between WSN nodes, extends the life cycle of each node, and prolongs the service life of the network. In addition, the proposed algorithm is proved to have sound robustness and strong applicability. Keywords-Routing Algorithms; Robustness Analysis; Wireless Sensor Network (WSN); Fuzzy Mathematics IntroductionIn wireless sensor network (WSN), the routing algorithm is responsible for setting up the path and mechanism of data transmission, realizing the dynamical update of network topology, and maintaining the information of network routing [1]. Therefore, the algorithm must be able to improve the energy efficiency of WSN nodes, and provide high quality services [2]. The traditional routing algorithms cannot satisfy the demand of WSN, which carries numerous different features from those of traditional networks. This calls for the design of a routing algorithm targeted at the demand of WSN [3]. The structure of a typical WSN is presented in Figure 1.

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Section: Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Routing Algorithm of Wireless Sensor Network and Robustness Analysis Based on Fuzzy Mathematics

et al. 2017

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“…Mohammad Hammoudeh et al [8] proposed the development of routing protocols with provide service assurance application-specific. They present the Route Optimization and Load-balancing protocol that is ROL, which uses a variety of Quality of Service (QoS) metrics.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network

Abror

Widodo

Rasyid

2018

emitter

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NO and CO. In WSN, node system is constrained to a limited power supply, so that the node system has a lifetime. To doing lifetime maximization, power management scheme is required and sensor nodes should use energy efficiently. This paper proposes dynamic sleep scheduling using Time Category-Fuzzy Logic (TimeFuzzy) Scheduling as a reference for calculating time interval for sleep and activated node system to support power management scheme. This research contributed in power management design to be applied to the WSN system to reduce energy expenditure. From the test result in real hardware node system, it can be seen that Time-Fuzzy Scheduling is better in terms of using the battery and it is better in terms of energy consumption too because it is more efficient 51.85% when it is compared with Fuzzy Scheduling, it is more efficient 68.81% when it is compared with Standard Scheduling and it is more efficient 85.03% when compared with No Scheduling.

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“…Therefore, there is a considerable problem how the routing algorithm decreases the influence of packet loss rate in the industrial communication. Some routing algorithms were proposed to solve the problem [2][3][4][5][6][7][8][9][10][11][12]. Most proposed algorithms focus on the choice of the shortest path based on the multi-restriction conditions.…”

Section: Introductionmentioning

confidence: 99%

Multipath Routing Scheme for Industrial Real-time Wireless Sensor Networks

Wang³

et al. 2017

Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

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Abstract-In the industrial scenes, the real-time property has to be considered in the data transmission. A novel routing scheme is proposed to reduce the packet loss rate effectively in the industrial wireless sensor networks. The scheme is based on Bellman-Ford algorithm, and saves some other shorter paths for the multipath transmission. According to different requirements of QoS in data transferring, the scheme can use more than one path to send the same packet synchronously. Moreover, the scheme use a unique label to mark every packet to assure that the receiver can discard the same packet from different path after a packet arrives in the receiver. Therefore, this scheme can reduce the probability of packet retransmission, and enhance the real-time property in the industrial wireless sensor networks.

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Adaptive routing in wireless sensor networks: QoS optimisation for enhanced application performance

Cited by 141 publications

References 19 publications

Routing Algorithm of Wireless Sensor Network and Robustness Analysis Based on Fuzzy Mathematics

Routing Algorithm of Wireless Sensor Network and Robustness Analysis Based on Fuzzy Mathematics

Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network

Multipath Routing Scheme for Industrial Real-time Wireless Sensor Networks

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