Optimization of Wireless Sensor Networks inspired by Small World Phenomenon

Kumar, Mithilesh; Pattanaik, K. K.; Yadav, Brijendra Singh; Verma, Rahul Kumar

doi:10.1109/iciinfs.2015.7398987

Cited by 10 publications

(7 citation statements)

References 6 publications

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“…Moreover, due to this limit, this paper only gives an analytical simulation result. Some simulators like NS and OPNET are well-established and have been applied for these specific WSN communication technologies [30,31,32,33], such as Zigbee, WiFi, LTE and so on. By choosing a WSN communication technology, we can extend the simulation work on these well-established simulators to verify more indicators.…”

Section: Discussionmentioning

confidence: 99%

A Fault Tolerance Mechanism for On-Road Sensor Networks

Feng

Guo

Sun

et al. 2016

Sensors

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On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%.

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Section: Discussionmentioning

confidence: 99%

A Fault Tolerance Mechanism for On-Road Sensor Networks

Feng

Guo

Sun

et al. 2016

Sensors

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“…How to design a high energy efficiency network is an important challenge for WSN. Smallworld networks have the characteristics of small average path length and the largest clustering coefficient, which can be used to optimize the energy [11], routing [12] [82][83][84] and topology [85] [86] of wireless sensor networks.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

“…In order to review the application of small world network in WSN more comprehensively, the performance indicators concerned by WSN in small world model mainly include the following items [12] 1) Network dynamics. Whether the small-world WSN network can adapt to the mobility of nodes in the network.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

“…Community detection [89] Industrial wireless sensor networks [10][11] Delay Tolerant Networks (DTNs) [58] Detection of the community structure of smart city network system [59] Topology planning [88] Grid system [31] East China power grid [32] HUST WU WUT CSU SYSU [29] Network attack [98] Wireless sensor network [92] User-side big data balanced partitioning [94] The end-to-end TCP [91] Job scheduling [60] Joint localization and data acquisition in wireless sensor networks [85][86] Optimize the average network latency of the network [57] Information center network [51] Network routing [12] cally the following, power consumption, delay, ductility, robustness. Figure .7 summarizes the industrial interconnection network topology mentioned above.…”

Section: Small-world Networkmentioning

confidence: 99%

“…For small-scale networks, the topology of the network has strong regularity, such as ring network, star network, etc. This type of network can also find corresponding instances in real industrial network deployment, such as wireless sensor network [10] [11] and computer network [12].…”

Section: Introductionmentioning

confidence: 99%

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A Survey on the Network Models applied in the Industrial Network Optimization

Chen¹,

Xiong²,

Xue³

et al. 2022

Preprint

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Network architecture design is very important for the optimization of industrial networks. The type of network architecture can be divided into small-scale network and large-scale network according to its scale. Graph theory is an efficient mathematical tool for network topology modeling. For small-scale networks, its structure often has regular topology. For large-scale networks, the existing research mainly focuses on the random characteristics of network nodes and edges. Recently, popular models include random networks, small-world networks and scale-free networks. Starting from the scale of network, this survey summarizes and analyzes the network modeling methods based on graph theory and the practical application in industrial scenarios. Furthermore, this survey proposes a novel network performance metric -system entropy. From the perspective of mathematical properties, the analysis of its non-negativity, monotonicity and concave-convexity is given. The advantage of system entropy is that it can cover the existing regular network, random network, small-world network and scale-free network, and has strong generality. The simulation results show that this metric can realize the comparison of various industrial networks under different models.

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