P-iRP: Physarum-Inspired Routing Protocol for Wireless Sensor Networks

Zhang, Mingchuan; Xu, Changqiao; Guan, Jianfeng; Zheng, Ruijuan; Wu, Qingtao; Zhang, Hongke

doi:10.1109/vtcfall.2013.6692365

Cited by 11 publications

(12 citation statements)

References 30 publications

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“…In [38,39], the mathematical model of Physarum polycephalum can select the appropriate routes which is used for data transmission. We improve this model, which can make it conduct route selection in ad hoc UAV network.…”

Section: Route Selectionmentioning

confidence: 99%

Bionic Optimization Based Stability and Congestion Aware Routing Algorithm for Airborne Highly Dynamic Network

Sheng

et al. 2016

International Journal of Distributed Sensor Networks

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Airborne highly dynamic ad hoc UAV network has features of high node mobility, fast changing network topology, and complex application environment. The performance of traditional routing algorithms is so poor over aspects such as end to end delay, data packet delivery ratio, and routing overhead that they cannot provide efficient communication for multi-UAVs carrying out missions synergistically. A bionic optimization based stability and congestion aware routing algorithm-BSCAR algorithm-is proposed to solve these problems. This algorithm integrates biological behavior and dynamic source routing algorithm, which can sense the congestion level of routes and the stability of routes. Ant colony optimization algorithm and the mathematical model of Physarum's behavior exert effort in the process of route discovery and maintenance. The level of pheromone in routes is chosen as a standard to choose route and calculated by the mathematical model of Physarum's behavior. A new volatilization mechanism of pheromone is also introduced into the algorithm. Meanwhile, the algorithm can make adjustment to the variance of UAV formation to prevent the compromise of the network performance. The simulation results show that the BSCAR algorithm has superiority over traditional algorithms and it is dependable in battlefield environment.

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Section: Route Selectionmentioning

confidence: 99%

Bionic Optimization Based Stability and Congestion Aware Routing Algorithm for Airborne Highly Dynamic Network

Sheng

et al. 2016

International Journal of Distributed Sensor Networks

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“…In this section, we improve PAO to acquire PAO path-assessment model. From [12][13][14][15], the flux through each plasmodial tube follows…”

Section: Perceptive Aco Path-finding Modelmentioning

confidence: 99%

“…Bio-inspired methods [10][11][12][13][14][15] are advantageous for solving the problems regardless of security and efficiency of routing protocols. Gunes et al [10] present an on-demand routing algorithm ARA based on ant colony optimization (ACO) and AODV [16].…”

Section: Introductionmentioning

confidence: 99%

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B-iTRS: A Bio-Inspired Trusted Routing Scheme for Wireless Sensor Networks

Zhang

Zheng

et al. 2015

Journal of Sensors

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In WSNs, routing algorithms need to handle dynamical changes of network topology, extra overhead, energy saving, and other requirements. Therefore, routing in WSNs is an extremely interesting and challenging issue. In this paper, we present a novel bio-inspired trusted routing scheme (B-iTRS) based on ant colony optimization (ACO) and Physarum autonomic optimization (PAO). For trust assessment, B-iTRS monitors neighbors’ behavior in real time, receives feedback from Sink, and then assesses neighbors’ trusts based on the acquired information. For routing scheme, each node finds routes to the Sink based on ACO and PAO. In the process of path finding, B-iTRS senses the load and trust value of each node and then calculates the link load and link trust of the found routes to support the route selection. Moreover, B-iTRS also assesses the route based on PAO to maintain the route table. Simulation results show how B-iTRS can achieve the effective performance compared to existing state-of-the-art algorithms.

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“…home, office or campus) to expand distributed service capability [1][2][3]. The user can have access to high quality service at any time with multi-devices cooperation [4][5][6]. Ubiquitous network changes network edges and forms ubiquitous stub environment in which people access directly through various heterogeneous devices.…”

Section: Introductionmentioning

confidence: 99%

A Novel Recovery Strategy for Service Interruption in Ubiquitous Stub Environment

Niu

Rui

Guo

et al. 2014

2014 IEEE 79th Vehicular Technology Conference (VTC Spring)

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In ubiquitous stub environment, several mobile devices can work cooperatively to provide efficient and reliable service. But device movement or failure usually causes service interruption. How to recover the service path quickly and enhance the user experience greatly is an important problem. This paper presents a novel recovery strategy to resolve the problem. First of all, the strategy conducts the local service recovery process. If it fails, the strategy will use the global service recovery process. Several key factors affecting recovery process are adopted in the strategy. Compared with other similar strategies in simulation experiment, the failure rate and service time of this strategy is lower than the others. So this novel strategy has a better performance.

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P-iRP: Physarum-Inspired Routing Protocol for Wireless Sensor Networks

Cited by 11 publications

References 30 publications

Bionic Optimization Based Stability and Congestion Aware Routing Algorithm for Airborne Highly Dynamic Network

Bionic Optimization Based Stability and Congestion Aware Routing Algorithm for Airborne Highly Dynamic Network

B-iTRS: A Bio-Inspired Trusted Routing Scheme for Wireless Sensor Networks

A Novel Recovery Strategy for Service Interruption in Ubiquitous Stub Environment

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