Modification of Floyd-Warshall's algorithm for Shortest Path routing in wireless sensor networks

Khan, Pritam; Konar, Gargi; Chakraborty, Nilanjan

doi:10.1109/indicon.2014.7030504

Cited by 14 publications

(6 citation statements)

References 14 publications

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“…Again from place of obstruction, it calculates multiple paths. In 2014, P. Khan et al [35] introduced a revised Floyd Warshall method that finds the quickest distance using the directed graph structure. Furthermore, for every travelled route, there is a verification path choice open.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Urban Cities: Optimal Path Selection Based on Ad Hoc Network

2023

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Fusion of internet of things (IoT) and artificial intelligence for smart cities has allowed structured policy making.In particular, traffic jam is one of the serious concern in metropolitan cities. In advanced countries, specific devices are installed to assemble flow of traffic. The state of traffic is streamed to commuters through network. This dependency on internet connection results in inappropriate solution in absence of stable physical infrastructure. The developing countries lack availability of internet on roadway and urban zones face even worst condition. This study proposes a smart framework to enable optimal path selection by communicating with neighbouring devices. The android smart phones serve the purpose of embedded sensors. A temporary network is created for smart transportation system. Data processing and cleaning were conducted on different routes of two urban cities. The proposed system is evaluated on conventional and proposed optimal path selection techniques. Computed results depict that travel times have been decreased to around 23.3% in comparison to conventional methods using MDSP algorithm.

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Section: Related Workmentioning

confidence: 99%

Intelligent Urban Cities: Optimal Path Selection Based on Ad Hoc Network

2023

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“…Close is the vertex set that has solved the shortest path, and Open is the vertex set that has not determined the shortest path. Dijkstra algorithm is widely used in path planning problems in small-scale urban road routing, wireless sensor network and software defined network [11][12][13]. However, due to the algorithm needs to traverse each node in the calculation process, the algorithm efficiency is low, so it is more suitable for use in static scenes with small amount of data, and it is difficult to be used in large-scale engineering.…”

Section: Dijkstramentioning

confidence: 99%

Multi-objective vehicle path planning based on DQN

Huo

2022

International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022)

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In the path planning problem based on geographic information system, distance and resource overhead often conflict with each other. For example, the shortest path may not be the most time-saving or convenient one. So, a Multi-objective vehicle path planning method is needed. Therefore, this paper proposes a vehicle path planning algorithm based on improved deep reinforcement learning, which not only solves the problem of single optimization objective restriction, but also reduce the chance of falling into local optimum in traditional path planning algorithm. In this paper, DQN network structure is selected, and neural network is used to store action value function instead of Q table. In the training process, prioritized experience replay strategy is used to accelerate the convergence. The simulation experiment and analysis of the proposed model show that the improved DQN algorithm model can effectively find the path with the optimal value, making the path planning more rational and intelligent.

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“…Floyd Warshall algorithm finds the shortest path between every pair of vertices. It is similar to the single-source shortest path Dijkstra's algorithm but Dijkstra's algorithm finds out the path from one of the source vertices [8].…”

Section: Floyd Warshall's Algorithmmentioning

confidence: 99%

Shortest Path Computation Technique in WSN for IOT Applications

Gill

Dubey

2022

Preprint

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A Wireless Sensor Network (WSN) consists of a large no of sensor nodes deployed inside a physical environment that are capable of sensing and processing the data related to that environment and communicating it over the network. One of the vital applications of WSN is its suitability to smart cities that consist of many features such as smart buildings, smart education, smart governance, smart security, and smart mobility. This paper focuses on calculating the shortest path from the source node to the destination node in WSN by means of Dijkstra’s Algorithm. Various other algorithms are also compared and their suitability to different application scenarios is discussed. Simulations have been made for the smart city and Internet of Things (IoT) application by using the WSN simulator CupCarbon U-One 4.2.

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Modification of Floyd-Warshall's algorithm for Shortest Path routing in wireless sensor networks

Cited by 14 publications

References 14 publications

Intelligent Urban Cities: Optimal Path Selection Based on Ad Hoc Network

Intelligent Urban Cities: Optimal Path Selection Based on Ad Hoc Network

Multi-objective vehicle path planning based on DQN

Shortest Path Computation Technique in WSN for IOT Applications

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