scholarly journals Comparative Analysis of Pathfinding Algorithms A *, Dijkstra, and BFS on Maze Runner Game

2018 ◽  
Vol 1 (2) ◽  
pp. 1 ◽  
Author(s):  
Silvester Dian Handy Permana ◽  
Ketut Bayu Yogha Bintoro ◽  
Budi Arifitama ◽  
Ade Syahputra
Keyword(s):  
Comparative Analysis ◽  
Shortest Path ◽  
Process Time ◽  
Destination Node ◽  
Comparison Process ◽  
Breadth First Search ◽  
Computing Process ◽  
Start Node

Maze Runner game is a game that requires pathfinding algorithm to get to the destination with the shortest path. This algorithm is used in an NPC that will move from start node to destination node. However, the use of incorrect algorithms can affect the length of the computing process to find the shortest path. The longer the computing process, the longer the players have to wait. This study compared pathfinding algorithms A *, Dijkstra, and Breadth First Search (BFS) in the Maze Runner game. Comparison process of these algorithms was conducted by replacing the algorithm in the game by measuring the process time, the length of the path, and the numbers of block played in the existing computing process. The results of this study recommend which algorithm is suitable to be applied in Maze Runner Game.

scholarly journals Improving the Quality of Service and Privacy by Integrating Dijkstra‟s, SafeQ and Extended Watchdog Algorithm in Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 5409-5414
Keyword(s):  
Wireless Sensor Networks ◽  
Quality Of Service ◽  
Sensor Networks ◽  
Shortest Path ◽  
Clustering Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Destination Node ◽  
Hop Count

The fundamental issue is framing the sensor nodes and steering the information from sender node to receiver node in wireless sensor networks (WSN). To resolve this major difficulty, clustering algorithm is one of the accessible methods employed in wireless sensor networks. Still, clustering concept also faces some hurdles while transmitting the data from source to destination node. The sensor node is used to sense the data and the source node helps to convey the information and the intended recipient receives the sensed information. The clustering proposal will choose the cluster head depending on the residual energy and the sensor utility to its cluster members. The cluster heads will have equal cluster number of nodes. The complexity is generated in computing the shortest path and this can be optimized by Dijkstra’s algorithm. The optimization is executed by Dijkstra’s shortest path algorithm that eliminates the delay in packet delivery, energy consumption, lifetime of the packet and hop count while handling the difficulties. The shortest path calculation will improve the quality of service (QoS). QoS is the crucial problem due to loss of energy and resource computation as well as the privacy in wireless sensor networks. The security can be improvised in this projected work. The preventive metrics are discussed to upgrade the QoS facility by civilizing the privacy parameter called as Safe and Efficient Query Processing (SAFEQ) and integrating the extended watchdog algorithm in wireless sensor networks.

A Generic Approach on How to Formally Specify and Model Check Path Finding Algorithms: Dijkstra, A* and LPA*

2020 ◽  
Vol 30 (10) ◽  
pp. 1481-1523
Author(s):  
Kazuhiro Ogata
Keyword(s):  
Model Checking ◽  
Shortest Path ◽  
Formal Specification ◽  
Model Check ◽  
Shortest Paths ◽  
Path Finding ◽  
Property A ◽  
Goal Node ◽  
The Cost ◽  
Start Node

The paper describes how to formally specify three path finding algorithms in Maude, a rewriting logic-based programming/specification language, and how to model check if they enjoy desired properties with the Maude LTL model checker. The three algorithms are Dijkstra Shortest Path Finding Algorithm (DA), A* Algorithm and LPA* Algorithm. One desired property is that the algorithms always find the shortest path. To this end, we use a path finding algorithm (BFS) based on breadth-first search. BFS finds all paths from a start node to a goal node and the set of all shortest paths is extracted. We check if the path found by each algorithm is included in the set of all shortest paths for the property. A* is an extension of DA in that for each node [Formula: see text] an estimation [Formula: see text] of the distance to the goal node from [Formula: see text] is used and LPA* is an incremental version of A*. It is known that if [Formula: see text] is admissible, A* always finds the shortest path. We have found a possible relaxed sufficient condition. The relaxed condition is that there exists the shortest path such that for each node [Formula: see text] except for the start node on the path [Formula: see text] plus the cost to [Formula: see text] from the start node is less than the cost of any non-shortest path to the goal from the start. We informally justify the relaxed condition. For LPA*, if the relaxed condition holds in each updated version of a graph concerned including the initial graph, the shortest path is constructed. Based on the three case studies for DA, A* and LPA*, we summarize the formal specification and model checking techniques used as a generic approach to formal specification and model checking of path finding algorithms.

scholarly journals Breadth First Search Approach for Shortest Path Solution in Cartesian Area

2018 ◽  
Vol 1019 ◽  
pp. 012038 ◽  
Author(s):  
Robbi Rahim ◽  
Dahlan Abdullah ◽  
Saiful Nurarif ◽  
Mukhlis Ramadhan ◽  
Badrul Anwar ◽  
...  
Keyword(s):  
Shortest Path ◽  
Breadth First Search ◽  
Search Approach

Shortest path algorithms using dynamic breadth-first search

Networks ◽  
1991 ◽  
Vol 21 (1) ◽  
pp. 29-50 ◽  
Author(s):  
Donald Goldfarb ◽  
Jianxiu Hao ◽  
Sheng-Roan Kai
Keyword(s):  
Shortest Path ◽  
Breadth First Search ◽  
Shortest Path Algorithms

Improvement A* Algorithm Based on Dynamic Consistency Assumption

2011 ◽  
Vol 97-98 ◽  
pp. 883-887
Author(s):  
Liang Zou ◽  
Zi Zhang ◽  
Ling Xiang Zhu
Keyword(s):  
Lower Bound ◽  
Shortest Path ◽  
Dynamic Networks ◽  
Shortest Paths ◽  
Dynamic Consistency ◽  
Destination Node ◽  
Shortest Path Algorithm ◽  
A Algorithm ◽  
Dynamic Form

Efficient dynamic shortest path algorithm in static networks plays an important role in ITS. To solve this problem, this paper brings forward the dynamic form of Consistency Assumption and Dynamic A* algorithm (A* algorithm based on dynamic lower bound, DA* algorithm) based on dynamic lower bound. DA* algorithm and the dynamic form of Consistency Assumption are described in detail. It is proved that DA* algorithm can solve one origin node to one destination node shortest paths problem in dynamic networks, if DA* algorithm’s dynamic lower bound satisfies the dynamic form of Consistency Assumption.

scholarly journals Simulation study of power aware routing algorithms in multi-hop networks

2021 ◽  
Author(s):  
Kalaimagal Balasubramaniam
Keyword(s):  
Programming Language ◽  
Shortest Path ◽  
Simulation Study ◽  
Routing Algorithms ◽  
Destination Node ◽  
Shortest Path Algorithm ◽  
Java Programming Language ◽  
Java Programming

In a multi-hop network, the connection between an arbitrary source and destination node can be established using intermediate nodes. This project discusses the existing power aware routing algorithms, MHC, MTPR, and MBCR, which are used to minimize the delay, power and nodal over-utilization. The project also presents two newly proposed algorithms, MWBCR and MTP-WBCR which are simulated in a tool based on Dijkstra's shortest path algorithm, to evaluate the performance using Java programming language.

scholarly journals Data Security and Shortest Path Finding in IOT

2019 ◽  
pp. 551-557
Author(s):  
W. Winfredruby ◽  
S Sivagurunathan
Keyword(s):  
Shortest Path ◽  
Humidity Sensor ◽  
Shortest Paths ◽  
Data Access ◽  
Destination Node ◽  
Network Congestion ◽  
Shortest Path Algorithm ◽  
Sensor Applications ◽  
Encryption And Decryption ◽  
The Internet Of Things

Nowadays with the rapid growth of the smart city and the internet of things applications are difficult to connect the data access center, to meet service requirements with low latency and high quality while sending and receiving data access requests. At the same time, lower security performance occurred. In temperature and humidity sensor applications we approach a cryptography technique to protect data. It is an ASCII values-based technique which uses some numerical calculation to perform encryption and decryption. Then the use of the shortest path algorithm we find an entire possible path using current node detail and the destination node is sent by the source node to the neighbourhood nodes. Neighbourhood node receives the detail and checks the destination node. In case, the neighbourhood node is not the destination, it appends its detail along with the received details and sends to its neighbourhood nodes and the process continues till reaching the destination. By calculating the link delay between the two nodes. We can find the delay time taken from source to destination. At last we display the entire possible shortest paths and secure data. It is useful when network congestion occurs. In this paper, we also overcome this problem.

scholarly journals Comparative Analysis of TCP, SCTP and MPTCP in Transport Layer of Wireless Sensor Networks

10.29007/h7cg ◽  
2018 ◽  
Author(s):  
Geerija Lavania ◽  
Preeti Sharma ◽  
Richa Upadhyay
Keyword(s):  
Comparative Analysis ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Packet Loss ◽  
Data Transfer ◽  
Reliable Data ◽  
Transport Layer ◽  
Wireless Sensor ◽  
Destination Node ◽  
Reliable Data Transfer

The wireless sensor network is the network that has large number of sensor nodes that are connected to each other. The wireless nodes sense the event and forward packets to the destination node. A transport layer handles congestion and packet loss recovery for reliable data transfer in WSN. There exist several protocols at the transport layer in WSN for reliable data transfer like ESRT, ATP, Tiny TCP/IP, PORT, CTCP, RTMC, DCDD, RETP etc. Each protocol has its merits and demerits. Traditional network uses TCP and UDP protocol at the transport layer. In WSN, these are not suitable. In this work, the TCP, SCTP and MPTCP are compared in the wireless sensor network environment. The wireless network with packet loss is considered. From the comparative analysis, we get the result that MPTCP gives the better performance than TCP and SCTP in the wireless sensor network.

Finding the Shortest Path With Neutrosophic Theory

2020 ◽  
pp. 1-32 ◽  
Author(s):  
Said Broumi ◽  
Shio Gai Quek ◽  
Ganeshsree Selvachandran ◽  
Florentin Smarandache ◽  
Assia Bakali ◽  
...  
Keyword(s):  
Shortest Path ◽  
Path Length ◽  
Real Life ◽  
Ranking Method ◽  
Source Node ◽  
Destination Node ◽  
Numerical Example ◽  
Triangular Neutrosophic Numbers

In this chapter, the authors study a kind of network where the edge weights are characterized by single-valued triangular neutrosophic numbers. First, rigorous definitions of nodes, edges, paths, and cycles of such a network were proposed, which are then defined in algebraic terms. Then, characterization on the length of paths in such a network were presented. This is followed by the presentation of an algorithm for finding the shortest path length between two given nodes on the network. The proposed algorithm gives the shortest path length from source node to destination node based on a ranking method that takes both the length of edges and the number of nodes into account. Finally, a numerical example based on a real-life scenario is also presented to illustrate the efficiency and usefulness of the proposed approach.

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