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Journal articles on the topic 'Adaptive routing'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Chien, Andrew A., and Jae H. Kim. "Planar-adaptive routing." Journal of the ACM 42, no. 1 (1995): 91–123. http://dx.doi.org/10.1145/200836.200856.

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2

Chien, Andrew A., and Jae H. Kim. "Planar-adaptive routing." ACM SIGARCH Computer Architecture News 20, no. 2 (1992): 268–77. http://dx.doi.org/10.1145/146628.140383.

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3

Economides, A. A., P. A. Ioannou, and J. A. Silvester. "Adaptive virtual circuit routing." Computer Networks and ISDN Systems 28, no. 3 (1996): 401–9. http://dx.doi.org/10.1016/0169-7552(95)00006-2.

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4

Nelakuditi, S., Zhi-Li Zhang, R. P. Tsang, and D. H. C. Du. "Adaptive proportional routing: a localized QoS routing approach." IEEE/ACM Transactions on Networking 10, no. 6 (2002): 790–804. http://dx.doi.org/10.1109/tnet.2002.804832.

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5

aghajani, Foroogh Haj, Ahmad Khademzadeh, Samira Saeidi, and Kambiz Badie. "Angle Routing: A Fully Adaptive Packet Routing for NoC." International Journal on Computational Science & Applications 5, no. 3 (2015): 01–12. http://dx.doi.org/10.5121/ijcsa.2015.5301.

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6

Tassiulas, Leandros. "Adaptive Routing on the Plane." Operations Research 44, no. 5 (1996): 823–32. http://dx.doi.org/10.1287/opre.44.5.823.

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7

Fu Chang and Lancelot Wu. "An optimal adaptive routing algorithm." IEEE Transactions on Automatic Control 31, no. 8 (1986): 690–700. http://dx.doi.org/10.1109/tac.1986.1104381.

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8

Manevich, Ran, Israel Cidon, avinoam kolodny, and Isask'har Walter. "Centralized Adaptive Routing for NoCs." IEEE Computer Architecture Letters 9, no. 2 (2010): 57–60. http://dx.doi.org/10.1109/l-ca.2010.17.

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9

Flajolet, Arthur, Sébastien Blandin, and Patrick Jaillet. "Robust Adaptive Routing Under Uncertainty." Operations Research 66, no. 1 (2018): 210–29. http://dx.doi.org/10.1287/opre.2017.1662.

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10

Navidi, Fatemeh, Prabhanjan Kambadur, and Viswanath Nagarajan. "Adaptive Submodular Ranking and Routing." Operations Research 68, no. 3 (2020): 856–77. http://dx.doi.org/10.1287/opre.2019.1889.

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Many applications of stochastic optimization involve making sequential decisions until some stopping criterion is satisfied. For example, in medical diagnosis, a doctor needs to perform an adaptive sequence of tests on a patient in order to diagnose a disease. Being adaptive allows the doctor to choose the next test based on the outcomes of prior tests. Given an a priori probability distribution over diseases, the goal is to minimize the expected cost of tests. In “Adaptive Submodular Ranking and Routing,” Navidi, Kambadur, and Nagarajan formulate a general stochastic optimization problem in w

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11

WHITESON, S., and P. STONE. "Adaptive job routing and scheduling." Engineering Applications of Artificial Intelligence 17, no. 7 (2004): 855–69. http://dx.doi.org/10.1016/s0952-1976(04)00109-5.

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12

Fischer, Simon, and Berthold Vöcking. "Adaptive routing with stale information." Theoretical Computer Science 410, no. 36 (2009): 3357–71. http://dx.doi.org/10.1016/j.tcs.2008.01.055.

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13

Fawcett, J., and P. Robinson. "Adaptive routing for road traffic." IEEE Computer Graphics and Applications 20, no. 3 (2000): 46–53. http://dx.doi.org/10.1109/38.844372.

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14

György, András, and György Ottucsák. "Adaptive Routing Using Expert Advice." Computer Journal 49, no. 2 (2006): 180–89. http://dx.doi.org/10.1093/comjnl/bxh168.

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15

Tsai, W. T., C. V. Ramamoorthy, W. K. Tsai, and O. Nishiguchi. "An adaptive hierarchical routing protocol." IEEE Transactions on Computers 38, no. 8 (1989): 1059–75. http://dx.doi.org/10.1109/12.30862.

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16

Chen, M. S., and J. S. Meditch. "A distributed adaptive routing algorithm." Computers & Electrical Engineering 13, no. 2 (1987): 105–15. http://dx.doi.org/10.1016/0045-7906(87)90004-8.

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17

Kim, J. H., Ziqiang Liu, and A. A. Chien. "Compressionless routing: a framework for adaptive and fault-tolerant routing." IEEE Transactions on Parallel and Distributed Systems 8, no. 3 (1997): 229–44. http://dx.doi.org/10.1109/71.584089.

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18

Zahavi, Eitan, Isaac Keslassy, and Avinoam Kolodny. "Distributed Adaptive Routing Convergence to Non-Blocking DCN Routing Assignments." IEEE Journal on Selected Areas in Communications 32, no. 1 (2014): 88–101. http://dx.doi.org/10.1109/jsac.2014.140109.

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19

Rohit, Sharma* Er. Rachna Rajput. "A REVIEW PAPER ON ROUTING USING ADAPTIVE POSITION UPDATE (APU) STRATEGY." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 5 (2017): 24–28. https://doi.org/10.5281/zenodo.571590.

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MANET is self-configured Mobile Ad hoc network of mobile nodes connected via random topology. The main issue in MANET is the selection of best path between any two nodes. Routing in MANET is to find the efficient path to transfer the data from source to destination. APU strategy is routing strategy for geographic routing in Mobile ad-hoc network which dynamically adjust the frequency of position updates based on the mobility dynamics of the nodes and the forwarding patterns in the network. The beacon updates include the current location and velocity of the nodes. Existing systems use periodic

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20

HusseinMamoun, Mamoun. "New Adaptive Routing Proposal for DTN." International Journal of Computer Applications 82, no. 9 (2013): 37–40. http://dx.doi.org/10.5120/14147-2306.

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21

Guleria, Ajay, and Kuldeep Singh. "Position Based Adaptive Routing for VANETs." International journal of Computer Networks & Communications 9, no. 1 (2017): 55–70. http://dx.doi.org/10.5121/ijcnc.2017.9105.

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22

Wojcik, Robert, Jerzy Domzal, and Zbigniew Dulinski. "Flow-Aware Multi-Topology Adaptive Routing." IEEE Communications Letters 18, no. 9 (2014): 1539–42. http://dx.doi.org/10.1109/lcomm.2014.2334314.

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23

Glass, Christopher J., and Lionel M. Ni. "The turn model for adaptive routing." Journal of the ACM 41, no. 5 (1994): 874–902. http://dx.doi.org/10.1145/185675.185682.

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24

Gavoille, Cyril, and Akka Zemmari. "The compactness of adaptive routing tables." Journal of Discrete Algorithms 1, no. 2 (2003): 237–54. http://dx.doi.org/10.1016/s1570-8667(03)00027-3.

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25

Boyles, Stephen D., and S. Travis Waller. "Optimal Information Location for Adaptive Routing." Networks and Spatial Economics 11, no. 2 (2009): 233–54. http://dx.doi.org/10.1007/s11067-009-9108-9.

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26

Soltani, Azadeh, M. R. Akbarzadeh-T, and M. Naghibzadeh. "Helping ants for adaptive network routing." Journal of the Franklin Institute 343, no. 4-5 (2006): 389–403. http://dx.doi.org/10.1016/j.jfranklin.2006.02.007.

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27

Awerbuch, Baruch, and Robert Kleinberg. "Online linear optimization and adaptive routing." Journal of Computer and System Sciences 74, no. 1 (2008): 97–114. http://dx.doi.org/10.1016/j.jcss.2007.04.016.

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28

Martı́nez, J. C., J. Flich, A. Robles, P. López, and J. Duato. "Supporting adaptive routing in IBA switches." Journal of Systems Architecture 49, no. 10-11 (2003): 441–56. http://dx.doi.org/10.1016/s1383-7621(03)00103-6.

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29

Rosenberg, J. L., S. A. Gruchevsky, and D. M. Piscitello. "Adaptive routing in Burroughs network architecture." ACM SIGCOMM Computer Communication Review 17, no. 5 (1987): 173–84. http://dx.doi.org/10.1145/55483.55500.

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30

Jia, Xu, Feng Xin, and Wang Ru Chuan. "ADAPTIVE SPRAY ROUTING FOR OPPORTUNISTIC NETWORKS." International Journal on Smart Sensing and Intelligent Systems 6, no. 1 (2013): 95–119. http://dx.doi.org/10.21307/ijssis-2017-530.

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31

Glass, Christopher J., and Lionel M. Ni. "The turn model for adaptive routing." ACM SIGARCH Computer Architecture News 20, no. 2 (1992): 278–87. http://dx.doi.org/10.1145/146628.140384.

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32

Bolding, K., M. Fulgham, and L. Snyder. "The case for chaotic adaptive routing." IEEE Transactions on Computers 46, no. 12 (1997): 1281–92. http://dx.doi.org/10.1109/12.641929.

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33

Prasad, Madhushini Narayana, Nedialko Dimitrov, and Evdokia Nikolova. "Non-Aggressive Adaptive Routing in Traffic." Mathematics 11, no. 17 (2023): 3639. http://dx.doi.org/10.3390/math11173639.

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Routing a person through a traffic road network presents a tension between selecting a fixed route that is easy to navigate and selecting an aggressively adaptive route that minimizes travel time. In this paper, we propose a novel routing framework that strikes a balance between adaptability and simplicity. Specifically, we propose to create non-aggressive adaptive routes that seek the best of both these extremes in the navigation world. These selected routes still adapt to changing traffic conditions, but we limit the number of adjustments made en route. This framework improves the driver exp

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34

Lin, X., A.-H. Esfahanian, and A. Burago. "Adaptive Wormhole Routing in Hypercube Multicomputers." Journal of Parallel and Distributed Computing 48, no. 2 (1998): 165–74. http://dx.doi.org/10.1006/jpdc.1997.1417.

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35

Belghith, Abdelfettah, Mohamed Amine Abid, and Adel Ben Mnaouer. "Adaptive Probabilistic Proactive Routing for Dense MANETs." Journal of Computer Networks and Communications 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/234824.

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Conventional proactive routing protocols, due to their inherent nature based on shortest paths, select longer links which are amenable to rapid breakages as nodes move around. In this paper, we propose a novel adaptive probabilistic approach to handle routing information in dense mobile ad hoc networks in a way to improve the proactive routing pertinence as a function of network dynamics. We first propose a new proactive routing framework based on probabilistic decisions and a generic model to compute the existence probabilities of nodes and links. Then, we present a distributed algorithm to c

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36

Shashidhar, P. K., T. C. Thanuja, and Rajashekar Kunabeva. "Adaptive RPL Routing Optimization Model for Multimedia Data Transmission using IOT." Indian Journal Of Science And Technology 17, no. 5 (2024): 436–50. http://dx.doi.org/10.17485/ijst/v17i5.2627.

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Objectives: The main objectives of this research endeavor encompass the development of the Adaptive RPL Optimization (ARPLO) model to enhance data transmission efficiency within IoT networks. This includes constructing a grid-based network structure optimized for data transfer, selecting the most suitable nodes as grid head nodes to maximize network lifespan while minimizing energy consumption, implementing an innovative objective function-driven approach to optimize parent node selection, and integrating an Adaptive Deep Neural Network (ADNN) to accurately classify medical data. Methods: The

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37

Chen, Zhe, Yan Xiang He, and Wen Ming Shi. "An Adaptive Threshold Routing Scheme in DTNs." Advanced Materials Research 850-851 (December 2013): 733–36. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.733.

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The paper proposes an adaptive threshold routing scheme for delay tolerant networks. And it introduces the principle of ATM. The applications motivate a routing method that is different from Epidemic Routing Strategy in two ways: throughput and delivery. Finally the simulation results show that ATM obtains significant superior by comparing with the ERS.

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38

Abolhasan, Mehran, Tadeusz Antoni Wysocki, and Eryk Dutkiewicz. "LPAR: an adaptive routing strategy for MANETs." Journal of Telecommunications and Information Technology, no. 2 (June 30, 2003): 28–37. http://dx.doi.org/10.26636/jtit.2003.2.173.

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This paper presents a new global positioning system (GPS)-based routing protocol, called location-based point-to-point adaptive routing (LPAR) for mobile ad hoc networks. This protocol utilises a 3-state route discovery strategy in a point-to-point manner to reduce routing overhead while maximising throughput in medium to large mobile ad hoc networks. In LPAR, data transmission is adaptable to changing network conditions. This is achieved by using a primary and a secondary data forwarding strategy to transfer data from the source to the destination when the condition of the route is changed du

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39

Freitas Silva, Rodrigo. "Adaptive: An Adaptive Routing Protocol for Vehicle Delay-Tolerant Networks." IEEE Latin America Transactions 18, no. 02 (2019): 223–31. http://dx.doi.org/10.1109/tla.2019.9082232.

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40

Freitas Silva, Rodrigo. "Adaptive: An Adaptive Routing Protocol for Vehicle Delay-Tolerant Networks." IEEE Latin America Transactions 18, no. 02 (2020): 223–31. http://dx.doi.org/10.1109/tla.2020.9085274.

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41

Khusnandar, Wahyudi, Fransiscus Ati Halim, and Felix Lokananta. "Design of TTL Based Routing Algorithm on UTAR Network on Chip Communication Architecture." International Journal of New Media Technology 5, no. 1 (2018): 54–57. http://dx.doi.org/10.31937/ijnmt.v5i1.738.

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XY adaptive routing protocol is a routing protocol used on UTAR NoC communication architecture. This routing algorithm adapts shrotest-path first algorithm, which will forward will not be able to work optimally if the closest route no longer have enough bandwidth to continue the packet. Packet will be stored inside the router and forwarded to the nearest router when closest route has enough bandwidth. This paper suggest TTL based routing algorithm to resolve this issue. TTL based routing algorithm adapts XY adaptive routing protocol by adding several parameters on RTL UTAR NoC and additional b

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42

Serhani, Abdellatif, Najib Naja, and Abdellah Jamali. "AQ-Routing: mobility-, stability-aware adaptive routing protocol for data routing in MANET–IoT systems." Cluster Computing 23, no. 1 (2019): 13–27. http://dx.doi.org/10.1007/s10586-019-02937-x.

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43

Gao, Song, Emma Frejinger, and Moshe Ben-Akiva. "Adaptive Route Choice Models in Stochastic Time-Dependent Networks." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (2008): 136–43. http://dx.doi.org/10.3141/2085-15.

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Adaptive route choice models are studied that explicitly capture travelers’ route choice adjustments according to information on realized network conditions in stochastic time-dependent networks. Two types of adaptive route choice models are explored: an adaptive path model in which a sequence of path choice models are applied at intermediate decision nodes and a routing policy choice model in which the alternatives correspond to routing policies rather than paths at the origin. A routing policy in this study is a decision rule that maps from all possible pairs (e.g., node, time) to the next l

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44

Devangavi, Anil D., and Rajendra Gupta. "Adaptive Congestion Controlled Multipath Routing in VANET." International Journal of Agent Technologies and Systems 9, no. 1 (2017): 43–68. http://dx.doi.org/10.4018/ijats.2017010103.

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This article describes how in the VANET environment, routes are broken owing to node mobility. Moreover, the usage of wireless links for data communication leads to inherent unreliability and are error prone. Single path routing uses a prediction mechanism to compute a reliable path considering vehicle velocity and vehicle direction. Nevertheless, this methodology does not deal with major real-world traffic conditions. Hence, to address the aforementioned problems and to enhance reliability and fault tolerance, multipath routing protocols are employed. However existing multipath routing protoc

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45

Pingale, Reena P., and Shinde S. N. "Adaptive-Sunflower-Based Grey Wolf Algorithm for Multipath Routing in IoT Networks." International Journal of Business Data Communications and Networking 17, no. 2 (2021): 1–27. http://dx.doi.org/10.4018/ijbdcn.286699.

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This paper devises a routing method for providing multipath routing inan IoT network. Here the Fractional Artificial Bee colony(FABC)algorithm is devised for initiating clustering process. Moreover the multipath routing is performed by the newly devised optimization technique, namely Adaptive-Sunflower based grey wolf(Adaptive-SFG)optimization technique which is designed by incorporating adaptive idea in Sunflower based grey wolf technique. In addition the fitness function is newly devised by considering certain factors that involves Context awareness, link lifetime Energy, Trust, and Delay.Fo

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46

Rasheed, Asim, Sana Ajmal, and Amir Qayyum. "Protocol Independent Adaptive Route Update for VANET." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/403918.

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High relative node velocity and high active node density have presented challenges to existing routing approaches within highly scaled ad hoc wireless networks, such as Vehicular Ad hoc Networks (VANET). Efficient routing requires finding optimum route with minimum delay, updating it on availability of a better one, and repairing it on link breakages. Current routing protocols are generally focused on finding and maintaining an efficient route, with very less emphasis on route update. Adaptive route update usually becomes impractical for dense networks due to large routing overheads. This pape

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47

Akinola, Oluwaseun Ibrahim. "Adaptive Location-based Routing Protocols for Dynamic Wireless Sensor Networks in Urban Cyber-physical Systems." Journal of Engineering Research and Reports 26, no. 7 (2024): 424–43. http://dx.doi.org/10.9734/jerr/2024/v26i71220.

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This study investigates the development and enhancement of adaptive location-based routing protocols within dynamic wireless sensor networks (WSNs) in urban cyber-physical systems, recommending the implementation of the study’s innovative Urban Adaptive Location-based Routing Protocol (UALRP). This innovative protocol integrates real-time data analytics and adaptive machine learning models into its algorithmic framework to dynamically optimize routing decisions based on continuously changing urban conditions. Through the utilization of data-driven simulation models and machine learning techniq

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48

Han, Guangzhi, Haifeng Jiang, Liansheng Lu, Shanshan Ma, and Shuo Xiao. "Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks." International Journal of Distributed Sensor Networks 14, no. 2 (2018): 155014771875921. http://dx.doi.org/10.1177/1550147718759217.

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Hybrid wireless mesh networks are suitable for complex environment communication in coal mine. Mesh clients with application service and routing function in hybrid wireless mesh networks can form a highly robust hybrid network with mesh routers. The processes of nutrient flux transfer and path choice in Physarum network are similar to data transmission and routing selection in hybrid wireless mesh networks. In this article, we use Physarum-inspired autonomic optimization model to design a Physarum-inspired multi-parameter adaptive routing protocol to improve the service quality of coal mine hy

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49

Wei-Kuo Liao and Chung-Ta King. "Valved routing: efficient flow control for adaptive nonminimal routing in interconnection networks." IEEE Transactions on Computers 44, no. 10 (1995): 1181–93. http://dx.doi.org/10.1109/12.467693.

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50

Russell, Brian, Michael L. Littman, and Wade Trappe. "Integrating machine learning in ad hoc routing: A wireless adaptive routing protocol." International Journal of Communication Systems 24, no. 7 (2011): 950–66. http://dx.doi.org/10.1002/dac.1202.

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