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Journal articles on the topic 'Mobile agents'

To see the other types of publications on this topic, follow the link: Mobile agents.

Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

Elijah and Muhammad Naveed Dilber. "Complete Analysis of Fault Tolerance Schemes in Mobile Agents for a Reliable Mobile Agent Computation." Bonfring International Journal of Industrial Engineering and Management Science 7, no. 1 (March 31, 2017): 20–24. http://dx.doi.org/10.9756/bijiems.8322.

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2

Diepolder, S., and K. H. Krempels. "Mobile Agenten. Mobile Agents." PIK - Praxis der Informationsverarbeitung und Kommunikation 29, no. 4 (December 2006): 203–7. http://dx.doi.org/10.1515/piko.2006.203.

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3

Huhns, M. N., and M. P. Singh. "Mobile agents." IEEE Internet Computing 1, no. 3 (1997): 80–82. http://dx.doi.org/10.1109/4236.589200.

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4

Reddy, Parineeth M. "Mobile agents." Resonance 7, no. 7 (July 2002): 35–43. http://dx.doi.org/10.1007/bf02836751.

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5

Borawake-Satao, Rachana, and Rajesh Shardanand Prasad. "Mobile Sink with Mobile Agents." International Journal of Rough Sets and Data Analysis 4, no. 2 (April 2017): 24–35. http://dx.doi.org/10.4018/ijrsda.2017040102.

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Wireless Sensor Networks (WSN) has been drawing considerable attention and discussion in recent years due to its potential applications in various fields. In modern applications for future internet the MSN (Mobile Sensor Network) is a key factor. Mobility allows the applications of Wireless Sensor Network to be compatible with IoT (Internet of Things) applications. As mobility enhances capability of the network it also affects the performance of the network at each layer. In recent years the various methodologies are proposed to handle mobility. Most of them use mobility for efficient data collection in WSNs. The purpose of this paper is to study effects of mobility on various performance parameters of the network and to explore the effective techniques to handle mobility in network. This paper proposes Mobile Sink with Mobile Agent mobility model for WSN which will increase the lifetime of the network using sink and agent node mobility.

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6

Leppänen, Teemu, José Álvarez Lacasia, Yoshito Tobe, Kaoru Sezaki, and Jukka Riekki. "Mobile crowdsensing with mobile agents." Autonomous Agents and Multi-Agent Systems 31, no. 1 (October 24, 2015): 1–35. http://dx.doi.org/10.1007/s10458-015-9311-7.

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7

Dalmeijer, M., D. K. Hammer, and A. T. M. Aerts. "Mobile software agents." Computers in Industry 41, no. 3 (May 2000): 251–60. http://dx.doi.org/10.1016/s0166-3615(99)00047-0.

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8

Martins, Rosane Maria, Magali Ribeiro Chaves, Luci Pirmez, and Luiz Fernando Rust da Costa Carmo. "Mobile agents applications." Internet Research 11, no. 1 (March 2001): 49–54. http://dx.doi.org/10.1108/10662240110365715.

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9

Zrari, Chadha, Hela Hachicha, and Khaled Ghedira. "Agent's Security During Communication in Mobile Agents System." Procedia Computer Science 60 (2015): 17–26. http://dx.doi.org/10.1016/j.procs.2015.08.100.

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10

Kovacs, Ern�, Klaus R�hrle, and Matthias Reich. "Integrating mobile agents into the mobile middleware." Personal Technologies 2, no. 2 (June 1998): 68–74. http://dx.doi.org/10.1007/bf01324936.

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11

Morreale, P. "Agents on the move [mobile software agents]." IEEE Spectrum 35, no. 4 (April 1998): 34–41. http://dx.doi.org/10.1109/6.666958.

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12

Bagga, Pallavi, and Rahul Hans. "Mobile Agents System Security." ACM Computing Surveys 50, no. 5 (November 13, 2017): 1–45. http://dx.doi.org/10.1145/3095797.

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13

Pietro Picco, Gian. "Mobile agents: an introduction." Microprocessors and Microsystems 25, no. 2 (April 2001): 65–74. http://dx.doi.org/10.1016/s0141-9331(01)00099-0.

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14

Shun, Zhou, Zhu Chunyan, and Ying Shi. "Mobile agents on internet." Wuhan University Journal of Natural Sciences 3, no. 1 (March 1998): 21–26. http://dx.doi.org/10.1007/bf02827506.

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15

Evripidou, Paraskevas, and George Samaras. "Metacomputing with Mobile Agents." International Journal of Parallel Programming 34, no. 5 (September 19, 2006): 429–58. http://dx.doi.org/10.1007/s10766-006-0021-2.

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16

Lange, Danny B., and Mitsuru Oshima. "Introduction to mobile agents." Personal Technologies 2, no. 2 (June 1998): 49–56. http://dx.doi.org/10.1007/bf01324934.

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17

Wong, David, Noemi Paciorek, and Dana Moore. "Java-based mobile agents." Communications of the ACM 42, no. 3 (March 1999): 92. http://dx.doi.org/10.1145/295685.295717.

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18

Greenberg, M. S., L. C. Byington, and D. G. Harper. "Mobile agents and security." IEEE Communications Magazine 36, no. 7 (July 1998): 76–85. http://dx.doi.org/10.1109/35.689634.

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19

STRASSER, MARKUS, and KURT ROTHERMEL. "RELIABILITY CONCEPTS FOR MOBILE AGENTS." International Journal of Cooperative Information Systems 07, no. 04 (December 1998): 355–82. http://dx.doi.org/10.1142/s0218843098000179.

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The use of mobile agent technology has been proposed for various fault-sensitive application areas, including electronic commerce and system management. A prerequisite for the use of mobile agents in these environments is that agents have to be executed reliably, independent of communication and node failures. In this article, we present two approaches improving the level of fault-tolerance in agent execution. The introduction of an itinerary concept allows to specify an agent's travel plan flexibly and provides the agent system with the possibility to postpone the visit of currently unavailable nodes or to choose alternative nodes in case of node failures. The second approach is a recently proposed fault-tolerant protocol to ensure the exactly-once execution of an agent. With this protocol, agents are preformed in stages. Each stage consists of a number of nodes. One of these nodes executes the agent while the others monitor the execution. After a summary of this protocol, we focus on the construction of stages. In particular, we investigate how the number of nodes per stage influences the probability of an agent to be blocked due to failures and which nodes should be selected when forming a stage to minimize the protocol overhead.

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20

Atawneh, Samer, Mousa Al-Akhras, Iman AlMomani, Anas Liswi, and Mohammed Alawairdhi. "Collaborative Mobile-Learning Architecture Based on Mobile Agents." Electronics 9, no. 1 (January 15, 2020): 162. http://dx.doi.org/10.3390/electronics9010162.

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The connection between collaborative learning and the new mobile technology has become tighter. Mobile learning enhances collaborative learning as learners can access information and learning materials from anywhere and at any time. However, supporting efficient mobile learning in education is a critical challenge. In addition, incorporating technological and educational components becomes a new, complex dimension. In this paper, an efficient collaborative mobile-learning architecture based on mobile agents is proposed to enhance learning activity and to allow teachers and students to collaborate in knowledge and information transfer. A mobile agent can control its own actions, is able to communicate with other agents, and adapts in accordance with previous experience. The proposed model consists of four components: the learner agent, the teacher agent, the device agent and the social agent. The social agent plays the main role in the collaborative tasks since it is responsible for evaluating the collaborative interactions among different learners. Additionally, it offers an evaluation indicator for the learners’ collaboration and supplies the teacher with learner’s collaboration reports. The proposed model is evaluated by introducing a collaborative mobile-learning case study applied to two full classes of undergraduate students. To conduct the model experiments, students were asked to complete a questionnaire after they used the proposed model. The questionnaire results statistically revealed that the proposed architecture is easy to use and access, well-organized, convenient, and facilitates the learning process. The students thought the proposed m-learning application should complement rather than replace the traditional lectures. Moreover, the experimental results show that the proposed collaborative mobile learning model enhances the learner’s skills in problem solving, increases the learner’s knowledge in comparison with individual learning, and social agent encourages learners for more participation in the learning tasks. Based on the experiments conducted, the authors found that the proposed model can improve the quality of the learning process by assessing learners’ and groups’ collaboration, and it can help teachers make learners improve how they work in groups. This also provides various ways of assessing learners abilities and skills in groups. It is also possible to integrate the collaborative e-learning with the proposed collaborative m-learning.

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21

Chen, Bo, Harry H. Cheng, and Joe Palen. "Mobile-C: a mobile agent platform for mobile C/C++ agents." Software: Practice and Experience 36, no. 15 (2006): 1711–33. http://dx.doi.org/10.1002/spe.742.

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22

Desai, Prashant R. "A Survey on Mobile Agents." International Journal for Research in Applied Science and Engineering Technology V, no. XI (November 23, 2017): 2915–19. http://dx.doi.org/10.22214/ijraset.2017.11401.

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23

Karjoth, Günter, and Joachim Posegga. "Mobile agents and telcos’ nightmares." Annales Des Télécommunications 55, no. 7-8 (July 2000): 388–400. http://dx.doi.org/10.1007/bf02994846.

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24

Dadhich, Priyanka, Dr Kamlesh Dutta, and Dr M. C. Govil. "Security Issues in Mobile Agents." International Journal of Computer Applications 11, no. 4 (December 10, 2010): 1–7. http://dx.doi.org/10.5120/1574-2104.

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25

Milojicic, Dejan S., William LaForge, and Deepika Chauhan. "Mobile Objects and Agents (MOA)." Distributed Systems Engineering 5, no. 4 (December 1998): 214–27. http://dx.doi.org/10.1088/0967-1846/5/4/007.

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26

Prasad, Sanjiva. "Models for mobile computing agents." ACM Computing Surveys 28, no. 4es (December 1996): 53. http://dx.doi.org/10.1145/242224.242292.

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27

Chess, D., B. Grosof, C. Harrison, D. Levine, C. Parris, and G. Tsudik. "Itinerant agents for mobile computing." IEEE Personal Communications 2, no. 5 (October 1995): 34–49. http://dx.doi.org/10.1109/98.468361.

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28

Holt, A., C. Y. Huang, and J. Monk. "Performance analysis of mobile agents." IET Communications 1, no. 3 (2007): 532. http://dx.doi.org/10.1049/iet-com:20050490.

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29

Jansen, Wayne A. "Intrusion detection with mobile agents." Computer Communications 25, no. 15 (September 2002): 1392–401. http://dx.doi.org/10.1016/s0140-3664(02)00040-3.

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30

Cabri, Giacomo, Letizia Leonardi, and Franco Zambonelli. "Coordination infrastructures for mobile agents." Microprocessors and Microsystems 25, no. 2 (April 2001): 85–92. http://dx.doi.org/10.1016/s0141-9331(01)00101-6.

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31

Degano, Pierpaolo, Corrado Priami, Lone Leth, and Bent Thomsen. "Causality for debugging mobile agents." Acta Informatica 36, no. 5 (September 1, 1999): 335–74. http://dx.doi.org/10.1007/s002360050164.

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32

Rothermel, Kurt. "Guest editorial: Mobile software agents." Personal Technologies 2, no. 2 (June 1998): 47–48. http://dx.doi.org/10.1007/bf01324933.

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33

Vu Anh Pham and A. Karmouch. "Mobile software agents: an overview." IEEE Communications Magazine 36, no. 7 (July 1998): 26–37. http://dx.doi.org/10.1109/35.689628.

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34

Hanandeh, Feras Ahmad, Izzat Alsmadi, Majdi Yousef Al Shannag, and Essam Al Daoud. "Mobile agents modelling using UML." International Journal of Business Information Systems 19, no. 4 (2015): 419. http://dx.doi.org/10.1504/ijbis.2015.070202.

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35

Bugliesi, Michele, Giuseppe Castagna, and Silvia Crafa. "Access control for mobile agents." ACM Transactions on Programming Languages and Systems 26, no. 1 (January 2004): 57–124. http://dx.doi.org/10.1145/963778.963781.

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36

Vasiu, L., and Q. H. Mahmoud. "Mobile agents in wireless devices." Computer 37, no. 2 (February 2004): 104–5. http://dx.doi.org/10.1109/mc.2004.1266304.

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37

Bieszczad, Andrzej, Bernard Pagurek, and Tony White. "Mobile agents for network management." IEEE Communications Surveys & Tutorials 1, no. 1 (1998): 2–9. http://dx.doi.org/10.1109/comst.1998.5340400.

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38

Chess, David, Benjamin Grosof, Colin Harrison, David Levine, Colin Parris, and Gene Tsudik. "Itinerant Agents for Mobile Computing." IEEE Communications Surveys & Tutorials 3, no. 3 (2000): 34–49. http://dx.doi.org/10.1109/comst.2000.5340729.

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39

Peschanski, Frédéric. "Mobile Agents in Interaction Spaces." Electronic Notes in Theoretical Computer Science 154, no. 1 (May 2006): 63–82. http://dx.doi.org/10.1016/j.entcs.2005.12.033.

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40

Jiao, Yu, and Ali R. Hurson. "Application of Mobile Agents in Mobile Data Access Systems." Journal of Database Management 15, no. 4 (October 2004): 1–24. http://dx.doi.org/10.4018/jdm.2004100101.

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41

Gadiraju, S., and V. Kumar. "Recovery in the mobile wireless environment using mobile agents." IEEE Transactions on Mobile Computing 3, no. 2 (April 2004): 180–91. http://dx.doi.org/10.1109/tmc.2004.13.

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42

Urra, Óscar, Sergio Ilarri Artigas, Raquel Trillo Lado, and Eduardo Mena Nieto. "Mobile agents and mobile devices: friendship or difficult relationship?" Journal of Physical Agents (JoPha) 3, no. 2 (2009): 27–37. http://dx.doi.org/10.14198/jopha.2009.3.2.06.

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43

., Asha Anil. "AN ENHANCED APPROACH FOR SECURING MOBILE AGENTS FROM THE ATTACK OF OTHER MALICIOUS MOBILE AGENTS." International Journal of Research in Engineering and Technology 03, no. 13 (March 25, 2014): 16–20. http://dx.doi.org/10.15623/ijret.2014.0313004.

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44

Kumar, Pradeep, Niraj Singhal, Dhiraj Pandey, and Avimanyou Vatsa. "Secure Mobile Agent Migration Using Lagrange Interpolation and Fast Fourier Transformation." International Journal of Computer Network and Information Security 15, no. 4 (August 8, 2023): 72–83. http://dx.doi.org/10.5815/ijcnis.2023.04.07.

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Mobile agent is a processing unit works on the behalf of host computer. Mobile agent with intelligence provides a new computing prototype that is totally different from conventional prototype. Mobile agents are automatically itinerating from one host Computer to another host computer and execute assigned task on the behalf of user in heterogeneous environment under own control. Because mobile agents roam around distributed networks automatically, the security of the agents and platforms is a major concern. The number of mobile agents-based software applications has increased dramatically over the past year. It has also enhanced the security risks associated with such applications. Most protection systems in the mobile agent paradigm focus on platform security and provide few guidelines for mobile agent security, which is still a challenging topic. There is a risk to information carries by mobile agents from the malicious mobile agents who can modify and steal the confidential information. In this paper proposed multilevel authentication framework of mobile agents and platform based on Lagrange interpolation and fast Fourier transformation (LIFFT). In this frame work ‘n’ number of mobile agent have two level of security first level key used authentication and second level of key used for execution of mobile agents.

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45

Miller, Kevin, and Gunjan Mansingh. "Comparing the Use of Mobile Intelligent Agents vs Client Server Approach in a Distributed Mobile Health Application." Journal of Computers 10, no. 6 (November 2015): 365–73. http://dx.doi.org/10.17706/jcp.10.6.365-373.

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46

Liu, Na, and Kun Liu. "Mobile Agents Build Web Information Retrieval System." Applied Mechanics and Materials 543-547 (March 2014): 3373–76. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.3373.

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In recent years, mobile agent has always been the hot spot of the academic research, this paper introduces the concept of mobile agent, mobile agent system architecture and key technologies, combined with the mobile technology and web information retrieval technology, design a model of information retrieval system based on mobile agent, and expounds the key technology to realize the model needs to solve.

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47

Macêdo, Raimundo J. Araújo, and Flávio M. Assis Silva. "The mobile groups approach for the coordination of mobile agents." Journal of Parallel and Distributed Computing 65, no. 3 (March 2005): 275–88. http://dx.doi.org/10.1016/j.jpdc.2004.10.001.

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48

Saleem, Hussain. "Mobile Agents: An Intelligent Multi-Agent System for Mobile Phones." IOSR Journal of Computer Engineering 6, no. 2 (2012): 26–34. http://dx.doi.org/10.9790/0661-0622634.

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49

Chung, Sheng-Hung, and Ean-Teng Khor. "Mobile Agents Approach for Transaction Processing in Mobile Database Systems – Mobile Learning Environment." Asian Association of Open Universities Journal 6, no. 1 (September 1, 2011): 74–83. http://dx.doi.org/10.1108/aaouj-06-01-2011-b008.

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This paper describes the architecture of using the Mobile Agent and ACID (Atomicity, Consistency, Isolation and Durability) in Mobile e-Learning (mLearning). In the coming years, there will be an incremental amount of mobile learning experiments for the purpose of implementing mobile ICTs into mainstream education. In this article, the Replication Agent and Snapshot Agent architecture is proposed as an effective way to overcome the problem of heavy loading on the limited bandwidth used in wireless transmission for mobile learning environment merge replication process. The implementation of mobile agents as middleware for mLearning environment is to provide database replication between learners and off-site database e.g., Knowledge Management Centre's (KMC) databases using handheld devices. The approach using the combination of both these agents plays an important role in wireless transmission. It provides an intelligent solution to the limitation of the wireless bandwidth by lowering the bandwidth taken up during the bursts of mobile transactions. In this proposed technique, a mLearning database is determined as a Snapshot publisher where a compact edition of files and information is generated at the snapshot location which resides on the central database server. Learners may retrieve quick bursts of information through mobile applications wirelessly. The Replication Agent offers the flexibility to move from one site (user) to another (central database) for essential data synchronization. In order to provide learners with appropriate courses, a prototype on mLearning platform supporting three-layered structure and device adapting was put forward. The architecture of the platform discussed in this study as the mobile agent approach would facilitate more widespread use of mLearning, including in courses discussions between learners and academicians.

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50

Abid, Khadija, L. Hayet Mouss, Okba Kazar, and Laid Kahloul. "A Novel Approach for Mobile Maintenance Using Mobile Agents Technology and Mobile Devices." Journal of Advanced Manufacturing Systems 14, no. 02 (April 27, 2015): 55–74. http://dx.doi.org/10.1142/s0219686715500055.

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The long use of a system causes its degradation. Hence, the maintenance activity is required in order to keep and improve the efficiency in the system. With the rapid development in networking technology, a need appears to change the manufacturing strategies. These new technologies improve the maintenance process, and establish remote maintenance (tele-maintenance, e-maintenance and m-maintenance). These kinds of maintenance try to provide personnel maintenance with the right information at the suitable time, which makes information available, anywhere and anytime. Our proposition is the use of mobile agent technology to reduce the maintenance costs and solve the problem of the unavailability of an expert in all phases of condition-based maintenance (CBM) strategy. The mobile agent technology overcomes a lot of problems and there is not much work that has used this technology. We have also used the web services (WS) to insure interoperability between machines and to support interaction over the network. Our approach gives great support to the maintenance engineer as it facilitates the access to decision-making support, work order, etc. which are available in the device like smartphone. This paper presents the development of a mobile maintenance support system based on mobile agent technology. The proposed system, the web and agent technology as well as remote communication were tested successfully.

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