A Survey on Mobile Agent Itinerary Planning for Information Fusion in Wireless Sensor Networks
In wireless sensor networks (WSNs), mobile agent (MA) is a new paradigm that has gained more attention lately. In this paradigm, MA migrates among sensor nodes (SNs) for data fusion. However, in comparison to traditional client/server paradigm; where each SN in the network sends its collected data t...
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| Published in | Archives of computational methods in engineering Vol. 28; no. 3; pp. 1323 - 1334 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Dordrecht
Springer Netherlands
01.05.2021
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1134-3060 1886-1784 |
| DOI | 10.1007/s11831-020-09417-1 |
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| Abstract | In wireless sensor networks (WSNs), mobile agent (MA) is a new paradigm that has gained more attention lately. In this paradigm, MA migrates among sensor nodes (SNs) for data fusion. However, in comparison to traditional client/server paradigm; where each SN in the network sends its collected data to the sink, MA presents a good alternative in terms of energy consumption, response time and network lifetime. In this paradigm, the most critical properties of MA is the itinerary planning, it has always been an issue and a NP-hard problem. In this paper, we present a survey of the proposed itinerary planning approaches for MAs in WSNs. MA itinerary planning techniques can be classified into three categories: static itinerary planning, dynamic itinerary planning and hybrid itinerary planing. The benefits and shortcomings of different MA itinerary planning approaches are presented. Furthermore, we implement, simulate and compare the most prominent itinerary planning algorithms upon a common parameter space, making realistic network-level assumptions. |
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| AbstractList | In wireless sensor networks (WSNs), mobile agent (MA) is a new paradigm that has gained more attention lately. In this paradigm, MA migrates among sensor nodes (SNs) for data fusion. However, in comparison to traditional client/server paradigm; where each SN in the network sends its collected data to the sink, MA presents a good alternative in terms of energy consumption, response time and network lifetime. In this paradigm, the most critical properties of MA is the itinerary planning, it has always been an issue and a NP-hard problem. In this paper, we present a survey of the proposed itinerary planning approaches for MAs in WSNs. MA itinerary planning techniques can be classified into three categories: static itinerary planning, dynamic itinerary planning and hybrid itinerary planing. The benefits and shortcomings of different MA itinerary planning approaches are presented. Furthermore, we implement, simulate and compare the most prominent itinerary planning algorithms upon a common parameter space, making realistic network-level assumptions. |
| Author | El Makkaoui, Khalid Beni-hssane, Abderrahim Ouhmad, Slimane El Fissaoui, Mohamed |
| Author_xml | – sequence: 1 givenname: Mohamed surname: El Fissaoui fullname: El Fissaoui, Mohamed email: Elfissaoui.m@ucd.ac.ma organization: LAROSERI Laboratory, FS, Univ Chouaib Doukkali – sequence: 2 givenname: Abderrahim surname: Beni-hssane fullname: Beni-hssane, Abderrahim organization: LAROSERI Laboratory, FS, Univ Chouaib Doukkali – sequence: 3 givenname: Slimane surname: Ouhmad fullname: Ouhmad, Slimane organization: LAVETE Laboratory, FST, Univ Hassan 1 – sequence: 4 givenname: Khalid surname: El Makkaoui fullname: El Makkaoui, Khalid organization: Laboratory of IPOSI, Mathematics and Computer Science Department, National School of Applied Team of Modeling and Scientific Computing, FP, Univ Mohammed 1 |
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| CitedBy_id | crossref_primary_10_1007_s12243_024_01055_z crossref_primary_10_3390_s21010023 crossref_primary_10_1016_j_procs_2020_07_097 crossref_primary_10_1109_ACCESS_2020_3046619 crossref_primary_10_32604_cmc_2022_025582 crossref_primary_10_1155_2022_4865209 crossref_primary_10_62762_CJIF_2024_999646 crossref_primary_10_1007_s11831_021_09670_y crossref_primary_10_1007_s11277_021_09309_y crossref_primary_10_1007_s00607_021_00978_y crossref_primary_10_1007_s00500_021_05910_2 |
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| SubjectTerms | Agents (artificial intelligence) Algorithms Client server systems Data collection Data integration Energy consumption Engineering Mathematical and Computational Engineering Multisensor fusion Original Paper Planing Response time Sensors Wireless networks Wireless sensor networks |
| Title | A Survey on Mobile Agent Itinerary Planning for Information Fusion in Wireless Sensor Networks |
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