Bloom filter–based efficient broadcast algorithm for the Internet of things
In the Internet of things, a large number of objects can be embedded over a region of interest where almost every device is connected to the Internet. This work scrutinizes the broadcast overhead problem in an Internet of things network, containing a very large number of objects. The work proposes a...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-12-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717749744 |
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| _version_ | 1832546749738123264 |
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| author | Anum Talpur Faisal K Shaikh Thomas Newe Adil A Sheikh Emad Felemban Abdelmajid Khelil |
| author_facet | Anum Talpur Faisal K Shaikh Thomas Newe Adil A Sheikh Emad Felemban Abdelmajid Khelil |
| author_sort | Anum Talpur |
| collection | DOAJ |
| description | In the Internet of things, a large number of objects can be embedded over a region of interest where almost every device is connected to the Internet. This work scrutinizes the broadcast overhead problem in an Internet of things network, containing a very large number of objects. The work proposes a probabilistic structure (bloom filter)-based technique, which uses a new broadcast structure that attempts to reduce the number of duplicate copies of a packet at every node. This article utilizes a clustering concept to make the broadcast efficient in terms of memory space, broadcast overhead, and energy usage. The unique idea of a bloom-based network uses a filter to incorporate neighbor information when taking a forwarding decision to reduce broadcast overhead. The simulation results show that parallel broadcasting among different clusters and the use of a bloom filter can achieve a reduction in broadcast overhead from hundreds to ones and tens, when compared with a conventional non-bloom-based broadcast algorithm and a bloom-based algorithm. In addition, it helps to reduce energy usage evenly throughout the network, 1/100 times, when compared with conventional broadcast (non-bloom-based) and, 1/10 times, when compared with bloom-based broadcast. This increases the lifetime of a network by having control over network density usage and communications overhead as a result of broadcasting. |
| format | Article |
| id | doaj-art-9853e4b589854b27901e8a4d9487933d |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-9853e4b589854b27901e8a4d9487933d2025-02-03T06:47:19ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-12-011310.1177/1550147717749744Bloom filter–based efficient broadcast algorithm for the Internet of thingsAnum Talpur0Faisal K Shaikh1Thomas Newe2Adil A Sheikh3Emad Felemban4Abdelmajid Khelil5Department of Telecommunication Engineering, Mehran UET, Jamshoro, PakistanDepartment of Telecommunication Engineering, Mehran UET, Jamshoro, PakistanUniversity of Limerick, Limerick, IrelandUmm Al-Qura University, Mecca, Saudi ArabiaUmm Al-Qura University, Mecca, Saudi ArabiaUniversity of Applied Sciences Landshut, Landshut, GermanyIn the Internet of things, a large number of objects can be embedded over a region of interest where almost every device is connected to the Internet. This work scrutinizes the broadcast overhead problem in an Internet of things network, containing a very large number of objects. The work proposes a probabilistic structure (bloom filter)-based technique, which uses a new broadcast structure that attempts to reduce the number of duplicate copies of a packet at every node. This article utilizes a clustering concept to make the broadcast efficient in terms of memory space, broadcast overhead, and energy usage. The unique idea of a bloom-based network uses a filter to incorporate neighbor information when taking a forwarding decision to reduce broadcast overhead. The simulation results show that parallel broadcasting among different clusters and the use of a bloom filter can achieve a reduction in broadcast overhead from hundreds to ones and tens, when compared with a conventional non-bloom-based broadcast algorithm and a bloom-based algorithm. In addition, it helps to reduce energy usage evenly throughout the network, 1/100 times, when compared with conventional broadcast (non-bloom-based) and, 1/10 times, when compared with bloom-based broadcast. This increases the lifetime of a network by having control over network density usage and communications overhead as a result of broadcasting.https://doi.org/10.1177/1550147717749744 |
| spellingShingle | Anum Talpur Faisal K Shaikh Thomas Newe Adil A Sheikh Emad Felemban Abdelmajid Khelil Bloom filter–based efficient broadcast algorithm for the Internet of things International Journal of Distributed Sensor Networks |
| title | Bloom filter–based efficient broadcast algorithm for the Internet of things |
| title_full | Bloom filter–based efficient broadcast algorithm for the Internet of things |
| title_fullStr | Bloom filter–based efficient broadcast algorithm for the Internet of things |
| title_full_unstemmed | Bloom filter–based efficient broadcast algorithm for the Internet of things |
| title_short | Bloom filter–based efficient broadcast algorithm for the Internet of things |
| title_sort | bloom filter based efficient broadcast algorithm for the internet of things |
| url | https://doi.org/10.1177/1550147717749744 |
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