Amiri, Iraj Sadegh and Prakash, J. and Balasaraswathi, M. and Sivasankaran, V. and Sundararajan, T. V. P. and Hindia, M. H. D. Nour and Tilwari, Valmik and Dimyati, Kaharudin and Henry, Ojukwu (2020) DABPR: A large-scale internet of things-based data aggregation back pressure routing for disaster management. Wireless Networks, 26 (4, SI). pp. 2353-2374. ISSN 1022-0038, DOI https://doi.org/10.1007/s11276-019-02122-3.
Full text not available from this repository.Abstract
In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely ``information-fusion-based role assignment (InFRA)'' and ``data routing for in-network aggregation (DRINA)'', which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively.
| Item Type: | Article |
|---|---|
| Funders: | Engineering and Physical Sciences Research Council [Grant No: EP/P028764/1] |
| Uncontrolled Keywords: | IoTs; Cluster head; Data aggregation; Backpressure; Network coding; MADM |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 04 Nov 2024 08:16 |
| Last Modified: | 04 Nov 2024 08:16 |
| URI: | http://eprints.um.edu.my/id/eprint/36709 |
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