Topology control through depth adjustment and transmission power control for UWSN routing protocols

Jouhari, Mohammed; Ibrahimi, Khalil; Benattou, Mohammed

doi:10.1109/wincom.2015.7381310

Cited by 14 publications

(6 citation statements)

References 8 publications

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“…By topology control in PP-JTCSR, the most stable and shortest path can be found. In [38], the authors investigate the impact of two topology control methods for resolving the problem of void/isolated nodes appeared in geographic routing protocols, which can reduce the number of void/isolated nodes significantly. In [39], the authors have shown that joint topology control and routing assignment as an optimization problem is a NP-hard problem.…”

Section: Rlated Workmentioning

confidence: 99%

Cross-Layer and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

Li¹,

Martínez-Ortega²,

Díaz³

2018

IEEE Sensors J.

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For improving the efficiency and the reliability of the opportunistic routing algorithm, in this paper, we propose the cross-layer and reliable opportunistic routing algorithm (CBRT) for Mobile Ad Hoc Networks, which introduces the improved efficiency fuzzy logic and humoral regulation inspired topology control into the opportunistic routing algorithm. In CBRT, the inputs of the fuzzy logic system are the relative variance (rv) of the metrics rather than the values of the metrics, which reduces the number of fuzzy rules dramatically. Moreover, the number of fuzzy rules does not increase when the number of inputs increases. For reducing the control cost, in CBRT, the node degree in the candidate relays set is a range rather than a constant number. The nodes are divided into different categories based on their node degree in the candidate relays set. The nodes adjust their transmission range based on which categories that they belong to. Additionally, for investigating the effection of the node mobility on routing performance, we propose a link lifetime prediction algorithm which takes both the moving speed and moving direction into account. In CBRT, the source node determines the relaying priorities of the relaying nodes based on their utilities. The relaying node which the utility is large will have high priority to relay the data packet. By these innovations, the network performance in CBRT is much better than that in ExOR; however, the computation complexity is not increased in CBRT. 

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Section: Rlated Workmentioning

confidence: 99%

Cross-Layer and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

Li¹,

Martínez-Ortega²,

Díaz³

2018

IEEE Sensors J.

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“…The literature on the selection of transmission power levels in WSNs is growing day-to-day [7,[20][21][22][23][24][25][26][27][28]. In [20], the authors proposed a distributed power controlled contention-based medium access control (MAC) layer protocol for WSNs.…”

Section: Related Workmentioning

confidence: 99%

“…In [25], discrete TPC and rate adaption algorithms were proposed for ultrareliable machine-to-machine control applications, in which a finite set of transmit rates is only supported with cardinality 4 and 8. In [26], two topology control techniques (i.e. depth adjustment and TPC) for geographic routing in underwater WSNs were studied.…”

Section: Related Workmentioning

confidence: 99%

“…In summary, in the literature on determining the optimal transmission power levels set, some works aimed to maximize the throughput of the network [10, 12-14, 16, 19, 27], while some others focused on the minimization of the energy consumption in the network [18,20,21,24,26,28]. There are also several studies considering other important performance metrics such as link quality [17,22,23], concurrent transmission time [25], average spectral density [15], and accuracy of localization [11].…”

Section: Related Workmentioning

confidence: 99%

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The impact of transmission power levels set size on lifetime of wireless sensor networks in smart grids

Yildiz¹

2018

Turk J Elec Eng & Comp Sci

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Wireless sensor networks (WSNs) have been confirmed as one of the most promising technologies for many smart grid (SG) applications due to their low complexity and inexpensive costs. A typical WSN is formed with numerous battery limited sensor nodes mounted on critical components of a SG system for monitoring applications. Acquired monitoring data by sensor nodes are conveyed to the base station generally by using multihop communication techniques. WSN-based SG applications encounter severe propagation losses due to extreme channel conditions of the SG environment. In order to reduce possible packet errors caused by channel variations, transmission power control approaches can be adopted where the set size of available transmission power levels differs among the utilized hardware platforms. Usage of low transmission power levels can reduce the energy dissipation of nodes, which may lead to high packet drops. On the other hand, usage of high transmission power levels can prevent packet errors. Nonetheless, this alternative solution may lead to premature death of sensor nodes. Depending on the networking conditions, it is possible to confront applications such that the utilization of all available power levels provided by the node hardware may be unnecessary. In order to overcome this issue, determination of optimal transmission power levels set size for WSN-based SG applications becomes a critical research topic to prolong the network lifetime. In this work, we propose an optimization model to maximize the network lifetime while limiting the size of the transmission power levels set. Furthermore, we propose two strategies that are built on top of the optimization model to investigate the impact of the most used and optimal power levels on WSN lifetime considering several SG environments under various networking conditions.

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“…The synchronization is needed even if the node is in failures or movement to maintain the transmission schedule. In our paper, we resolved the issue of failed nodes using topology control through movement assisted and transmission power. During the communication process, some nodes drain their residual energy and break down, for this some nodes lose their connection with the sonobuoys.…”

Section: Introductionmentioning

confidence: 99%

Signaling game approach to improve the MAC protocol in the underwater wireless sensor networks

Jouhari

Ibrahimi

Tembiné

et al. 2019

Int J Communication

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Summary Underwater sensor networks (UWSNs) are instructed for critical applications like military surveillance and underwater oil spills that conducted in a very massive three‐dimensional (3‐D) space that needs many underwater nodes (UNs) to cover the target area. Those UNs are not easy to recharge and cannot exploit solar power. MAC protocols deployed for UWSN ought to consider the energy efficiency, so as, to extend the network lifetime with total connectivity and significant throughput. Terrestrial MAC protocols could not be used for UWSN due to long and unpredictable propagation delay. Consequently, the development of a new MAC protocol for the harsh environment as underwater is a challenging task. In this study, we focus on the deployment of TDMA in UWSN for this, two schemes entitled TDMA slot sharing (TSS) and free time slots reallocation (FTSR) are proposed. Received data stored in the buffer waiting for processing and forwarding might lead to an unlimited data transfer latency those results in the buffer overflow. Otherwise, free time slots appearing during the communication process resulting from dead nodes increase uselessly sleep time for the rest of the nodes. Both schemes based on signaling game are proposed to overcome those problems, TSS is used to enable the slot sharing between UNs during the communication process to reduce the buffer overflow. FTSR scheme aims to increase the throughput of UNs by allowing the reuse of free time slots. Numerical results conducted in this work show good improvement in the network performance concerning throughput.

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Topology control through depth adjustment and transmission power control for UWSN routing protocols

Cited by 14 publications

References 8 publications

Cross-Layer and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

Cross-Layer and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

The impact of transmission power levels set size on lifetime of wireless sensor networks in smart grids

Signaling game approach to improve the MAC protocol in the underwater wireless sensor networks

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