Mobility-aware medium access control protocols for wireless sensor networks: A survey

Zareei, Mahdi; Islam, A. K. M. Muzahidul; Vargas-Rosales, César; Mansoor, Nafees; Goudarzi, Shidrokh; Rehmani, Mubashir Husain

doi:10.1016/j.jnca.2017.12.009

Cited by 51 publications

(23 citation statements)

References 54 publications

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“…Each node transmits the packet having the size of 50 bytes. The MAC protocol as in Xie et al [10,50] is used, which advances packets are on the free channel and drops them when congestion occurs even after attempting predefined multiple times. Energy of 10 J energy is assigned to every node, except in the proposed schemes that assign more energy to low depth nodes to avoid their early death.…”

Section: Simulation Settingsmentioning

confidence: 99%

Energy Balanced Localization-Free Cooperative Noise-Aware Routing Protocols for Underwater Wireless Sensor Networks

et al. 2019

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Owing to the harsh and unpredictable behavior of the sea channel, network protocols that combat the undesirable and challenging properties of the channel are of critical significance. Protocols addressing such challenges exist in literature. However, these protocols consume an excessive amount of energy due to redundant packets transmission or have computational complexity by being dependent on the geographical positions of nodes. To address these challenges, this article designs two protocols for underwater wireless sensor networks (UWSNs). The first protocol, depth and noise-aware routing (DNAR), incorporates the extent of link noise in combination with the depth of a node to decide the next information forwarding candidate. However, it sends data over a single link and is, therefore, vulnerable to the harshness of the channel. Therefore, routing in a cooperative fashion is added to it that makes another scheme called cooperative DNAR (Co-DNAR), which uses source-relay-destination triplets in information advancement. This reduces the probability of information corruption that would otherwise be sent over a single source-destination link. Simulations-backed results reveal the superior performance of the proposed schemes over some competitive schemes in consumed energy, packet advancement to destination, and network stability.

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Section: Simulation Settingsmentioning

confidence: 99%

Energy Balanced Localization-Free Cooperative Noise-Aware Routing Protocols for Underwater Wireless Sensor Networks

et al. 2019

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“…It comprises idle nodes as well as active nodes. In on-demand wake-up approach, the node is inactive for 10 seconds then it will go into inactive state and after 60 sec it wakes up for activity [10][11] [13]. If is there any activity for that node, it completes that activity and wait for 10 sec and so on.…”

Section: Case 3: Shift Activity Of a Nodementioning

confidence: 99%

Mobility Aware Clustering Routing Algorithm (MACRON) to improve lifetime of Wireless Sensor Network

Bhandai¹,

Sekhar²

2019

IJRTE

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In wireless sensor network energy consumption is the recent research trend. Sleep scheduling and clustering of nodes in mobile environment are two different approaches adopted to elongate the life of network. In this paper Mobility Aware Clustering routing algorithm (MACRON) is proposed by integrating two challenging approaches. In the sleep scheduling approach, the node takes the decision for their states independently in decentralized manner. Using this reward based approach; the node decides its own current state (sleep, wake, idle) and it also predict the state of neighbors without communicating with neighbors. The performance improvement of sleep scheduling algorithm is significant but, to enhance performance it should be integrated with clustering approaches. To support the mobility in wireless sensor network various MAC protocol has been proposed, but they consume huge energy for data transmission. The proposed MACRON algorithm works efficiently in both mobile and stationary network. The performance of proposed algorithm gives decent outcome in varying size of nodes ranging from 10 to 40 in ns-2.

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“…In [17], the authors proposed geometric model for mobile sink which has performed very well on various performance matrices. In [1,13], TTDD protocol is designed where WSN is partitioned into virtual grids based upon the mobile sink node. The path for mobile sink is based upon the grid node [18,19] which eliminated the hot spot problem.…”

Section: Related Workmentioning

confidence: 99%

“…Due to multihop communication, generally the sensor nodes which are near to base stations always become overloaded because they are intermediate nodes between base station and remaining wireless sensor network for data forwarding to the base station [1]. This situation happens to be a hot spot problem [2,3] where SNs near to sink node send their own data as well as other nodes data.…”

Section: Introductionmentioning

confidence: 99%

Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

Soni

Shrivastava

2018

Wireless Communications and Mobile Computing

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Generally, wireless sensor network is a group of sensor nodes which is used to continuously monitor and record the various physical, environmental, and critical real time application data. Data traffic received by sink in WSN decreases the energy of nearby sensor nodes as compared to other sensor nodes. This problem is known as hot spot problem in wireless sensor network. In this research study, two novel algorithms are proposed based upon reinforcement learning to solve hot spot problem in wireless sensor network. The first proposed algorithm RLBCA, created cluster heads to reduce the energy consumption and save about 40% of battery power. In the second proposed algorithm ODMST, mobile sink is used to collect the data from cluster heads as per the demand/request generated from cluster heads. Here mobile sink is used to keep record of incoming request from cluster heads in a routing table and visits accordingly. These algorithms did not create the extra overhead on mobile sink and save the energy as well. Finally, the proposed algorithms are compared with existing algorithms like CLIQUE, TTDD, DBRkM, EPMS, RLLO, and RL-CRC to better prove this research study.

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Mobility-aware medium access control protocols for wireless sensor networks: A survey

Cited by 51 publications

References 54 publications

Energy Balanced Localization-Free Cooperative Noise-Aware Routing Protocols for Underwater Wireless Sensor Networks

Energy Balanced Localization-Free Cooperative Noise-Aware Routing Protocols for Underwater Wireless Sensor Networks

Mobility Aware Clustering Routing Algorithm (MACRON) to improve lifetime of Wireless Sensor Network

Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

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