Hybrid Recovery Strategy Based on Random Terrain in Wireless Sensor Networks

Wang, Xiaoding; Xu, Li; Zhou, Shuming; Wu, Wei

doi:10.1155/2017/5807289

Cited by 16 publications

(24 citation statements)

References 26 publications

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“…is technique is further enhanced by the proximity factor to the node failure and then using PADRA for the optimization of the cascaded relocation in intrapartition [19,20]. e technique in [21] is based on incomplete sensor failure information. e assumption of this work is to equip nodes with cameras to collect topology facts (normally the numeral of end nodes).…”

Section: Related Workmentioning

confidence: 99%

Quality of Service-Based Node Relocation Technique for Mobile Sensor Networks

Awan

Khan

Malik

et al. 2019

Wireless Communications and Mobile Computing

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Wireless sensor networks (WSNs) deployed in harsh and unfavorable environments become inoperable because of the failure of multiple sensor nodes. This results into the division of WSNs into small disjoint networks and causes stoppage of the transmission to the sink node. Furthermore, the internodal collaboration among sensor nodes also gets disturbed. Internodal connectivity is essential for the usefulness of WSNs. The arrangement of this connectivity could be setup at the time of network startup. If multiple sensor nodes fail, the tasks assigned to those nodes cannot be performed; hence, the objective of such WSNs will be compromised. Recently, different techniques for repositioning of sensor nodes to recover the connectivity have been proposed. Although capable to restore connectivity, these techniques do not focus on the coverage loss. The objective of this research is to provide a solution for both coverage and connectivity via an integrated approach. A novel technique to reposition neighbouring nodes for multinode failure is introduced. In this technique, neighbouring nodes of the failed nodes relocate themselves one by one and come back to their original location after some allocated time. Hence, it restores both prefailure connectivity and coverage. The simulations show our proposed technique outperforms other baseline techniques.

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Section: Related Workmentioning

confidence: 99%

Quality of Service-Based Node Relocation Technique for Mobile Sensor Networks

Awan

Khan

Malik

et al. 2019

Wireless Communications and Mobile Computing

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“…A hybrid recovery strategy based on random terrain (HRSRT) to restore the connectivity of damaged WSNs is proposed in [12]. The influence of realistic terrain is planned by mapping the area of interest into a grid of equal sized cells.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Calculate ( reng ( )) (5) if ( reng ( )) < threshold then (6) //Send energy alert message to neighboring nodes (Nbr j ) (7) energy alert (Nbr j ) (8) For each neighboring node Nbr j of n i (9) //Neighboring node will increase its transmission range (10) recovery offered (Nbr j ) (11) end if (12) if reng ( ) < threshold then (13) Send energy defficiency message to slave keeper (14) Send activity time message to master keeper (15) Send activity granted message from master keeper have sufficient energy, then the total number of iterations (best score) required to execute the algorithm is (n × E). If the number of slave keepers is s, then the total executions required will be {(n × E) × s}.…”

Section: Complexitymentioning

confidence: 99%

Intelligent On‐Demand Connectivity Restoration for Wireless Sensor Networks

Mahmood

Khan

Hassan

et al. 2018

Wireless Communications and Mobile Computing

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Wireless sensor networks are envisioned to play a very important role in the Internet of Things in near future and therefore the challenges associated with wireless sensor networks have attracted researchers from all around the globe. A common issue which is well studied is how to restore network connectivity in case of failure of single or multiple nodes. Energy being a scarce resource in sensor networks drives all the proposed solutions to connectivity restoration to be energy efficient. In this paper we introduce an intelligent on-demand connectivity restoration technique for wireless sensor networks to address the connectivity restoration problem, where nodes utilize their transmission range to ensure the connectivity and the replacement of failed nodes with their redundant nodes. The proposed technique helps us to keep track of system topology and can respond to node failures effectively. Thus our system can better handle the issue of node failure by introducing less overhead on sensor node, more efficient energy utilization, better coverage, and connectivity without moving the sensor nodes.

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“…According to the classification of the cost, there exist two major types of restoration strategies [ 1 ]. One utilizes the least number of relay devices (i.e., RNs and MDCs) to federate disconnected components [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ], while the other one pursues the minimum energy consumption influenced by realistic terrains [ 19 , 20 , 21 , 22 , 23 ].…”

Section: Related Workmentioning

confidence: 99%

“…On the other hand, another type of connectivity restoration strategy pursues the minimum energy consumption influenced by a variety of realistic terrains (e.g., mountain, river, forest, swamp, etc.) [ 19 , 20 , 21 , 22 , 23 ]. In this paper, the connectivity restoration strategy with minimum RN consumption is developed.…”

Section: Introductionmentioning

confidence: 99%

A Straight Skeleton Based Connectivity Restoration Strategy in the Presence of Obstacles for WSNs

Wang

Zhou

2017

Sensors

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Connectivity has significance in both of data collection and aggregation for Wireless Sensor Networks (WSNs). Once the connectivity is lost, relay nodes are deployed to build a Steiner Minimal Tree (SMT) such that the inter-component connection is reestablished. In recent years, there has been a growing interest in connectivity restoration problems. In previous works, the deployment area of a WSN is assumed to be flat without obstacles. However, such an assumption is not realistic. In addition, most of the existing strategies chose the representative of each component, which serves as the starting point of relay node deployment during the connectivity restoration, either in a random way or in the shortest-distance based manner. In fact, both ways of representative selection could potentially increase the length of the SMT such that more relay nodes are required. In this paper, a novel connectivity restoration strategy is proposed—Obstacle–Avoid connectivity restoration strategy based on Straight Skeletons (OASS), which employs both the polygon based representative selection with the presence of obstacles and the straight skeleton based SMT establishment. The OASS is proved to be a 3-opt approximation algorithm with the complexity of O(nprefixlogn), and the approximation ratio can reduce to 332 while it satisfies a certain condition. The theoretical analysis and simulations show that the performance of the OASS is better than other strategies in terms of the relay count and the quality of the established topology (i.e., distances between components, delivery latency and balanced traffic load) as well.

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Hybrid Recovery Strategy Based on Random Terrain in Wireless Sensor Networks

Cited by 16 publications

References 26 publications

Quality of Service-Based Node Relocation Technique for Mobile Sensor Networks

Quality of Service-Based Node Relocation Technique for Mobile Sensor Networks

Intelligent On‐Demand Connectivity Restoration for Wireless Sensor Networks

A Straight Skeleton Based Connectivity Restoration Strategy in the Presence of Obstacles for WSNs

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