Minimizing Energy Expenditures using Genetic Algorithm for Scalability and Longlivety of Multi hop Sensor Networks

Abro, Adeel; Deng, Zhongliang; Memon, Kamran Ali; Mohammadani, Khalid Hussain; Ain, Noor Ul; Memon, Saleemullah; Memon, Imran; Panhwar, Muhammad Aamir

doi:10.1109/iceiec.2019.8784682

Cited by 8 publications

(9 citation statements)

References 9 publications

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“…This simulation is integrated with Simulation Urban Mobility (SUMO) for evaluation of runtime environment. For the simulation, we arrayed 10,000 different nodes randomly in the distance of 200 m, and IEEE 802.11 standard protocol was used for medium access [59] with the transmission speed of 8Mbps. The remaining parameters are shown in Table 2.…”

Section: Experimental and Evaluationmentioning

confidence: 99%

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

et al. 2021

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Many algorithms use clustering to improve vehicular ad hoc network performance. The expected points of many of these approaches support multiple rounds of data to the roadside unit and constantly include clustering in every round of single-hop data transmission towards the road side unit; however, the clustering in every round maximizes the number of control messages and there could be the possibility of collision and decreases in network energy. Multi-hop transmission prolongs the cluster head node’s lifetime and boosts the network’s efficiency. Accordingly, this article proposes a new fuzzy-clustering-based routing algorithm to benefit from multi-hop transmission clustering simultaneously. This research has analyzed the limitation of clustering in each round, different algorithms were used to perform the clustering, and multi-hop routing was used to transfer the data of every cluster to the road side unit. The fuzzy logic was used to choose the head node of each cluster. Three parameters, (1) distance of each node, (2) remaining energy, and (3) number of neighbors of every node, were considered as fuzzy criteria. The results of this research were compared to various other algorithms in relation to parameters like dead node in every round, first node expire, half node expire, last node expire, and the network lifetime. The simulation results show that the proposed approach outperforms other methods. On the other hand, the vehicular ad hoc network (VANET) environment is vulnerable at the time of data transmission. The NS-2 software tool was used to simulate and evaluate the proposed fuzzy logic opportunistic routing’s performance results concerning end-to-end delay, packet delivery, and network throughput. We compare to the existing protocols, such as fuzzy Internet of Things (IoT), two fuzzy, and Fuzzy-Based Driver Monitoring System (FDMS). The performance comparison also emphasizes an effective utilization of the resources. Simulations on the highway environment show that the suggested protocol has an improved Quality of Service (QoS) efficiency compared to the above published methods in the literature.

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Section: Experimental and Evaluationmentioning

confidence: 99%

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

et al. 2021

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“…The combination of BLF and the genetic algorithm will give full play to the advantage of intelligent optimization method for task processing sequence, which achieves the purpose of efficient utilization of limited time-frequency resources in a short time. 29…”

Section: Cross-network Radio Resource Scheduling Based On Multi-population Genetic Algorithm 41 | the Framework Of Cross-network Radio Rementioning

confidence: 99%

A novel scheme of cross‐network radio resources scheduling in SAGN based on unified resources mapping and genetic algorithm

Lin

et al. 2021

Int J Communication

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To decrease human deaths in the disaster and ensure the efficiency of emergency aid, high accuracy logistics can play an important role. To achieve this target, anytime and anywhere communications would contribute to rapid information interaction on situation monitoring of logistics. Space-air-ground network (SAGN) is the network combined with satellite network, aerial network, and territorial network, which can achieve global communication coverage. That means it would be a heterogeneous network, in which each network providing with different radio communication resources. If we would like to exploit the SAGN to achieve reliable support of communication, we have to solve the problems of the unified mapping of different radio communication resources. Besides, we should further design the exact scheduling scheme for the communication service of emergency logistics with global heterogeneous networks. Therefore, we propose a novel scheme of cross-network radio resources scheduling in SAGN based on unified resources mapping and genetic algorithm. First, we build the system model for SAGN in the scenario of emergency logistics. Second, the unified resource mapping method is proposed, which achieves global cross-network resources virtualization by the quality of service (QoS) bearer matching. Third, the multi-population genetic algorithm is introduced to relate with each network resource to achieve available virtual global radio communication resource scheduling. The simulation results show that the resource efficiency of this proposed scheme has a better performance compared with the other resource scheduling method, which increased by 11.8% compared with bottom-left (BL) algorithm.

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“…It means that sensor nodes are prepared well before the failure. References [7,18,23] are the examples of such approach. (c) Hybrid approach: in this approach, both reactive and proactive approaches are used.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Nodes Failure Recovery Management Algorithm for Mobile Sensor Networks

Jadoon

Awan

Khan

et al. 2020

Mathematical Problems in Engineering

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Wireless sensor networks are not prone to harsh environments and may fail due to various reasons. Failure of sensor nodes causes partitioning of network into various small segments and restricts the communication of nodes. Due to the significant importance of restoration mechanisms, many approaches have been proposed in the literature so far. However, these approaches do not focus on uniform distribution of sensor nodes before the occurrence of failure. This paper fulfills the shortcoming in the literature by proposing a Uniform Distribution and Recovery Algorithm (UDRA) in two parts. The first part (prefailure algorithm) focuses on preparing the mobile sensor nodes to be ready for the failure beforehand by maintaining half of their communication distance between them. Also, it uses a novel method of directional matrix based on one-hop information. By using this method, each mobile node declares itself as cut-vertex (CV), intermediate node, or leaf node. The second part of the algorithm (postfailure algorithm) gives complete recovery procedure in the network by its recovery nodes. The extensive simulations prove that the proposed algorithm supersedes the existing approaches.

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Minimizing Energy Expenditures using Genetic Algorithm for Scalability and Longlivety of Multi hop Sensor Networks

Cited by 8 publications

References 9 publications

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

A novel scheme of cross‐network radio resources scheduling in SAGN based on unified resources mapping and genetic algorithm

An Efficient Nodes Failure Recovery Management Algorithm for Mobile Sensor Networks

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