A New Method of Mobile Ad Hoc Network Routing Based on Greed Forwarding Improvement Strategy

Zhang, Degan; Zhao, Pengzhen; Cui, Yu-ya; Chen, Lü; Zhang, Ting; Wu, Hao

doi:10.1109/access.2019.2950266

Cited by 84 publications

(47 citation statements)

References 45 publications

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“…The MANET researches focus on the routing protocol, QoS, energy management, etc. Zhang et al [40] proposed a new greedy forwarding improvement routing method for MANET to calculate the reliable communication area and evaluate the quality of the link according to the relative displacement between the nodes and the maintenance time of the link. Sharifi and Babamir [41] presented a new clustering method and considered the good performance of Evolutionary Algorithms (EAs) good in finding proper head clusters and a specific EA-based method named Imperialist Competitive Algorithm (ICA) via numerical coding by considering the high efficiency of clustering methods among the routing algorithms.…”

Section: Mobile Ad Hoc Networkmentioning

confidence: 99%

Dispersed Computing for Tactical Edge in Future Wars: Vision, Architecture, and Challenges

Yang

Sun

et al. 2021

Wireless Communications and Mobile Computing

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In the future, the tactical edge is far away from the command center, the resources of communication and computing are limited, and the battlefield situation is changing rapidly, which leads to the weak connection and fast changes of network topology in a harsh and complex battlefield environment. Thus, to meet the needs of communication and computing to build a new generation of computing architecture for real-time sharing and service collaboration of tactical edge resources to win the future war, the dispersed computing (DCOMP) seeks a new solution to satisfy the requirements of fast and efficient sensing, transmission, integrating, scheduling, and processing of various information in the tactical edge. Through the research of a traditional computing paradigm of mobile cloud computing (MCC), fog computing (FC), mobile edge computing (MEC), mobile ad hoc network (MANET), etc., it can be found that these computations have difficulty in meeting the high changing and complex battlefield environment and we propose a novel architecture of DCOMP to build a scalable, extensible, and robust decision-making system, to realize powerful and secure communication, computing, storage, and information processing capabilities for the tactical edge. We illustrate the fundamental principles of building a network model, channel allocation, and forwarding control mechanism of the network architecture for DCOMP called DANET and then design a new architecture, programming model, task awareness, and computing scheduling for DCOMP. Finally, we discuss the main requirements and challenges of DCOMP in future wars.

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Section: Mobile Ad Hoc Networkmentioning

confidence: 99%

Dispersed Computing for Tactical Edge in Future Wars: Vision, Architecture, and Challenges

Yang

Sun

et al. 2021

Wireless Communications and Mobile Computing

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“…For resource‐constrained MANET, the authors in Reference proposed a greedy forwarding‐based routing method for MANET. Their approach computes reliable communication links by evaluating the quality of each link using the quality of the link, the distance between the source node and the destination node, and the number of the neighboring nodes.…”

Section: Related Workmentioning

confidence: 99%

Mobility and energy prediction models: Approach toward effective route management in mobile wireless sensor networks

Olakanmi

Odeyemi

Abbas

2020

Engineering Reports

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Mobile wireless sensor network (MWSN), as a backbone of most communication and embedded systems, is characterized by low data delivery as a result of the energy constraint and in‐deterministic movement of the nodes. To select optimal route path for a reliable data routing, protocols need to select neighbouring nodes with low mobility and residual energy parameters along the route. However, obtaining these parameters from the targeted nodes may encourage mischievous nodes to manipulate their energy and mobility parameters in their favor, leading to the selection of non‐optimal route path and/or exposing the network to other attacks. Rather than depending on the targeted nodes for these parameters, they can be accurately and securely obtained by sink node or base station using effective predictive models. However, most of the existing predictive models engaged by MWSN routing protocols either provide only the energy level or mobility factor of the nodes for optimal route path selection. This, therefore, reduces the reliability of the obtained optimal route paths in terms of data delivery. In this article, we propose predictive models for an accurate prediction of mobility and residual energy parameters of nodes in MWSN for efficient route management. The models are simulated on an existing MWSN protocol to determine their performance. The simulation results show that the adoption of these models in the development of routing protocol will not only lead to optimal route paths' selection but also enhance data delivery rate in MWSN.

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“…Finally, the neighbor node rotates and becomes a new CH for a random time slice, which can effectively reduce CH mortality rate, extend cluster lifetime, and improve data transmission efficiency.The proposed method is more effective in saving network energy, improving data transmission efficiency, and maximizing network lifetime of the RWSN for smart home or smart community. The topic in this paper is a multi-objective optimization problem, which means that a mathematical optimization model is needed to be used [46][47][48][49][50][51][52][53][54][55].…”

Section: Related Workmentioning

confidence: 99%

“…As one of many scenarios for residential energy management of RWSN [38][39][40][41][42], the proposed method was tested in the residential environment of smart home or smart community [47][48][49][50][51][52][53][54][55]. According to related statistics, many gas explosions occur every year, which cause huge economic losses and casualties.…”

Section: C) Tests With Real Scenariosmentioning

confidence: 99%

New Approach of Energy-Efficient Hierarchical Clustering Based on Neighbor Rotation for RWSN

Chen

Zhang

et al. 2020

IEEE Access

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Energy Efficient Hierarchical Clustering (EEHC) method is a distributed random clustering algorithm for residential wireless sensor networks (RWSNs) with the goal of maximizing network lifetime. However, during selection of the cluster head stage, a node declares itself as a cluster head to neighboring nodes with probability p, which does not consider well the topological characteristics of the network. The new energy-efficient hierarchical clustering approach based on neighbor rotation (EEHCN) for RWSN has been proposed in this paper, the new idea of which determines whether a node of RWSN can become a cluster head node by comparing the comprehensive weighting of the degree of the sensor node and the distance between the sensor node and the center of the subarea. When the cluster head is replaced, a member node in the set of neighbor nodes of the current cluster head becomes the new cluster head for a random time slice, and the merged information is transmitted to the nearest sink node in a multi-hop manner according to the routing information. The experimental results demonstrate that the proposed method is more effective in saving network energy, improving data transmission efficiency, and maximizing network lifetime of RWSN. The innovative research work is very useful for the relative application of the RWSN, such as smart home or smart community.

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A New Method of Mobile Ad Hoc Network Routing Based on Greed Forwarding Improvement Strategy

Cited by 84 publications

References 45 publications

Dispersed Computing for Tactical Edge in Future Wars: Vision, Architecture, and Challenges

Dispersed Computing for Tactical Edge in Future Wars: Vision, Architecture, and Challenges

Mobility and energy prediction models: Approach toward effective route management in mobile wireless sensor networks

New Approach of Energy-Efficient Hierarchical Clustering Based on Neighbor Rotation for RWSN

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