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node deployment Based on Extra Path Creation for Wireless Sensor Networks on Mountain Roads

IEEE COMMUNICATIONS LETTERS 2017年第11期21卷 2376-2379页

作者： Liu, Xuxun South China Univ Technol Coll Elect & Informat Engn Guangzhou 510641 Guangdong Peoples R China South China Univ Technol Key Lab Autonomous Syst & Network Control Minist Educ Guangzhou 510641 Guangdong Peoples R China

Wireless sensor networks on mountain roads will form winding and long transmission paths and accordingly result in centralized energy dissipation near the sink and large transmission delay. In this letter, we propose a node deployment scheme to settle the above-mentioned thorny issues. The core idea is to construct extra paths to the sink and achieve data diversion. Specifically, the places with relatively large transmission hops to the sink and also comparatively small distance away from it are selected as the starting points of the extra paths. This selection mechanism contributes to alleviating the energy holes and reducing the transmission delay. Finally, experimental simulations show the effectiveness and superiority of our deployment scheme.

关键词： Wireless sensor networks node deployment extra path mountain roads

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node deployment for wireless sensor networks based on improved multi-objective evolutionary algorithm

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INTERNATIONAL JOURNAL OF INTERNET PROTOCOL TECHNOLOGY 2017年第3期10卷 189-195页

作者： Wei, Kaibin Tianshui Normal Univ Tianshui 741000 Peoples R China

node deployment is a crucial issue for wireless sensor networks, and it significantly affects the performance of wireless sensor networks. In this paper, we proposed a novel node deployment algorithm for wireless sensor networks via solving the multi-objective optimisation problem. The aim of node deployment in WSN is to determine an optimal node arrangement satisfying two conditions: 1) Cover all targets in the sensing range;2) Reduce the number of wireless sensors. The main innovation of this paper is to optimise multiple objectives, such as average energy consumption, average sensitivity area and network reliability. To solve the multi-objective optimisation problem, we improve the MOEA/D method by: 1) using the uniform design to generate aggregation coefficient vectors;2) exploiting the simplified quadratic approximation to promote accuracy of the local search. Finally, simulation results demonstrate that the proposed algorithm outperforms other optimisation methods for all optimisation objectives.

关键词： node deployment wireless sensor networks WSN intelligent optimisation multi-objective optimisation decision vector

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node deployment in wireless sensor networks using the new multi-objective Levy flight bee algorithm

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IET WIRELESS SENSOR SYSTEMS 2020年第2期10卷 78-87页

作者： Hajizadeh, Nahid Javidan, Reza Shamsinejad, Pirooz Akbari, Reza Shiraz Univ Technol Dept Comp Engn & Informat Technol Shiraz Iran

Wireless sensor networks (WSNs) play a prominent role in the world of computer networks. WSNs rely on deployment as a basic requirement and an effective factor on the basic network services. In deployment, creating a balance between conflicting optimisation factors, e.g. connectivity and coverage, is a challenging and sophisticated issue, so that deployment turns into an NP-complete problem. The majority of existing researches has attempted to tackle this problem by applying classic single-objective metaheuristic algorithms in 2D small-scale uniform environments. In this study, a new hybrid multi-objective optimisation algorithm, which is constructed by the combination of multi-objective bee algorithms and Levy flight (LF) random walk is proposed to deal with the deployment problem in WSNs. For this purpose, two of the most important criteria, connectivity and coverage, have been considered as objectives. A series of experiments are carried out in large-scale non-uniform 3D environments, despite the fact that most of the present methods are applicable in small-scale uniform 2D environments. This study completely takes into account the stochastic behaviour of swarms, something that other papers do not consider. The evaluation results show that the multi-objective LF bee algorithm, in most cases, surpasses NSGAII, IBEA and SPEA2 algorithms.

关键词： wireless sensor networks genetic algorithms Pareto optimisation search problems computational complexity small-scale uniform environments hybrid multiobjective optimisation algorithm multiobjective bee algorithms Levy flight random walk deployment problem WSNs large-scale nonuniform 3D environments small-scale uniform 2D environments multiobjective LF bee algorithm SPEA2 algorithms node deployment wireless sensor networks multiobjective Levy flight bee algorithm computer networks basic network services conflicting optimisation factors sophisticated issue NP-complete problem single-objective metaheuristic algorithms

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node deployment of Wireless Sensor Networks in Long Narrow Area

Node Deployment of Wireless Sensor Networks in Long Narrow A...

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4th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2012)

作者： Sun, Xu-guang He, Jing-sha Yang, Ming-xin Sun, Xiao-ling Beijing Univ Technol Sch Comp Sci Beijing Peoples R China Beijing Univ Technol Sch Software Engn Beijing Peoples R China Inst Disaster Prevent Dept Disaster Informat Engn Langfang Shi Peoples R China

ISBN: (纸本)9783037852842

In this paper, we study the node deployment in long narrow area of wireless sensor networks. Currently, studies on node deployment of wireless sensor networks mostly concentrated in two-dimensional flat area and three-dimensional space area which are complicated or inapplicable for long narrow area. The significant difference of node deployment between long narrow area and two-dimensional area is that the nodes in two-dimensional monitored area can be deployed anywhere, while the nodes in long narrow area can only be deployed by side with the environmental constraints. Considering the coverage, connectivity and reliability, we give out the densities and numbers of needed nodes in node deployment scheme for both 1-connected cover and k-connected cover in long narrow area covered completely by sensor networks.

关键词： wireless sensor networks node deployment long narrow area coverage connectivity

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node deployment of Wireless Sensor Networks Based on MOEA/P Algorithm 13

Node Deployment of Wireless Sensor Networks Based on MOEA/P ...

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13th IEEE International Conference on Communication Software and Networks (ICCSN)

作者： Lv, Li Peng, Funan Chen, Weiru Wang, Jun Chinese Acad Sci Shenyang Inst Comp Technol Shenyang 110168 Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Shenyang Univ Chem Technol Sch Comp Sci & Technol Shenyang Peoples R China

ISBN: (纸本)9781665431828

node deployment is one of the most important research directions of WSN, and it is the precondition that wireless sensor network can realize the predetermined function. Reasonable node deployment strategy can optimize the topology of the network, improve the overall energy efficiency of the network, improve the service quality of the network, and also a prerequisite for a long life cycle. The research of sensor network node deployment technology has extremely important theoretical and practical value. Wireless sensor node deployment is defined as the multi-objective optimization problem, which can ensure the maximum network connectivity, maximize network coverage, minimize the total network energy consumption, minimize network cost and maximize the network life cycle. This paper focuses on the deployment of sensor nodes in two-dimensional planar area. Based on the multi-objective optimization MOEA/P algorithm, the node deployment scheme is realized, which can maximize coverage area and minimize cost. The experiment shows that the algorithm can effectively solve the multi-objective optimization problem in wireless sensor network deployment.

关键词： wireless sensor networks node deployment multi-objective optimization coverage

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Reliable Data Storage in Heterogeneous Wireless Sensor Networks by Jointly Optimizing Routing and Storage node deployment

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Tsinghua Science and Technology 2021年第2期26卷 230-238页

作者： Huan Yang Feng Li Dongxiao Yu Yifei Zou Jiguo Yu College of Computer Science and Technology Qingdao UniversityQingdao 266071China School of Computer Science and Technology Shandong UniversityQingdao 266237China School of Computer Science and Technology Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China Department of Computer Science the University of Hong KongHong Kong 999077China Shandong Computer Science Center(National Supercomputer Center in Jinan) Jinan 250014China

In the era of big data,sensor networks have been pervasively deployed,producing a large amount of data for various ***,because sensor networks are usually placed in hostile environments,managing the huge volume of data is a very challenging *** this study,we mainly focus on the data storage reliability problem in heterogeneous wireless sensor networks where robust storage nodes are deployed in sensor networks and data redundancy is utilized through coding *** minimize data delivery and data storage costs,we design an algorithm to jointly optimize data routing and storage node *** problem can be formulated as a binary nonlinear combinatorial optimization problem,and due to its NP-hardness,designing approximation algorithms is highly *** leveraging the Markov approximation framework,we elaborately design an efficient algorithm driven by a continuous-time Markov chain to schedule the deployment of the storage node and corresponding routing *** also perform extensive simulations to verify the efficacy of our algorithm.

关键词： reliable data storage routing node deployment heterogeneous sensor networks

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Double attribute based node deployment in wireless sensor networks using novel weight based clustering approach

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2022年第3期47卷 1-11页

作者： Manoharan, J. Samuel Sir Isaac Newton Coll Engn & Technol Dept ECE Nagapattinam 611102 Tamil Nadu India

In recent years, WSNs have become one of the fastest emerging networks. It enables a larger variety of applications in the real-time as well as automation industries. WSN applications are made up of a large count of sensor nodes that are distributed as per the application's requirements. Sensor nodes, depending on its manufacturing rationale, monitor, sense, receive, record, and transfer any type of data. Sensors are inexpensive, tiny, and have limited energy efficiency. Inefficient methods of utilizing this scarce battery power results in the death of nodes which consequently affects the lifetime of the entire network. The failure of nodes because of inadequate routing strategies reduces the network's lifespan and overall quality. Numerous previous research methodologies were applied to improve network lifespan and node connection together with communication dependability. Most of the solutions failed to deliver ideal performance in terms of improving overall QoS, which is a collective characteristic. In this research, a novel WBC approach for data gathering, node clustering, and load balancing in WSN is proposed. The functioning of the proposed model relies on the effective assignment of nodes to the communication task based on their weighted function computed based on the performance characteristic. Load balancing as well as data aggregation, are the two attributes effectively considered in this research work. The performance of the suggested WBC is compared to traditional benchmark techniques using the NS2 program. Multiple measures have been calculated and studied, and in every case, the suggested WBC outperforms.

关键词： node deployment wireless sensor networks clustering data gathering energy efficiency novel weight based clustering approach

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Efficient physical intrusion detection in Internet of Things: A node deployment approach

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COMPUTER NETWORKS 2019年第May 8期154卷 28-46页

作者： Halder, Subir Ghosal, Amrita Conti, Mauro Univ Padua Dept Math Padua Italy

In Internet of Things (IoT), intrusion detection plays an important role in many applications for detecting malicious intruders. The intruder can be, an unexpected physically moving entity, invading an area under surveillance, or an adversary in a battlefield. node deployment strategy plays a crucial role in determining the intrusion detection capability of an loT network. With uniform deployment, the detection probability is the same for any location in the network area. Nevertheless, different applications may need diverse levels of detection probability at key areas within the network. For example, a battlefield surveillance application needs improved detection probability around the headquarter. On the contrary, a Gaussian deployment strategy provides improved detection probability to the key areas due to differentiated node density. However, it is neither energy-efficient nor provides a quick detection of the physical intruder. In this work, we introduce a novel deployment strategy to overcome the above said limitations of both uniform and Gaussian deployments for energy-efficient and quick detection. Initially, we investigate the problem of physical intrusion detection in our introduced deployment strategy considering a realistic sensing model. Furthermore, we examine the effects of different network parameters on the detection probability in details. We also derive the relationship between the different network parameters and connectivity to ensure fast detection. We perform exhaustive experiments on real datasets, primarily, in order to validate the correctness of modeling and analyses. Next, we examine the effects of different network parameters on the detection probability. The results clearly demonstrate that our approach improves the detection probability by more than 25% when compared to two well-known deployment strategies under various network parameters. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Gaussian distribution Internet of Things Network connectivity node deployment Physical intrusion detection

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Maximizing coverage and maintaining connectivity in WSN and decentralized IoT: an efficient metaheuristic-based method for environment-aware node deployment

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NEURAL COMPUTING & APPLICATIONS 2023年第1期35卷 611-641页

作者： Nematzadeh, Sajjad Torkamanian-Afshar, Mahsa Seyyedabbasi, Amir Kiani, Farzad Nisantasi Univ Fac Engn & Architecture Comp Engn Dept Istanbul Turkey Istinye Univ Fac Engn & Nat Sci Software Engn Dept Istanbul Turkey Fatih Sultan Mehmet Vakif Univ Fac Engn Comp Engn Dept Istanbul Turkey

The node deployment problem is a non-deterministic polynomial time (NP-hard). This study proposes a new and efficient method to solve this problem without the need for predefined circumstances about the environments independent of terrain. The proposed method is based on a metaheuristic algorithm and mimics the grey wolf optimizer (GWO) algorithm. In this study, we also suggested an enhanced version of the GWO algorithm to work adaptively in such problems and named it Mutant-GWO (MuGWO). Also, the suggested model ensures connectivity by generating topology graphs and potentially supports data transmission mechanisms. Therefore, the proposed method based on MuGWO can enhance resources utilization, such as reducing the number of nodes, by maximizing the coverage rate and maintaining the connectivity. While most studies assume classical rectangle uniform environments, this study also focuses on custom (environment-aware) maps in line with the importance and requirements of the real world. The motivation of supporting custom maps by this study is that environments can consist of custom shapes with prioritized and critical areas. In this way, environment awareness halts the deployment of nodes in undesired regions and averts resource waste. Besides, novel multi-purpose fitness functions of the proposed method satisfy a convenient approach to calculate costs instead of using complicated processes. Accordingly, this method is suitable for large-scale networks thanks to the capability of the distributed architecture and the metaheuristic-based approach. This study justifies the improvements in the suggested model by presenting comparisons with a Deterministic Grid-based approach and the Original GWO. Moreover, this method outperforms the fruit fly optimization algorithm, bat algorithm (BA), Optimized BA, harmony search, and improved dynamic deployment technique based on genetic algorithm methods in declared scenarios in literature, considering the results of simulations.

关键词： node deployment Metaheuristic Mutant GWO WSN DIoT Coverage Connectivity Environment-aware

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Optimization of relay node deployment for multisource multipath routing in Wireless Multimedia Sensor Networks using Gaussian distribution

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COMPUTER NETWORKS 2018年 145卷 96-106页

作者： Awad, Fahed H. Jordan Univ Sci & Technol Dept Network Engn & Secur POB 3030 Irbid 22110 Jordan

In Wireless Multimedia Sensor Networks, source nodes send intense multimedia traffic, under strict quality-of-service requirements, to the base station via resource-limited relay nodes. To satisfy such requirements, all discoverable routing paths must be concurrently utilized. The shorter the paths are, the lower the energy consumption and the shorter the packet delay are, resulting in an enhanced network lifespan and higher rates of data delivery. Optimizing the number and the deployment strategy of relay nodes has been a vital problem to solve. Focusing mainly on single source node scenarios, previous theoretical studies assumed that either a deterministic or a random uniform distribution of relay nodes is to be used. Recent studies, however, have proven that when practical deployment strategies are used, controllable Gaussian distributions of relay nodes can be achieved, and both network resources and routing performance can otherwise be optimized. This paper presents an analytical framework for the optimal deployment of relay nodes using a two-dimensional Gaussian distribution. Given the network parameters (such as number of sources nodes, communication range and number of routing paths needed) both the theoretical minimum number of relay nodes needed and the optimal standard deviation can be exactly determined. To validate the mathematical model and evaluate its performance, a simulation study has been conducted. Statistical analysis revealed that when optimal Gaussian distribution was used, instead of a uniform distribution, routing performance increased by at least twofold. That is sufficiently close to the ideal deterministic distribution. Additionally, the average path length and the number of control packets were considerably reduced, which can potentially improve energy consumption, packet delay, network lifetime and data delivery. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Wireless Multimedia Sensor Networks Efficient multipath routing node deployment Gaussian distribution Analytical model Network simulation

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