Intelligent multi-agent model for energy-efficient communication in wireless sensor networks

IF 2.5 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Kiran Saleem, Lei Wang, Salil Bharany, Khmaies Ouahada, Ateeq Ur Rehman, Habib Hamam
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引用次数: 0

Abstract

The research addresses energy consumption, latency, and network reliability challenges in wireless sensor network communication, especially in military security applications. A multi-agent context-aware model employing the belief-desire-intention (BDI) reasoning mechanism is proposed. This model utilizes a semantic knowledge-based intelligent reasoning network to monitor suspicious activities within a prohibited zone, generating alerts. Additionally, a BDI intelligent multi-level data transmission routing algorithm is proposed to optimize energy consumption constraints and enhance energy-awareness among nodes. The energy optimization analysis involves the Energy Percent Dataset, showcasing the efficiency of four wireless sensor network techniques (E-FEERP, GTEB, HHO-UCRA, EEIMWSN) in maintaining high energy levels. E-FEERP consistently exhibits superior energy efficiency (93 to 98%), emphasizing its effectiveness. The Energy Consumption Dataset provides insights into the joule measurements of energy consumption for each technique, highlighting their diverse energy efficiency characteristics. Latency measurements are presented for four techniques within a fixed transmission range of 5000 m. E-FEERP demonstrates latency ranging from 3.0 to 4.0 s, while multi-hop latency values range from 2.7 to 2.9 s. These values provide valuable insights into the performance characteristics of each technique under specified conditions. The Packet Delivery Ratio (PDR) dataset reveals the consistent performance of the techniques in maintaining successful packet delivery within the specified transmission range. E-FEERP achieves PDR values between 89.5 and 92.3%, demonstrating its reliability. The Packet Received Data further illustrates the efficiency of each technique in receiving transmitted packets. Moreover the network lifetime results show E-FEERP consistently improving from 2550 s to round 925. GTEB and HHO-UCRA exhibit fluctuations around 3100 and 3600 s, indicating variable performance. In contrast, EEIMWSN consistently improves from round 1250 to 4500 s.
无线传感器网络节能通信的智能多代理模型
该研究解决了无线传感器网络通信,特别是军事安全应用中的能耗、延迟和网络可靠性挑战。研究提出了一种采用信念-愿望-意图(BDI)推理机制的多代理情境感知模型。该模型利用基于语义知识的智能推理网络监控禁区内的可疑活动,并生成警报。此外,还提出了一种 BDI 智能多级数据传输路由算法,以优化能耗约束并增强节点间的能量感知。能量优化分析涉及能量百分比数据集,展示了四种无线传感器网络技术(E-FEERP、GTEB、HHO-UCRA、EEIMWSN)在保持高能量水平方面的效率。E-FEERP 始终表现出卓越的能源效率(93% 至 98%),凸显了其有效性。能耗数据集提供了每种技术的焦耳能耗测量数据,突出了它们不同的能效特性。E-FEERP 的延迟时间为 3.0 至 4.0 秒,而多跳延迟时间为 2.7 至 2.9 秒。数据包交付率 (PDR) 数据集显示,这些技术在指定传输范围内保持数据包成功交付的性能始终如一。E-FEERP 的 PDR 值介于 89.5% 和 92.3% 之间,证明了其可靠性。数据包接收数据进一步说明了每种技术在接收传输数据包方面的效率。此外,网络寿命结果显示,E-FEERP 从 2550 秒持续提高到 925 秒。GTEB 和 HHO-UCRA 在 3100 秒和 3600 秒左右出现波动,表明性能参差不齐。相比之下,EEIMWSN 从 1250 到 4500 秒持续改善。
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来源期刊
EURASIP Journal on Information Security
EURASIP Journal on Information Security COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
8.80
自引率
0.00%
发文量
6
审稿时长
13 weeks
期刊介绍: The overall goal of the EURASIP Journal on Information Security, sponsored by the European Association for Signal Processing (EURASIP), is to bring together researchers and practitioners dealing with the general field of information security, with a particular emphasis on the use of signal processing tools in adversarial environments. As such, it addresses all works whereby security is achieved through a combination of techniques from cryptography, computer security, machine learning and multimedia signal processing. Application domains lie, for example, in secure storage, retrieval and tracking of multimedia data, secure outsourcing of computations, forgery detection of multimedia data, or secure use of biometrics. The journal also welcomes survey papers that give the reader a gentle introduction to one of the topics covered as well as papers that report large-scale experimental evaluations of existing techniques. Pure cryptographic papers are outside the scope of the journal. Topics relevant to the journal include, but are not limited to: • Multimedia security primitives (such digital watermarking, perceptual hashing, multimedia authentictaion) • Steganography and Steganalysis • Fingerprinting and traitor tracing • Joint signal processing and encryption, signal processing in the encrypted domain, applied cryptography • Biometrics (fusion, multimodal biometrics, protocols, security issues) • Digital forensics • Multimedia signal processing approaches tailored towards adversarial environments • Machine learning in adversarial environments • Digital Rights Management • Network security (such as physical layer security, intrusion detection) • Hardware security, Physical Unclonable Functions • Privacy-Enhancing Technologies for multimedia data • Private data analysis, security in outsourced computations, cloud privacy
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