Towards a novel trust-based opportunistic routing protocol for wireless networks

Salehi, Mahmood; Boukerche, Azzedine; Darehshoorzadeh, Amir; Mammeri, Abdelhamid

doi:10.1007/s11276-015-1010-4

Cited by 35 publications

(10 citation statements)

References 37 publications

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“…Different trust computational approaches have been introduced as different trust models. Our study shows that E2TX [52], RTOR [180] and its close relatives, TORDP and GEOTOR [181], are metrics that accommodate trust via a very simple direct trust model. ETOR [33] extends the trust model to include indirect trust.…”

Section: A Parameters Developmentmentioning

confidence: 83%

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Opportunistic routing metrics: A timely one-stop tutorial survey

Abdollahi

Eshghi

Kelarestaghi

et al. 2020

Journal of Network and Computer Applications

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High-speed, low latency, and heterogeneity features of 5G, as the common denominator of many emerging and classic wireless applications, have put wireless technology back in the spotlight. Continuous connectivity requirement in low-power and wide-reach networks underlines the need for more efficient routing over scarce wireless resources, in multi-hp scenarios. In this regard, Opportunistic Routing (OR), which utilizes the broadcast nature of wireless media to provide transmission cooperation amongst a selected number of overhearing nodes, has become more promising than ever. Crucial to the overall network performance, which nodes to participate and where they stand on the transmission-priority hierarchy, are decided by userdefined OR metrics embedded in OR protocols. Therefore, the task of choosing or designing an appropriate OR metric is a critical one. The numerousness, proprietary notations, and the objective variousness of OR metrics can cause the interested researcher to lose insight and become overwhelmed, making the metric selection or design effort-intensive. While there are not any comprehensive OR metrics surveys in the literature, those who partially address the subject are non-exhaustive and lacking in detail. Furthermore, they offer limited insight regarding related taxonomy and future research recommendations. In this paper, starting with a custom tutorial with a new look to OR and OR metrics, we devise a new framework for OR metric design. Introducing a new taxonomy enables us to take a structured, investigative, and comparative approach to OR metrics, supported by extensive simulations. Exhaustive coverage of OR metrics, formulated in a unified notation, is presented with sufficient details. Self-explanatory, easy-to-grasp, and visual-friendly quick references are provided, which can be used independently from the rest of the paper. Finally, a new insightful framework for future research directions is developed. This tutorial-survey has been organized to benefit both generalists and OR specialists equally, and to be used not only in its entirety but selectively as well.

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Section: A Parameters Developmentmentioning

confidence: 83%

“…• Reliable Trust-based OR (RTOR), TORDP, GEOTOR: [180] and [181] consider the trustworthiness of a neighboring node as well as its link reliability by defining a new metric, RT OR. Each node i calculates its neighboring node j's RTOR according to the following:…”

Section: • Multicast Expected Advancement Rate (Mear) I-mearmentioning

confidence: 99%

Opportunistic routing metrics: A timely one-stop tutorial survey

Abdollahi

Eshghi

Kelarestaghi

et al. 2020

Journal of Network and Computer Applications

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“…Beyond mobile crowdsensing, the notion of computational trust has been employed to solve many research problems related to the QoI, including e-commerce [93,124]. Among the fields closely related to mobile crowdsensing, we include sensor networks [9,83,84,137,163], opportunistic networks [32,99,153,198], and social networks [59,197], to name a few. However, establishing trust in mobile crowdsensing poses some unique challenges that cannot be addressed solely with existing trust frameworks.…”

Section: Related Workmentioning

confidence: 99%

Quality of Information in Mobile Crowdsensing

Restuccia

Ghosh

Bhattacharjee

et al. 2017

ACM Trans. Sen. Netw.

154

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Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work. F. Restuccia et al.Not only are today's smartphones ubiquitous devices, they are also equipped with a plethora of embedded multi-modal sensors; integrate wireless communication technologies such as 4G/WiFi Internet connectivity, and possess complex processing capabilities. For example, the cameras on smartphones can be used as video and image sensors [29], the microphone can be used as an acoustic sensor [39,154,206], and the embedded global positioning system (GPS) receiver can be used to gather accurate location information, while gyroscopes, accelerometers, and proximity sensors can be used to extract contextual information about the users, such as driving or walking states [75,122]. Further, additional sensors can be easily interfaced with smartphones via Bluetooth or wired connections, such as temperature, air quality, and humidity [69,168].These technological features, combined with the advanced sensing capability of humans, has spurred a significant amount of research from both academia and industry, which together have proposed over the last 10 years a myriad of applications based on the emerging mobile crowdsensing paradigm 1 . Mobile crowdsensing empowers ordinary citizens (or users 2 ) with the capability to actively monitor various phenomena pertaining to themselves (e.g., health, social connections) or their community (e.g., environment). This rich information or inference about themselves or the community may also be sent back to the participating or other concerned users to improve their life experiences, thus influencing their choices. Real-life applications, which can take advantage of both low-level sensor data and high-level user activities, range from real-time traffic monitoring applications, to environmental pollution monitoring, crime monitoring, and social networking, just to name a few. For a survey on mobile crowdsensin...

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“…Comparing the established model with the SAT model [8] and the DCT model [9], the results show that with the increase of malicious nodes in the network, the trust mechanism established in this paper has better anti-interference ability. 2) Combine the node trust degree and ETX value, and compare with the four routing algorithms TBOR [10], RTOR [11], TAODV, and EXOR to conduct comparative experiments on throughput, end-to-end delay, and packet delivery rate. Simulation results show that combining the trust model and OR protocol proposed in this paper can significantly improve the communication performance in harsh environments.…”

Section: Introductionmentioning

confidence: 99%

Trusted Opportunistic Routing Based on Node Trust Model

Huan

2020

IEEE Access

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In vehicular ad hoc networks, opportunistic routing can effectively improve the reliability and throughput. However, opportunistic routing also has security issues. For example, malicious nodes can easily mix into node candidate sets, which can interfere with network performance. In this paper, a trust model based on node behavior is proposed for solving the problem of malicious nodes in the opportunistic routing and forwarding candidate set. The proposed trust model uses pruning and filtering mechanisms to remove malicious suggestions,and uses dynamic weight calculation methods to combine direct trust and indirect trust when calculating the comprehensive trust value, which can screen and filter low-trust nodes in the network. Then, combining the ETX (Expected Transmission Count) value and the node trust value, an opportunity routing algorithm based on trust model (BTOR) is proposed. Extensive simulation results represent that the algorithm can significantly improve the network performance and reduce the interference of malicious nodes to the network system.

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Towards a novel trust-based opportunistic routing protocol for wireless networks

Cited by 35 publications

References 37 publications

Opportunistic routing metrics: A timely one-stop tutorial survey

Opportunistic routing metrics: A timely one-stop tutorial survey

Quality of Information in Mobile Crowdsensing

Trusted Opportunistic Routing Based on Node Trust Model

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