A Mini Review of Peer-to-Peer (P2P) for Vehicular Communication

Yogarayan, Sumendra; Razak, Siti Fatimah Abdul; Azman, Azreen; Abdullah, Mohd Fikri Azli

doi:10.52549/ijeei.v9i1.2736

Cited by 3 publications

(2 citation statements)

References 74 publications

(78 reference statements)

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“…For instance, decentralized data sharing frequently relies on voluntary resource contribution, where individuals are willing to contribute their network resources for the benefit of others. To achieve better resource utilization efficiency, incentive mechanisms can be used to balance the demand and supply of network resources through a peer-to-peer data trading market [10], [11]. In this market, users who demand resources pay a price for the resources they get, while users who have extra resources are compensated for supplying them.…”

Section: Introductionmentioning

confidence: 99%

Differentiated Security Architecture for Secure and Efficient Infotainment Data Communication in IoV Networks

Jiani

Shar

Guo

et al. 2022

Network and System Security

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The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through onboard infotainment applications. Decentralized data sharing can improve security, privacy, reliability, and facilitate infotainment data sharing in IoVs. However, decentralized data sharing may not achieve the expected efficiency if there are IoV users who only want to consume the shared data but are not willing to contribute their own data to the community, resulting in incomplete information observed by other vehicles and infrastructure, which can introduce additional transmission latency. Therefore, in this paper, by modeling the data sharing ecosystem as a data trading market, we propose a decentralized data-sharing incentive mechanism based on multiintelligent reinforcement learning to learn the supply-demand balance in markets and minimize transmission latency. Our proposed mechanism takes into account the dynamic nature of IoV markets, which can experience frequent fluctuations in supply and demand. We propose a time-sensitive Key-Policy Attribute-Based Encryption (KP-ABE) mechanism coupled with Named Data Networking (NDN) to protect data in IoVs, which adds a layer of security to our proposed solution. Additionally, we design a decentralized market for efficient data sharing in IoVs, where continuous double auctions are adopted. The proposed mechanism based on multi-agent deep reinforcement learning can learn the supply-demand equilibrium in markets, thus improving the efficiency and sustainability of markets. Theoretical analysis and experimental results show that our proposed learning-based incentive mechanism outperforms baselines by 10% in determining the equilibrium of supply and demand while reducing transmission latency by 20%.

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Section: Introductionmentioning

confidence: 99%

Differentiated Security Architecture for Secure and Efficient Infotainment Data Communication in IoV Networks

Jiani

Shar

Guo

et al. 2022

Network and System Security

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“…Active networking solutions such as switch ware [14] and software routing suites such as click modular router [15] and bird internet routing daemon (BIRD) [16] are released prior to SDN that supports programmability [17] of the control plane. Routing control platform (RCP) [18], forwarding and control element separation (ForCES) framework released by internet engineering task force (IETF) [19], 4D design of network architecture [20], path computation element (PCE) architecture [21], [22], ethane [23] and open flow [22] are released prior to SDN that supports separation of control and data planes.…”

Section: Introductionmentioning

confidence: 99%

Controller placement problem in software defined networks

Saleh

Mishkal

Ibrahim

2022

IJEECS

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<span>The requirements <span>for the network are increasing by the expanding and spreading the Internet. The Previous techniques of the network do not meet the modern needs, thus, a new technical presents software-defined networking (SDN). SDN recognizes as a promising new model that separates the control plane (traffic routing and network topology) from the data plane (network architecture layers). The architecture of SDN has some features that find in a single controller or many controllers instance of programmable, flexible, and scalable. In the current SDN, multiple controllers are essential. Therefore, the optimal number of the controllers and their locations is the most significant challenge, known as the controller placement problem (CPP). It deploys the optimal number of controllers within the network while meeting presentations requirements considered conflicting in nature example: credibility, load balancing, latency, energy efficiency, and computation time. Many studies researched the ways to develop solutions for improving scalability, place selection for SDN. This paper presents the CPP and gives a comprehensive review of SDN issues based on the recent well-known research to extract available solution strategies. Finally, it discusses the limitations and future study directions that can support researchers in this field.</span></span>

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