QoS with Selfish Nodes in Wireless Networks

Author(s):  
S.R. Sandeep ◽  
P. Nuggehalli
Author(s):  
Bhalaji N

The autonomous mobile nodes framing an instantaneous network, utilizing the nearby available device that volunteer in establishing network is coined as the fly wire network. These adhoc type of network framed simultaneously are prone to various vulnerabilities, developing alterations in the information’s or hacking of information’s or the blocking of services. These security threats causing losses in the information transmitted, makes it necessary for the trust evaluation of the nodes to identify the selfish nodes. So the paper proposes the block chain trust management of nodes to avoid the vulnerabilities in the transmission path, enhancing the performance of the network. The performance of the proposed method is validated in the network simulator –II to ensure its capability in terms of the quality of service and the security (defense).


Author(s):  
Alessandro Aldini ◽  
Alessandro Bogliolo

User-centric wireless networks are characterized by a community-scale objective aiming at the shared provision of user-generated services and contents. This may be contrasted by the reticence of individuals to share the limited resources of mobile devices. Hence, cooperation incentives play a key role to promote prosocial decisions and to isolate selfish nodes and cheating behaviors. In particular, trust-based incentives and remuneration are used to induce collaborative behaviors in Wi-Fi communities. Typically, these mechanisms are based on reputation infrastructures and virtual currency systems, the application of which should not hinder the normal operation of the network. In this chapter, the authors present an approach to the combined use of indirect rewards deriving from trust-based incentives and direct rewards deriving from remuneration. The effectiveness and efficiency of such an approach in the setting of user-centric wireless networks is verified by conducting a formal study of the benefits of the joint application of these rewards and of the related impact upon performance.


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