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COMPUTER ENGINEERING PROJRCT TOPICS

DEVELOPMENT OF A PRIVACY AIDED TRUST ROUTING ALGORITHM

DEVELOPMENT OF A PRIVACY AIDED TRUST ROUTING ALGORITHM

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DEVELOPMENT OF A PRIVACY AIDED TRUST ROUTING ALGORITHM

Chapter One: Introduction 1.1 Background of the Study
An opportunistic network (OppNet) is a type of Delay Tolerant Network (DTN) and an evolution of Mobile Ad-hoc Network (MANET) in which a message can be sent from source to destination even if a continuous connection between source and destination does not exist at any one time.

As a result, it takes advantage of and relies on opportunistic pair-wise contact between network nodes. As a result, communications are routed (or passed) from one node to another whenever they are within the relatively limited wireless range of one another.

This may occur frequently, until the message reaches its target. Thus, it employs the store-carry-forward networking paradigm (C’amara et al., 2011; Musolesi & Mascolo, 2008). Figure 1.1 shows how relay nodes forward a message hop by hop from a source node to a destination node.

Figure 1: Message Forwarding on OppNet (Noorin, 2009).

OppNets are highly scalable and can be used in a variety of applications, including ubiquitous computing, disaster management, military surveillance, wildlife monitoring, VANETs, IoT, and deep space exploration (Luo et al., 2008; Malladi & Agrawal, 2002; NASA, 2012).

Despite the fact that OppNets have the ability to solve some of the problems of traditional networks, their frequent disruption, long latency, dynamic and ad-hoc (self-organizing) nature present significant hurdles that must be overcome in order to fully benefit from their use.

OppNets research crosses multiple fields, including computer networking (computer science and engineering), mathematics, information sciences, and social sciences (sociology and social psychology).

OppNets have recently sparked increased study attention because they offer a possible alternative to the limitations of standard network architecture. Researchers have worked extensively on routing protocols.

Because OppNets use a store-carry-forward network model, buffer management is a critical component of the network. Many detailed studies on buffer management options have also been published (Viscal et al., 2014; Pan et al., 2013).

Wireless devices in this network that help route communications may be held by humans, attached to animals, or part of transportation systems such as automobiles, ships, and aeroplanes, among others (Balasubramanian et al., 2008; Eagle & Pentland, 2006; McNett & Voelker, 2005).

These devices not only buffer the message, but also carry it as they move across the environment until they encounter the destination or more appropriate relay nodes. As a result, the mobility of these device carriers has a significant impact on OppNets’ performance (Camp et al., 2002; Karamshuk et al., 2011; Lin et al., 2004).

As a result, studies have been conducted on this topic in order to increase network performance. Furthermore, data from real-world contact traces have been collected in an effort to make an OppNet a reality (Henderson et al., 2004; Mtibaa et al., 2008; Piorkowski et al., 2009).
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More recently, researchers have investigated human behavioural patterns resulting from social interactions in terms of connection and mobility. The social interaction comprises dwelling, friends, place of work, and so on.

Others employ behavioural patterns associated with interest, centrality, community, and closeness, among other things (D’ora & Holezer, 2010; Hui et al., 2011; Fan et al., 2013; Daly et al., 2009; Abdelkader et al., 2013). Many studies have highlighted the behavioural pattern of social contacts as the most promising method of routing (Zhang et al., 2014; Zhou et al., 2013; Usman and Gutierrez, 2018).

Thus, because nodes in OppNet are mobile and’social’ by definition (i.e., mobility and social interaction cannot be totally separated in real life), it is also known as Opportunistic Mobile Social Networks (OMSN).

Despite all of these efforts, the usefulness of OppNets is limited unless security and privacy concerns are seriously addressed (Liang et al., 2013; Kumar et al., 2018; Liu et al., 2018).

Because of the nature of OppNets, there is a trade-off between routing efficiency and privacy, as described by Costantino et al. (2014). As a result, further in-depth and realistic research into this area of OppNet is needed.

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