Reputation and credit based incentive mechanism for data-centric message delivery in delay tolerant networks

In a Data-centric Delay Tolerant Networks (DTNs), it is essential for nodes to cooperate in message forwarding in order to enable successful delivery of a message in an opportunistic fashion with nodes having their social interests defined. In the data-centric dissemination protocol proposed here, a source annotates messages (images) with keywords, and then intermediate nodes are presented with an option of adding keyword-based annotations in order to create higher content strength messages on path toward the destination. Hence, contents like images get enriched as there is situation evolution or learned by these intermediate nodes, such as in a battlefield, or in a disaster situation. Nodes might turn selfish and not participate in relaying messages due to relative scarcity of battery and storage capacity in mobile devices. Therefore, in addition to content enrichment, an incentive mechanism is proposed in this thesis which considers factors like message quality, battery usage, level of interests, etc. for the calculation of incentives. Moreover, with the goal of preventing the nodes from turning malicious by adding inappropriate message tags in the quest of acquiring more incentive, a distributed reputation model (DRM) is developed and consolidated with the proposed incentive scheme. DRM takes into account inputs from multiple users like ratings for the relevance of annotations in the message, message quality, etc. The proposed scheme safeguards the network from congestion due to uncooperative or selfish nodes in the system. The performance evaluation shows that our approach delivers more high priority and high quality messages while reducing traffic at a slightly lower message delivery ratio compared to ChitChat --Abstract, page iv

Socio-economic aware data forwarding in mobile sensing networks and systems

The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Data Dissemination And Information Diffusion In Social Networks

Data dissemination problem is a challenging issue in social networks, especially in mobile social networks, which grows rapidly in recent years worldwide with a significant increasing number of hand-on mobile devices such as smart phones and pads. Short-range radio communications equipped in mobile devices enable mobile users to access their interested contents not only from access points of Internet but also from other mobile users. Through proper data dissemination among mobile users, the bandwidth of the short-range communications can be better utilized and alleviate the stress on the bandwidth of the cellular networks. In this dissertation proposal, data dissemination problem in mobile social networks is studied. Before data dissemination emerges in the research of mobile social networks, routing protocol of finding efficient routing path in mobile social networks was the focus, which later became the pavement for the study of the efficient data dissemination. Data dissemination priorities on packet dissemination from multiple sources to multiple destinations while routing protocol simply focus on finding routing path between two ends in the networks. The first works in the literature of data dissemination problem were based on the modification and improvement of routing protocols in mobile social networks. Therefore, we first studied and proposed a prediction-based routing protocol in delay tolerant networks. Delay tolerant network appears earlier than mobile social networks. With respect to delay tolerant networks, mobile social networks also consider social patterns as well as mobility patterns. In our work, we simply come up with the prediction-based routing protocol through analysis of user mobility patterns. We can also apply our proposed protocol in mobile social networks. Secondly, in literature, efficient data dissemination schemes are proposed to improve the data dissemination ratio and with reasonable overhead in the networks. However, the overhead may be not well controlled in the existing works. A social-aware data dissemination scheme is proposed in this dissertation proposal to study efficient data dissemination problem with controlled overhead in mobile social networks. The data dissemination scheme is based on the study on both mobility patterns and social patterns of mobile social networks. Thirdly, in real world cases, an efficient data dissemination in mobile social networks can never be realized if mobile users are selfish, which is true unfortunately in fact. Therefore, how to strengthen nodal cooperation for data dissemination is studied and a credit-based incentive data dissemination protocol is also proposed in this dissertation. Data dissemination problem was primarily researched on mobile social networks. When consider large social networks like online social networks, another similar problem was researched, namely, information diffusion problem. One specific problem is influence maximization problem in online social networks, which maximize the result of information diffusion process. In this dissertation proposal, we proposed a new information diffusion model, namely, sustaining cascading (SC) model to study the influence maximization problem and based on the SC model, we further plan our research work on the information diffusion problem aiming at minimizing the influence diffusion time with subject to an estimated influence coverage

Socially-aware congestion control in ad-hoc networks: Current status and the way forward

Ad-hoc social networks (ASNETs) represent a special type of traditional ad-hoc network in whicha user’s social properties (such as the social connections and communications metadata as wellas application data) are leveraged for offering enhanced services in a distributed infrastructurelessenvironments. However, the wireless medium, due to limited bandwidth, can easily suffer from theproblem of congestion when social metadata and application data are exchanged among nodes—a problem that is compounded by the fact that some nodes may act selfishly and not share itsresources. While a number of congestion control schemes have been proposed for the traditional ad-hoc networks, there has been limited focus on incorporating social awareness into congestion controlschemes. We revisit the existing traditional ad-hoc congestion control and data distribution protocolsand motivate the need for embedding social awareness into these protocols to improve performance.We report that although some work is available in opportunistic network that uses socially-awaretechniques to control the congestion issue, this area is largely unexplored and warrants more researchattention. In this regards, we highlight the current research progress and identify multiple futuredirections of research

Enhanced Interest Aware PeopleRank for Opportunistic Mobile Social Networks

Network infrastructures are being continuously challenged by increased demand, resource-hungry applications, and at times of crisis when people need to work from homes such as the current Covid-19 epidemic situation, where most of the countries applied partial or complete lockdown and most of the people worked from home. Opportunistic Mobile Social Networks (OMSN) prove to be a great candidate to support existing network infrastructures. However, OMSNs have copious challenges comprising frequent disconnections and long delays. we aim to enhance the performance of OMSNs including delivery ratio and delay. We build upon an interest-aware social forwarding algorithm, namely Interest Aware PeopleRank (IPeR). We explored three pillars for our contribution, which encompass (1) inspect more than one hop (multiple hops) based on IPeR (MIPeR), (2) by embracing directional forwarding (Directional-IPeR), and (3) by utilizing a combination of Directional forwarding and multi-hop forwarding (DMIPeR). For Directional-IPeR, different values of the tolerance factor of IPeR, such as 25% and 75%, are explored to inspect variations of Directional-IPeR. Different interest distributions and users’ densities are simulated using the Social-Aware Opportunistic Forwarding Simulator (SAROS). The results show that (1) adding multiple hops to IPeR enhanced the delivery ratio, number of reached interested forwarders, and delay slightly. However, it increased the cost and decreased F-measure hugely. Consequently, there is no significant gain in these algorithms. (2) Directional-IPeR-75 performed generally better than IPeR in delivery ratio, and the number of reached interested forwarders. Besides, when some of the uninterested forwarders did not participate in messages delivery, which is a realistic behavior, the performance is enhanced and performed better generally in all metrics compared to IPeR. (3) Adding multiple hops to directional guided IPeR did not gain any enhancement. (4) Directional-IPeR-75 performs better in high densities in all metrics except delay. Even though, it enhances delay in sparse environments. Consequently, it can be utilized in disastrous areas, in which few people are with low connectivity and spread over a big area. In addition, it can be used in rural areas as well where there is no existing networks

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio