Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

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.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

A Neighborhood-Based Trust Protocol for Secure Collaborative Routing in Wireless Mobile D2D HetNets

Heterogeneous Device-to-Device mobile networks are characterised by frequent network disruption and unreliability of peers delivering messages to destinations. Trust-based protocols has been widely used to mitigate the security and performance problems in D2D networks. Despite several efforts made by previous researchers in the design of trust-based routing for efficient collaborative networks, there are fewer related studies that focus on the peers’ neighbourhood as a routing metrics’ element for a secure and efficient trust-based protocol. In this paper, we propose and validate a trust-based protocol that takes into account the similarity of peers’ neighbourhood coefficients to improve routing performance in mobile HetNets environments. The results of this study demonstrate that peers’ neighborhood connectivity in the network is a characteristic that can influence peers’ routing performance. Furthermore, our analysis shows that our proposed protocol only forwards the message to the companions with a higher probability of delivering the packets, thus improving the delivery ratio and minimizing latency and mitigating the problem of malicious peers ( using packet dropping strategy)

On the Relation Between Mobile Encounters and Web Traffic Patterns: A Data-driven Study

Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper, we characterize mobility encounters and study the correlation between encounters and web traffic profiles using large-scale datasets (30TB in size) of WiFi and NetFlow traces. The analysis quantifies these correlations for the first time, across spatio-temporal dimensions, for device types grouped into on-the-go Flutes and sit-to-use Cellos. The results consistently show a clear relation between mobility encounters and traffic across different buildings over multiple days, with encountered pairs showing higher traffic similarity than non-encountered pairs, and long encounters being associated with the highest similarity. We also investigate the feasibility of learning encounters through web traffic profiles, with implications for dissemination protocols, and contact tracing. This provides a compelling case to integrate both mobility and web traffic dimensions in future models, not only at an individual level, but also at pairwise and collective levels. We have released samples of code and data used in this study on GitHub, to support reproducibility and encourage further research (https://github.com/BabakAp/encounter-traffic).Comment: Technical report with details for conference paper at MSWiM 2018, v3 adds GitHub lin

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

Content Dissemination in Mobile Social Networks

Mobile social networking(MSN) has emerged as an effective platform for social network users to pervasively disseminate the contents such as news, tips, book information, music, video and so on. In content dissemination, mobile social network users receive content or information from their friends, acquaintances or neighbors, and selectively forward the content or information to others. The content generators and receivers have different motivation and requirements to disseminate the contents according to the properties of the contents, which makes it a challenging and meaningful problem to effectively disseminate the content to the appropriate users. In this dissertation, the typical content dissemination scenarios in MSNs are investigated. According to the content properties, the corresponding user requirements are analyzed. First, a Bayesian framework is formulated to model the factors that influence users behavior on streaming video dissemination. An effective dissemination path detection algorithm is derived to detect the reliable and efficient video transmission paths. Second, the authorized content is investigated. We analyze the characteristics of the authorized content, and model the dissemination problem as a new graph problem, namely, Maximum Weighted Connected subgraph with node Quota (MWCQ), and propose two effective algorithms to solve it. Third, the authorized content dissemination problem in Opportunistic Social Networks(OSNs) is studied, based on the prediction of social connection pattern. We then analyze the influence of social connections on the content acquirement, and propose a novel approach, User Set Selection(USS) algorithm, to help social users to achieve fast and accurate content acquirement through social connections

Beyond Traditional DTN Routing: Social Networks for Opportunistic Communication

This article examines the evolution of routing protocols for intermittently connected ad hoc networks and discusses the trend toward social-based routing protocols. A survey of current routing solutions is presented, where routing protocols for opportunistic networks are classified based on the network graph employed. The need to capture performance tradeoffs from a multi-objective perspective is highlighted.Comment: 8 pages, 4 figures, 1 tabl