Socially-Aware Networking: A Survey

The widespread proliferation of handheld devices enables mobile carriers to be connected at anytime and anywhere. Meanwhile, the mobility patterns of mobile devices strongly depend on the users' movements, which are closely related to their social relationships and behaviors. Consequently, today's mobile networks are becoming increasingly human centric. This leads to the emergence of a new field which we call socially-aware networking (SAN). One of the major features of SAN is that social awareness becomes indispensable information for the design of networking solutions. This emerging paradigm is applicable to various types of networks (e.g. opportunistic networks, mobile social networks, delay tolerant networks, ad hoc networks, etc) where the users have social relationships and interactions. By exploiting social properties of nodes, SAN can provide better networking support to innovative applications and services. In addition, it facilitates the convergence of human society and cyber physical systems. In this paper, for the first time, to the best of our knowledge, we present a survey of this emerging field. Basic concepts of SAN are introduced. We intend to generalize the widely-used social properties in this regard. The state-of-the-art research on SAN is reviewed with focus on three aspects: routing and forwarding, incentive mechanisms and data dissemination. Some important open issues with respect to mobile social sensing and learning, privacy, node selfishness and scalability are discussed.Comment: accepted. IEEE Systems Journal, 201

Social-aware Opportunistic Routing: The New Trend

Since users move around based on social relationships and interests, the resulting movement patterns can represent how nodes are socially connected (i.e., nodes with strong social ties, nodes that meet occasionally by sharing the same working environment). This means that social interactions reflect personal relationships (e.g., family, friends, co-workers, passers-by) that may be translated into statistical contact opportunities within and between social groups over time. Such contact opportunities may be exploited to ensure good data dissemination and retrieval, even in the presence of intermittent connectivity. Thus, in the last years, a new trend based on social similarity emerged where social relationships, interests, popularity and among others, are used to improve opportunistic routing. In this chapter, the reader will learn about the different approaches related to opportunistic routing focusing on the social-aware approaches and how such approaches make use of social information derived from opportunistic contacts to improve data forwarding. Additionally, a brief overview on the existing taxonomies for opportunistic routing as well as an updated one are provided along with a set of experiments in scenarios based on synthetic mobility models and human traces in order to show the potential of social-aware solutions.Comment: 42 pages, 10 figures, 1 tabl

Data Dissemination in Opportunistic Networks

Mobile devices integrating wireless short-range communication technologies make possible new applications for spontaneous communication, interaction and collaboration. An interesting approach is to use collaboration to facilitate communication when mobile devices are not able to establish direct communication paths. Opportunistic networks, formed when mobile devices communicate with each other while users are in close proximity, can help applications still exchange data in such cases. In opportunistic networks routes are built dynamically, as each mobile device acts according to the store-carry-and-forward paradigm. Thus, contacts between mobile devices are seen as opportunities to move data towards destination. In such networks data dissemination is done using forwarding and is usually based on a publish/subscribe model. Opportunistic data dissemination also raises questions concerning user privacy and incentives. Such problems are addressed differently by various opportunistic data dissemination techniques. In this paper we analyze existing relevant work in the area of data dissemination in opportunistic networks. We present the categories of a proposed taxonomy that captures the capabilities of data dissemination techniques used in such networks. Moreover, we survey relevant data dissemination techniques and analyze them using the proposed taxonomy.Comment: Please cite this as "Radu Ciobanu, Ciprian Dobre, Data Dissemination in Opportunistic Networks, in Proc. of 18th International Conference on Control Systems and Computer Science (CSCS-18), Bucharest, Romania, 2011, pp. 529-536, ISSN: 2066-4451, Politehnica Press

PRIF: A Privacy-Preserving Interest-Based Forwarding Scheme for Social Internet of Vehicles

Recent advances in Socially Aware Networks (SANs) have allowed its use in many domains, out of which social Internet of vehicles (SIOV) is of prime importance. SANs can provide a promising routing and forwarding paradigm for SIOV by using interest-based communication. Though able to improve the forwarding performance, existing interest-based schemes fail to consider the important issue of protecting users' interest information. In this paper, we propose a PRivacy-preserving Interest-based Forwarding scheme (PRIF) for SIOV, which not only protects the interest information, but also improves the forwarding performance. We propose a privacy-preserving authentication protocol to recognize communities among mobile nodes. During data routing and forwarding, a node can know others' interests only if they are affiliated with the same community. Moreover, to improve forwarding performance, a new metric {\em community energy} is introduced to indicate vehicular social proximity. Community energy is generated when two nodes encounter one another and information is shared among them. PRIF considers this energy metric to select forwarders towards the destination node or the destination community. Security analysis indicates PRIF can protect nodes' interest information. In addition, extensive simulations have been conducted to demonstrate that PRIF outperforms the existing algorithms including the BEEINFO, Epidemic, and PRoPHET

Modeling Human Mobility and its Applications in Routing in Delay-Tolerant Networks: a Short Survey

Human mobility patterns are complex and distinct from one person to another. Nevertheless, motivated by tremendous potential benefits of modeling such patterns in enabling new mobile services and technologies, researchers have attempted to capture salient characteristics of human mobility. In this short survey paper, we review some of the major techniques for modeling humans' co-location, as well as predicting human location and trajectory. Further, we review one of the most important application areas of such models, namely, routing in delay-tolerant networks

Friendship and Selfishness Forwarding: applying machine learning techniques to Opportunistic Networks data forwarding

Opportunistic networks could become the solution to provide communication support in both cities where the cellular network could be overloaded, and in scenarios where a fixed infrastructure is not available, like in remote and developing regions. A critical issue that still requires a satisfactory solution is the design of an efficient data delivery solution. Social characteristics are recently being considered as a promising alternative. Most opportunistic network applications rely on the different mobile devices carried by users, and whose behavior affects the use of the device itself. This work presents the "Friendship and Selfishness Forwarding" (FSF) algorithm. FSF analyses two aspects to make message forwarding decisions when a contact opportunity arises: First, it classifies the friendship strength among a pair of nodes by using a machine learning algorithm to quantify the friendship strength among pairs of nodes in the network. Next, FSF assesses the relay node selfishness to consider those cases in which, despite a strong friendship with the destination, the relay node may not accept to receive the message because it is behaving selfishly, or because its device has resource constraints in that moment. By using trace-driven simulations through the ONE simulator, we show that the FSF algorithm outperforms previously proposed schemes in terms of delivery rate, average cost, and efficiency.Comment: 27 pages, 25 figure

Survey of Important Issues in UAV Communication Networks

Unmanned Aerial Vehicles (UAVs) have enormous potential in the public and civil domains. These are particularly useful in applications where human lives would otherwise be endangered. Multi-UAV systems can collaboratively complete missions more efficiently and economically as compared to single UAV systems. However, there are many issues to be resolved before effective use of UAVs can be made to provide stable and reliable context-specific networks. Much of the work carried out in the areas of Mobile Ad Hoc Networks (MANETs), and Vehicular Ad Hoc Networks (VANETs) does not address the unique characteristics of the UAV networks. UAV networks may vary from slow dynamic to dynamic; have intermittent links and fluid topology. While it is believed that ad hoc mesh network would be most suitable for UAV networks yet the architecture of multi-UAV networks has been an understudied area. Software Defined Networking (SDN) could facilitate flexible deployment and management of new services and help reduce cost, increase security and availability in networks. Routing demands of UAV networks go beyond the needs of MANETS and VANETS. Protocols are required that would adapt to high mobility, dynamic topology, intermittent links, power constraints and changing link quality. UAVs may fail and the network may get partitioned making delay and disruption tolerance an important design consideration. Limited life of the node and dynamicity of the network leads to the requirement of seamless handovers where researchers are looking at the work done in the areas of MANETs and VANETs, but the jury is still out. As energy supply on UAVs is limited, protocols in various layers should contribute towards greening of the network. This article surveys the work done towards all of these outstanding issues, relating to this new class of networks, so as to spur further research in these areas.Comment: arXiv admin note: substantial text overlap with arXiv:1304.3904 by other author

Content Retrieval At the Edge: A Social-aware and Named Data Cooperative Framework

Recent years with the popularity of mobile devices have witnessed an explosive growth of mobile multimedia contents which dominate more than 50\% of mobile data traffic. This significant growth poses a severe challenge for future cellular networks. As a promising approach to overcome the challenge, we advocate Content Retrieval At the Edge, a content-centric cooperative service paradigm via device-to-device (D2D) communications to reduce cellular traffic volume in mobile networks. By leveraging the Named Data Networking (NDN) principle, we propose sNDN, a social-aware named data framework to achieve efficient cooperative content retrieval. Specifically, sNDN introduces Friendship Circle by grouping a user with her close friends of both high mobility similarity and high content similarity. We construct NDN routing tables conditioned on Friendship Circle encounter frequency to navigate a content request and a content reply packet between Friendship Circles, and leverage social properties in Friendship Circle to search for the final target as inner-Friendship Circle routing. The evaluation results demonstrate that sNDN can save cellular capacity greatly and outperform other content retrieval schemes significantly.Comment: Lingjun Pu, Xu Chen, Jingdong Xu, and Xiaoming Fu, "Content Retrieval At the Edge: A Social-aware and Named Data Cooperative Framework," accepted by IEEE Transactions on Emerging Topics in Computing, 201

A Survey of Delay Tolerant Networks Routing Protocols

Advances in Micro-Electro-Mechanical Systems (MEMS) have revolutionized the digital age to a point where animate and inanimate objects can be used as a communication channel. In addition, the ubiquity of mobile phones with increasing capabilities and ample resources means people are now effectively mobile sensors that can be used to sense the environment as well as data carriers. These objects, along with their devices, form a new kind of networks that are characterized by frequent disconnections, resource constraints and unpredictable or stochastic mobility patterns. A key underpinning in these networks is routing or data dissemination protocols that are designed specifically to handle the aforementioned characteristics. Therefore, there is a need to review state-of-the-art routing protocols, categorize them, and compare and contrast their approaches in terms of delivery rate, resource consumption and end-to-end delay. To this end, this paper reviews 63 unicast, multicast and coding-based routing protocols that are designed specifically to run in delay tolerant or challenged networks. We provide an extensive qualitative comparison of all protocols, highlight their experimental setup and outline their deficiencies in terms of design and research methodology. Apart from that, we review research that aims to exploit studies on social networks and epidemiology in order to improve routing protocol performance. Lastly, we provide a list of future research directions.Comment: 56 page

MPAR: A Movement Pattern-Aware Optimal Routing for Social Delay Tolerant Networks

Social Delay Tolerant Networks (SDTNs) are a special kind of Delay Tolerant Network (DTN) that consists of a number of mobile devices with social characteristics. The current research achievements on routing algorithms tend to separately evaluate the available profit for each prospective relay node and cannot achieve the global optimal performance in an overall perspective. In this paper, we propose a Movement Pattern-Aware optimal Routing (MPAR) for SDTNs, by choosing the optimal relay node(s) set for each message, which eventually based on running a search algorithm on a hyper-cube solution space. Concretely, the movement pattern of a group of node(s) can be extracted from the movement records of nodes. Then the set of commonly visited locations for the relay node(s) set and the destination node is obtained, by which we can further evaluate the co-delivery probability of the relay node(s) set. Both local search scheme and tabu-search scheme are utilized in finding the optimal set, and the tabu-search based routing Tabu-MPAR is proved able to guide the relay node(s) set in evolving to the optimal one. We demonstrate how the MPAR algorithm significantly outperforms the previous ones through extensive simulations, based on the synthetic SDTN mobility model.Comment: 18 page