—Routing is one of the difficult issues in mobile opportunistic networks, due to the lack of global knowledge and sporadic links. Related works use a greedy strategy to forward packets, i.e., they select relays with higher/bigger quality metrics. In this paper, we study the Opportunistic Routing Protocols (ORPs) from the perspective of social network analysis. Specifically, we discuss the impact of social relationship on the performance of ORPs. We first classify nodes into strangers and friends. We then explore the optimized number of strangers we can employ. Third, we propose STRON, a socially aware data forwarding scheme by taking both STRangers and their Optimized Number into account. We finally compare STRON with the state-of-the-art works through synthetical and trace-driven simulations, the numerical results demonstrate that STRON achieves a better performance, especially in terms of combined overhead/packet delivery ratio and the average number of hops per message.

—Opportunistic networks exploit human mobility and consequent device-to-device contacts to opportunistically create data paths over time. Identifying influential nodes as relay is a crucial problem for efficient routing in opportunistic networks. The degree centrality method is very simple but of little relevance. Although closeness centrality and betweenness centrality can effectively identify influential nodes, they are incapable to be applied in large-scale networks due to the high computational complexity. In this paper, we focus on designing an effective centrality ranking metric with low computational complexity in opportunistic networks. We propose the semi locally evaluated centrality metric to identify influential nodes for message forwarding in opportunistic networks. We also present a simple message forwarding algorithm, and employ real world mobility traces and synthetic mobility traces to evaluate the benefits of the proposed semi locally evaluated centrality metric. Results demonstrate the efficiency of the proposed metric in opportunistic networks.

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powered by The constellations of the Milky Way have been guiding our ancestors for thousands of years. The stars have helped us to navigate, govern the seas and discover new lands. In the rise of the 21st century discovery, communication and navigation are still prominent to the advancement of our kind. The new means to humanity’s eternal goals are smartphone devices powered with sensors, advanced software and cloud supported internet connectivity. A significant evolution in the past four years has been the rise of location-based social networks. Systems like Foursquare enable the crowdsourcing of unprecedented amounts and layers of information describing the location, activity and communication traits of millions of mobile users at a global scale. Not only they promise the large scale evaluation of past theories in fields of urban transport, social science and geography, but they offer the opportunity for novel applications for the computer sciences.In the era of the mobile web, the stars are the mobile users.

lay Tolerant Network (DTN) is a wireless network that experience frequent and long duration partitions during transmission of data. The fully connected path from source to destination is u nli ke l y to exist. And due to the existenc e of contemporaneous connectivity b e t w e e n n o d e s, n e t w o r k topology may change dynamically and randomly. This leads to a problem of how to route a packet from one node to another in DTN. Most of the nodes in DTN are mobile, so that the connectivity is established when they come into the transmission range of each other. The design of a routing protocol for this type of network is an important issue. This work, surveys various routing strategies in Delay Tolerant Networks.. General Terms Scalability, Resource consumption, Hop count, Delivery ratio. Keywordsay Tolerant Networks (DTN), opportunistic communication, Mobility, flooding.

connected mobile ad-hoc networks are kind of wireless networks where end to end connectivity unlikely exists. Routing in such environment is carried out through the store-carry-forward mechanism. Thus, message delivery relies on node"s mobility, their contact opportunities and contact patterns. Intermittently connected mobile ad-hoc networks can be viewed as dynamic graph, where mobile nodes are vertices and contact between nodes are edges. Such graph constantly evolves as node"s connection, disconnection and reconnection and reveals the dynamic behaviour of the network. Detecting and dealing with congestion in delay tolerant networks is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards particular nodes in order to maximize delivery ratios and minimize delays, but as traffic demands increase these nodes may become unusable. In this thesis we attempted to improve BUBBLE RAP algorithm performance by using congestion control, forwarded message exchange and message priority update mechanism. We proposed Congestion Control algorithm (CCA) to reduce the congestion occurring on highly social nodes and to improve the forwarding efficiency significantly compared to oblivious forwarding schemes. In CCA algorithm, the congestion level of node and message priority are utilized to construct a Congestion Metric (CM). In the forwarding process, the concept of message forwarding to lower CM valued nodes is added together with the BUBBLE RAP strategy to improve the delivery probability as well as together with that a try to reduce the congestion by dropping the messages over nodes having low centrality links with destination is also made.

Within vehicular delay-tolerant network, conflict exists in the scenario of which two vehicles happen to choose the same parking space. To solve this problem, two protocols are proposed, respectively, which are called privacy protection protocol based on secure multiparty computation and routing protocol based on angle and density. The proposed methods prevent the leaking of privacy information of the vehicles involved during the parking space seeking process and improve the performance of the transmission ratio and reduce the transmission delay by unifying the directions of messages and choosing the vehicle of the highest distribution density as the next hop. The results of the simulation show the efficiency of our method.

With wide applications of intelligent handset devices, social networks have received more and more attentions. Currently, Disruption-Tolerant Networking provides a feasible content-distribution solution for a mobile device-dependent social network through its store-and-forward mechanism. This article puts forward an interest-driven routing algorithm for a Disruption-Tolerant Networking social networks, in which those nodes with similar interests are grouped into a same community to achieve reliable and resource-efficient forwarding of messages. In particular, each local node carrying a message will forward it by selecting the next-hop nodes with stronger Community Social Strength in the candidate node set with partial overlapped interests. On the other side, if the local node does not find a next-hop node with partially equivalent interests, the message will be forwarded to a next-hop node with a stronger Perceived Social Strength. Through the simulation experiments, the proposed routing algorithm could effectively improve the message delivery rate, average hop-count and load, compared with Epidemic and Prophet routing algorithms.

With their proliferation and increasing capabilities, mobile devices with local wireless interfaces can be organized into delay-tolerant networks DTNs that exploit communication opportunities arising out of the movement of their users. As the mobile devices are usually carried by people, these DTNs can also be viewed as social networks. Unfortunately, most existing routing algorithms for DTNs rely on relatively simple mobility models that rarely consider these social network characteristics, and therefore, the mobility models in these algorithms cannot accurately describe users' real mobility traces. In this paper, we propose two predict and spread PreS message routing algorithms for DTNs. We employ an adapted Markov chain to model a node's mobility pattern and capture its social characteristics. A comparison with state-of-the-art algorithms demonstrates that PreS can yield better performance in terms of delivery ratio and delivery latency, and it can provide a comparable performance with the epidemic routing algorithm with lower resource consumption. Copyright © 2013 John Wiley & Sons, Ltd.

With the wide use of smart mobile devices and the popularity of mobile social networks (MSNs), direct marketing has been adopted by more and more companies to announce the news of their products first to a group of selected profitable customers and let them diffuse the news by "word-of-mouth" to other potential buyers to control the marketing cost. In this paper, we study the diffusion minimization problem whose goal is to select an optimal set of initial nodes to disseminate the information to the whole network as quickly as possible. We tackle the problem by taking advantage of node social features in MSNs. We define dynamic social features to capture nodes' dynamic contact behavior and use social similarity metrics to measure their social closeness. We adopt the community concept in social networks to reduce the complexity of the diffusion minimization problem. We propose novel diffusion node selection algorithms based on these new features to minimize the diffusion time. Simulation results show that our algorithms have lower diffusion times than the existing ones.

With the vigorous development of IOT (Internet of Things), sensor units carried by human beings will form the largest DTMSN in the world. However, most of the existing DTMSN routing protocols haven't taken the characteristics of human mobility into account, and may not work well in human-oriented data gathering. In this paper, we analyze the characteristics of human mobility, and propose a novel delay- based routing protocol (DRP) for human-oriented DTMSN. In DRP, a sensor node calculates the estimated data delivery delay and takes it as a measure of the delivery capacity, the smaller the estimated delay, the higher the delivery capacity of a sensor node. When two nodes meet, data messages are forwarded to the one with smaller estimated delay. To minimize transmission overhead, DRP employs the message rank and survival time to decide message's transmission or dropping. We evaluate the proposed scheme in a real human moving scenario provided by MIT Reality datasets, which collected the traces of 100 individuals of MIT over the course of 9 months. Simulation results have shown that the proposed DRP routing protocol achieves a better performance than some other DTMSN data gathering approaches.

With the ubiquity of mobile phones, a high accuracy of characterizing and modeling people movement is achievable. The knowledge about people's mobility enables many applications including highly efficient planning of cities' resources and network infrastructures, or dissemination of safety alerts. However, characterizing and modeling people movement remain very challenging due to difficulties in (a) capturing, cleaning, analyzing and storing real traces, and (b) achieving accurate predictions of different future contexts.In this paper, we present our effort in measuring and capturing phone sensory data as real traces, cleaning up measurements, and constructing prediction models. Specifically, we discuss design methodology, learned lessons from the implementation and deployment of a large-scale scanning system on 123 Google Android phones for 6 months at University of Illinois campus. We also conduct a characterization study on collected traces and present new findings in location visit pattern, location popularity, and contact pattern. Finally, we exploit joint location/contact traces to derive: (1) predictive models of missing contacts, and (2) prediction framework that provides future contextual information of people movement including locations, stay duration, and social contacts.

With the ubiquitous use of smartphones and other connected pieces of equipment, the number of devices connected to the Internet is exponentially growing. This will test the efficiency of the envisioned 5G network architectures for data acquisition and its storage. It is a common observation that the communication between smart devices is typically influenced by their social relationship. This suggests that the theory of social networks can be leveraged to improve the quality of service for such communication links. In fact, the social networking concepts of centrality and community have been investigated for an efficient realization of novel wireless network architectures. This work provides a comprehensive introduction to social networks and reviews the recent literature on the application of social networks in wireless communications. The potential challenges in communication network design are also highlighted, for a successful implementation of social networking strategies. Finally, some future directions are discussed for the application of social networking strategies to emerging wireless technologies such as non-orthogonal multiple access and visible light communications.

With the remarkable proliferation of intelligent wireless devices and active mobile users, we have witnessed a rapid increasing trend of mobile crowdsourcing applications. While crowdsourcing does not depend on any specific underlying network, the device-to-device (D2D)-based crowdsourcing is highly desired when the originator of a crowdsourcing task cannot directly reach out to the participants or the conventional approaches for data transportation are costly. The marriage of crowdsourcing and D2D creates new, interesting research problems, mainly due to the unique non-deterministic setting in D2D. In this work, we focus on the problem of how to efficiently distribute a crowdsourcing task and recruit participants based on D2D communications. We formally formulate the minimum-cost crowdsourcing (MCC) problem in D2D networks, which explores a multi-dimensional design space to seek an optimal solution that minimizes the total crowdsourcing cost while satisfying the coverage probability over the field of interest. We introduce an approximation algorithm based on a reduced solution space and formally prove that its cost is bounded by a desired approximation ratio in comparison with the optimal solution. We further propose a lightweight online heuristic that inherits the same design philosophy but implements it in a distributed manner. We prototype the proposed online scheme in Android and carry out experiments in a campus environment, involving 21 Dell Streak tablets carried by students for a period of 15 days. We also extract the algorithm codes from our prototype and perform extensive simulations based on Haggle trace. The results demonstrate the efficiency of the proposed heuristics and reveal empirical insights into the design tradeoffs and practical considerations in D2D-based crowdsourcing.

With the recent technical advances and popularization of smartphones, which are able to store, display, and transmit various types of media content, message forwarding in opportunistic mobile social networks has become a hot topic. In this paper, we propose a social-aware single-copy routing approach, which leverages the internal social feature information to resolve the social distance between the source and destination step-by-step. We introduce an optimal social feature forwarding set selection scheme for routing guidance, which is proven to achieve small message forwarding delay. We convert the routing process into an iterative 2-hop routing scheme, with a novel transition probability to measure the delivery delay of each hop. The transition probability is according to the community structure in each social feature space. Extensive simulations on both real and synthetic traces are conducted in comparison with several existing state-of-art approaches.

With the rapid growth of smartphone usage, mobile social networks (MSNs) are becoming increasingly popular. MSN can be considered as a type of delay tolerant network (DTN) which lacks continuous end-to-end connections between nodes, due to the node mobility and limited transmission range. Inspired by the homophily of social networks that friends are usually similar in characteristics, we present a novel concept - cloud, where the nodes in frequent contact with the destinations will form destination clouds. Neighbors in the destination cloud have a special status that can forward the message to the destination directly. We propose a cloud-based multicast scheme with feedback in MSNs with two phases: pre-cloud and inside-cloud. In the pre-cloud process, the message holder will forward the copy of the multicast message to the encountered node, based on a given forwarding metric. The forwarding metric can be iteratively refined from a feedback control mechanism. In the inside-cloud process, the message holder will wait until it meets with the destinations. We analytically formulate the multicast problem into a continuous Markov chain problem, and formally analyze the latency in this model. Extensive trace-driven simulations show that our scheme significantly improves the performance compared to existing schemes.

With the rapid emergence of applications in Mobile Opportunistic Networks (MONs), understanding and characterizing their properties becomes extremely important. A fundamental model for MONs is time-varying graph, which currently remains poorly understood since many well-recognized properties of static graphs have no obvious counterpart in dynamic ones. In MONs, the dynamical links change opportunistically and usually the system energy is very limited, which results in unique and unknown properties about the network connectivity and reachability. In this paper, taking the communication energy into account, we introduce the concept of Energy-aware Temporal Reachability Graphs (ETRG), which characterizes the connectivity of MONs with the consideration of communication consumed energy, and consequently reveals the communication capabilities of MONs with the given of real-world system parameters of data size, tolerable delay, and energy budget. We come up with efficient algorithm to calculate ETRG from the corresponding time-varying graphs. By applying ETRG to several mobile networks recorded by real-life human and vehicular mobility traces, we characterize their network connectivity properties in terms of average reachability, communication asymmetry, and stability. Moreover, utilizing ETRG that places upper bounds of the communications capabilities, we reveal the fundamental relations and tradeoffs among large-scale variability of the system metrics of energy budget, tolerable delay, and data size on the system performance.

With the rapid development of wireless communication technologies, mobile social networks (MSNs) become more and more popular and have attracted much attention from researchers. In this paper, we address the routing issue in MSNs where a set of social related mobile devices communicate opportunistically and intermittently. Existing routing strategies are mostly based on location information (i.e., geographical coordination and physical distance) and social information (i.e., the number of friends and the strength of social ties). These two kinds of information indeed represent two different levels of human behaviors: the location information is concrete and corresponds to the physical property of human activity; while the social information is logical and represents virtual human interactions. In the context of data routing, a rising question is: does the concrete location information outperform the logical social information in designing routing strategies in MSNs? To address the question, we devise a comprehensive social-based routing strategy called Soc and a general location-based strategy called Loc. We provide comprehensive performance comparisons of Soc and Loc together with other social-based and location-based strategies. Our experiment results show that the social-based strategy and the location-based strategy have no significant difference in routing performance: they perform closely in delivery ratio, delay and delivery cost with a slight difference less than 5% in most cases. This indicates that concrete location information is not always necessary to be the key consideration for routing design and logical social information could be potential substitute. Since collecting location information needs dedicated equipment and arguably violates user privacy, our work implies that the proposed social-based routing strategy is safe and effective for MSNs.

With the rapid development of network technology, mobile information service for networks is an important part of people’s lives. This chapter first describes the concept of mobile information service for networks and the general network architecture. Then this chapter introduces the classification of the mobile information services for networks, and finally lists the roles of key technologies in mobile information service for networks according to a hierarchical structure. In this book, network neighbor discovery technology, efficient network routing, user association technology, and network community detection technology will be elaborated later. After introducing these main technologies, this book will introduce mobile information service platform for networks and related applications in intelligent transportation, smart tourism, and mobile payment. Mobile information service for networks involves many techniques and methods. This book is only a summary of authors’ recent innovative work about smart city. We hope that with the development of the times, new technologies will emerge continuously. 1.1 Concept and Development of Mobile Information Service for Networks The rapid development of wireless network technology promotes extensive use of mobile devices such as mobile phones, tablets, and ultrabooks. The mobile network provides a solid platform for mobile nodes interconnections and applications of related services. To deal with various scenarios of human activities, information service based on the wireless mobile network has become a research hotspot. We define Mobile Information Service for Networks as a platform-independent functional entity that provides various services based on the communication network platform. Mobile information services can be published on the network through various mobile devices in the method of wireless access networks [1]. With the development of 5G and Internet of Things, the carriers of mobile services not only include handheld devices but also include physical devices related to individuals, such as vehicles [2–4]. © Springer Nature Singapore Pte Ltd. & Science Press 2020 C. Jiang and Z. Li,Mobile Information Service for Networks, https://doi.org/10.1007/978-981-15-4569-6_1 1 2 1 Preliminary of Mobile Information Service for Networks According to preliminary data released by App Annie, an app analytics company, the number of APP downloads exceeded 204 billion in 2019, an increase of 6% compared to last year. The total expenditure on paid applications, in-app purchases, etc., is $120 billion.Mobile users spend an average of 3.7 hours onAPP each day. The explosive development has made mobile information services penetrate into every corner of people’s lives. There are many disciplines involved in mobile information service for networks. This book conducts a layered introduction to analyze related theoretical methods, and introduces new application technologies. Since the current mobile information service for networks is different from traditional information services, the requirements of adaptability of network changes, efficiency, security, accuracy, energy and sociality all bring about great challenges to its further developments. 1.2 Network Communication Architecture According to the types of applications and communication standards, mobile information service for networks can be deployed under a centralized, distributed, or hybrid network communication architecture. (1) Centralized Architecture (e.g. cellular networks): A centralized server can exchange, share, and transmit data between content providers and mobile users. In this client/server structure, the user is a client and the server provides contents such asmaps, and videos. Under the centralized architecture, data is passed through third-party applications or service providers. This architecture is widely used in the network communications nowadays. The centralized communication architecture can not only provide information services efficiently and conveniently, but also can control the network globally. However, there are also some problems such as single point failure, privacy leakage [5]. (2) Distributed Architecture (e.g. networks supporting Ad hoc communication modes): Mobile users can directly establish P2P transmission links by using technologies such as Wi-Fi and Bluetooth. Under this architecture, nodes use the “storage-carry-forward” protocol to keep real-time communications in the physical world. Services based on this type of architecture are some location-based services [6], such as E-SmallTalker [7], MobiClique [8], Who’s Near Me. The distributed architecture can be used as an effective way to reduce the transmission pressure of centralized base stations. However, the distributed architecture cannot be applied in large-scale areas. (3) Hybrid Architecture: The centralized architecture is usually used by service providers while the distributed architecture has been promoting by the academic communities. A hybrid architecture can perfectly combine the domains of industry and academy together. In a hybrid architecture, a distributed network usually assists a centralized network to realize various services. 1.3 Classification of Mobile Information Service for Networks 3 1.3 Classification of Mobile Information Service for Networks Referring to the 2019 APP classification list given by Internet Weekly & eNet Research Institute, the content of mobile information service for networks includes the following 14 types: (1) Social welfare; (2) Government functions, such as party affairs, police affairs, taxation, citizen cloud, and labour unions; (3) Audio and video entertainment, such as video, live broadcast, games, music, and radio; (4) News such as books, and comics; (5) E-commerce platform (domestic or overseas); (6) Travel and transport, such as maps, taxis, tour, ticketing, accommodation, guides, and car rental; (7) Health care, such as body-building and medical treatment; (8) Social; (9) Financial management, such as banking, securities, insurance, stocks, investment, and management; (10) Automobile industry, such as charging of new energy vehicles and vehicle after sales service platform; (11) Learning and education; (12) Enterprise, such as mailbox, enterprise cooperation, customer relationship management, andfinancial affairs; (13)Utility tools, such as inputmethod,wallpaper, browser, network security protection, search engines, weather forecast, application market, calendar, and transmission backup; (14) Leisures, such as beauty makeup, meal ordering, house lease, home furnishings, community service, job hunting, and express logistics. In addition, the main external impacting factors of mobile information service for networks are the mobile environment and the individual. Therefore, the mobile information service modes can be divided into instant services, location-based services and personalized services [9] based on the three factors: time, location and individual. The instant service mode can provide users with required information and services according to users’ instant needs in a mobile environment. The instant information includes vehicles’ security warning in Chap. 6, news, financial market, instant communications, etc. The location-based service mode provides users with required geographic information and other information services related to the geographical location. These services are based on the geographical locations of users in a mobile environment. The location-based services include vehicle trajectory analysis in Chap. 6, location recommendations in Chap. 7, weather forecast, chatting and making friends, etc. The personalized service mode can provide targeted information services for the personalized needs of users. And it can also establish an information demand model for users by utilizing a mobile information service system based on the privacy and identifiability of mobile terminals. The personalized services include personal payment authentications in Chap. 8, personalized location recommendation, personalized search and subscription services. 4 1 Preliminary of Mobile Information Service for Networks 1.4 Key Technologies of Mobile Information Service for Networks In this book, we will introduce some key technologies of mobile information service for networks according to a hierarchical structure and application backgrounds. To beginwith,wemainly introduce themajor technologies ofmobile information service for networks in three layers: • Neighbor discovery technology in the data link layer. • Efficient network routing and balanced association technology in the network layer. • Network community detection technology in the application layer. Then, we will introduce some extension technologies for three main applications involved in a smart city, i.e., intelligent transportation, smart tourism, and mobile payment. The content structure of this book is shown in Fig. 1.1. The key technologies and methods of mobile information service for networks include the following aspects: (1) Neighbor discovery technology. In the mobile information service, neighbor discovery is an important technology in the data link layer. It is a technology that can discover neighbor nodes and establish effective connections. This technology guarantees the first step of the network building. High efficiency, energy-saving, and scene adaptation are problems encountered by the current technology. Therefore, for social application scenarios and crowded scenarios, this book presents a role-based neighbor discovery method and a crowded scenario-based neighbor discovery method, respectively. More details will be provided in Chap. 2. (2) Efficient network routing and balanced association technology. In the network layer, the efficiency of various information services, depends on fast data transmissions. Traditional routing protocols that depend on the network topology or Neighbor Discovery Technology Netw