944 research outputs found

    Content Dissemination in Mobile Social Networks

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    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

    Optimal channel choice for collaborative ad-hoc dissemination

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    Abstract—Collaborative ad-hoc dissemination of information has been proposed as an efficient means to disseminate information among devices in a wireless ad-hoc network. Devices help in forwarding the information channels to the entire network, by disseminating the channels they subscribe to, plus others. We consider the case where devices have a limited amount of storage that they are willing to devote to the public good, and thus have to decide which channels they are willing to help disseminate. We are interested in finding channel selection strategies which optimize the dissemination time across the channels. We first consider a simple model under the random mixing assumption; we show that channel dissemination time can be characterized in terms of the number of nodes that forward this channel. Then we show that maximizing a social welfare is equivalent to an assignment problem, whose solution can be obtained by a centralized greedy algorithm. We show empirical evidence, based on Zune data, that there is a substantial difference between the utility of the optimal assignment and heuristics that were used in the past. We also show that the optimal assignment can be approximated in a distributed way by a Metropolis-Hastings sampling algorithm. We also give a variant that accounts for battery level. This leads to a practical channel selection and reselection algorithm that can be implemented without any central control. I

    Context-awareness for mobile sensing: a survey and future directions

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    The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

    Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey

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    The integration of things’ data on the Web and Web linking for things’ description and discovery is leading the way towards smart Cyber–Physical Systems (CPS). The data generated in CPS represents observations gathered by sensor devices about the ambient environment that can be manipulated by computational processes of the cyber world. Alongside this, the growing use of social networks offers near real-time citizen sensing capabilities as a complementary information source. The resulting Cyber–Physical–Social System (CPSS) can help to understand the real world and provide proactive services to users. The nature of CPSS data brings new requirements and challenges to different stages of data manipulation, including identification of data sources, processing and fusion of different types and scales of data. To gain an understanding of the existing methods and techniques which can be useful for a data-oriented CPSS implementation, this paper presents a survey of the existing research and commercial solutions. We define a conceptual framework for a data-oriented CPSS and detail the various solutions for building human–machine intelligence

    모바일 소셜네트워크에서 사용자간 기회적인 공유기반트래픽 오프로딩

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    학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2013. 8. 최양희.최근 모바일 트래픽의 빠른 증가는 이동통신 사업자에게 심각한 문제가 되고 있다. 이러한 문제를 해결하기 위해 단거리 통신 기술 및 모바일 소셜 네트워크 등을 이용하여 사용자간 직접 데이터를 주고 받는 오프로딩 기법을 사용하는 것에 대한 연구가 이루어지고 있다. 본 논문에서는 사용자간 직접 통신을 통한 효율적인 콘텐츠 공유 및 오프로딩 기법을 제안하고자 한다. 첫번째 연구로, 모바일 소셜 네트워크에서 사용자간 직접 전송기회를 활용해 데이터를 공유하는 모바일 트래픽 오프로딩의 핵심 기술인 TOSS를 제안 하였다. TOSS에서는 셀룰러 네트워크에서 급속히 증가하고 있는 트래픽으로 인한 네트워크 과부하를 경감시키기 위해 온라인 소셜 네트워크에서 사용자의 연결성 및 오프라인 네트워크에서 사용자의 이동성을 고려하여 콘텐츠를 전달할 사용자를 결정하고 블루투스나 와이파이 다이렉트 등의 기술을 이용해 콘텐츠를 직접 전달 하였다. 또한 소셜네트워크 서비스 사용자의 서로 다른 콘텐츠 접근 패턴, 즉 각 사용자가 콘텐츠 생성으로부터 오프로딩을 위해 콘텐츠에 접근하기까지의 시간을 고려 하였다. 본 연구에서는 이러한 요건을 고려하여 트래픽 오프로딩과 콘텐츠 확산을 모델링하고 분석 하였다. 모바일 소셜 네트워크의 데이타 셋을 기반으로 분석 결과에서 TOSS는 모든 사용자의 딜레이 요구조건을 만족시키면서 최대 86.5의 셀룰러 트래픽을 경감시키는 것을 보였다. 두번째의 연구에서는 모바일 네트워크에서 멀티셀을 고려하여 콘텐츠를 배포하는 프레임워크에 대한 연구를 진행 하였다. 해당 프레임워크에서 콘텐츠는 셀룰러 링크와 모바일 사용자간 로컬 링크를 통해 푸시-공유 기반의 통신으로 전달 되였다. 이러한 기법을 바탕으로 multi-compartment 모델을 이용하여 셀 간 핸드오버 및 콘텐츠 전달을 모델링 및 분석하고, 콘텐츠 전달 딜레이와 에너지 소모 사이의 trade-off를 수학적인 최적화 기법을 사용하여 해결 하였다. 본 논문에서는 이와 같이 기존의 측정 연구에 기반한 trace-driven 분석, 모델링 및 시스템 최적화에 대한 연구를 통해 모바일 소셜 네트워크에서 사용자간 직접 전송을 통한 오프로딩 기법이 고효율적임을 보였다. 또한 본 논문은 제안된 기법의 상용화 전망 및 이를 위한 이슈들에 대한 논의도 포함 하였다.The fast increasing traffic demand becomes a serious concern of mobile network operators. To solve this traffic explosion problem, there have been efforts to offload the traffic from cellular links to local short-range communications among mobile users that are moving around and forming mobile social networks. In my thesis, I mainly focus on the user-to-user opportunistic sharing and try to elaborate its effectiveness and efficiency for to offload mobile traffic. In the first work, I propose the Traffic Offloading assisted by Social network services via opportunistic Sharing in mobile social networks, TOSS. In TOSS, initially a subset of mobile users are selected as initial seeds depending on their content spreading impact in online social network services (SNSs) and their mobility patterns in offline mobile social networks (MSNs). Then users share the content via opportunistic local connectivity (e.g., Bluetooth, Wi-Fi Direct) with each other. Due to the distinct access patterns of individual SNS users, TOSS further exploits the user-dependent access delay between the content generation time and each user's access time for the purpose of traffic offloading. I model and analyze process of the traffic offloading and content spreading by taking into account various options in linking SNS and MSN data sets. The trace-driven evaluation shows that TOSS can reduce up to 86.5% of the cellular traffic while satisfying the access delay requirements of all users. In the second work, I focus on the analytical research on Push-Share framework for content disseminating in mobile networks. One content is firstly pushed the to a subset of subscribers via cellular links, and mobile users spread the content via opportunistic local connectivity. I theoretically model and analyze how the content can be disseminated, where handovers are modeled based on the multi-compartment model. I also formulate the mathematical optimization framework, by which the trade-off between the dissemination delay and the energy cost is explored. Based on the measurement study, trace-driven analysis, theoretical modeling and system optimization in above papers, the traffic offloading by user-to-user opportunistic sharing in mobile social networks is proved to be effective and efficient. Additionally, further discussions on the practical deployment, future vision, and open issues are discussed as well.Abstract i I. Introduction 1 II. RelatedWork 7 2.1 Opportunistic Sharing in DTNs/MSNs 7 2.2 Mobile Traffic Offloading 9 2.3 Information/Content Spreading in SNSs 10 III. TOSS 13 3.1 Framework Details 13 3.1.1 Preliminaries 13 3.1.2 Spreading Impact in the Online SNS 16 3.1.3 Access Delays of Users in the SNS 18 3.1.4 Mobility Impact in the Offline MSN 21 3.2 System Optimization 25 3.3 Trace-Driven Measurement 26 3.3.1 Measurement of the Online SNS 26 3.3.2 Measurement of Offline MSNs, λi j and IM 33 3.3.3 Content Obtaining Delays 36 3.3.4 How C Impacts the Obtaining Delay 38 3.4 Performance Evaluation 39 3.4.1 How C Impacts the Total Access Utility 39 3.4.2 Satisfying 100%, 90%, and 80% of Users 44 3.4.3 On-Demand Delivery 47 3.5 Conclusion 48 IV. Push-Share 50 4.1 Framework Details 50 4.2 System Model 53 4.3 Content Dissemination in Single Cell 56 4.3.1 Content Dissemination by Sharing Only 57 4.3.2 Content Dissemination with Initial Push and Final Push 59 4.3.3 Content Dissemination Energy Cost 62 4.4 Content Dissemination in Multiple Cells 63 4.4.1 Non-steady-state Modeling of MSs in Multiple Cells 66 4.4.2 Steady-State Modeling of MSs in Multiple Cells 66 4.4.3 How Handovers Affect the Content Dissemination 67 4.5 Optimization Framework 69 4.5.1 Minimum Dissemination Completion Delay 69 4.5.2 Minimum Dissemination Completion Cost 70 4.5.3 Conjunctive Minimization of Delay and Cost 71 4.6 Evaluation Results 73 4.6.1 Content Dissemination within One Single Cell 74 4.6.2 Content Dissemination within Multiple Cells 77 4.6.3 Optimization Framework 80 4.7 Conclusion 82 V. Summary and Future Work 84 5.1 A Comparison with Traffic Offloading based on Wi-Fi APs 85 5.2 Practical Deployment and Application 86 5.3 Future Work and Vision 88 Bibliography 90Docto

    SECURE AND EFFICIENT INFORMATION MANAGEMENT IN DELAY(DISRUPTION) TOLERANT NETWORK

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    In environments like international military coalitions on the battlefield or multi-party relief work in a disaster zone, multiple teams are deployed to serve different mission goals by the command-and-control center (CC). They may need to survey damages and send information to the CC for situational awareness and also transfer messages to each other for mission purposes. However, due to the damaged network infrastructure in the emergency, nodes need to relay messages using the store and forward paradigm, also called Delay-tolerant Networks (DTNs). In DTN, the limited bandwidth, energy, and contacts among the nodes, and their interdependency impose several challenges such as sensitive data leakage to malicious nodes, redundant data generation, limited and delayed important message delivery, non-interested messages in storage, etc. We aim to focus on solving these challenges. We propose message fragmentation for secure message transfer because existing public-private-key cryptographic approaches may not work due to the unavailability of Public Key Infrastructure (PKI). Besides, to ensure more message delivery, redundant fragments are generated. However, too much redundancy may consume the energy and bandwidth of the nodes while transferring similar messages. Hence, we propose to send diverse content and limit the redundancy. Again, the dynamic environment we consider is prone to many adverse and sudden events. We aim to respond to these events by sending the event-related message to the CC fast with the help of intermediate nodes. The nodes are interested in certain types of content defined by their mission and interest. Therefore, we target to learn nodes\u27 interests using Reinforcement Learning so that the nodes can populate themselves with the messages according to their mission requirements and increase the collaboration among them. Our future work will include machine learning techniques for predicting important places where node encounters the most and to cache data for each other according to their interest, encounter frequency, and encounter locations --Abstract, p. i

    Data Storage and Dissemination in Pervasive Edge Computing Environments

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    Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, mobile devices often experience poor connectivity, leading to availability issues if application storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed. Hence, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. This thesis focuses on the design and evaluation of resilient and efficient data storage and dissemination solutions for pervasive edge computing environments, operating with or without access to the network infrastructure. In line with this dichotomy, our goal can be divided into two specific scenarios. The first one is related to the absence of network infrastructure and the provision of a transient data storage and dissemination system for networks of co-located mobile devices. The second one relates with the existence of network infrastructure access and the corresponding edge computing capabilities. First, the thesis presents time-aware reactive storage (TARS), a reactive data storage and dissemination model with intrinsic time-awareness, that exploits synergies between the storage substrate and the publish/subscribe paradigm, and allows queries within a specific time scope. Next, it describes in more detail: i) Thyme, a data storage and dis- semination system for wireless edge environments, implementing TARS; ii) Parsley, a flexible and resilient group-based distributed hash table with preemptive peer relocation and a dynamic data sharding mechanism; and iii) Thyme GardenBed, a framework for data storage and dissemination across multi-region edge networks, that makes use of both device-to-device and edge interactions. The developed solutions present low overheads, while providing adequate response times for interactive usage and low energy consumption, proving to be practical in a variety of situations. They also display good load balancing and fault tolerance properties.Resumo Hoje em dia, os dispositivos móveis inteligentes geram grandes quantidades de dados em todos os tipos de aglomerações de pessoas. Muitos desses dados têm interesse loca- lizado e efêmero, mas podem ser de grande utilidade se partilhados entre dispositivos co-localizados. No entanto, os dispositivos móveis muitas vezes experienciam fraca co- nectividade, levando a problemas de disponibilidade se o armazenamento e a lógica das aplicações forem totalmente delegados numa infraestrutura remota na nuvem. Por sua vez, o paradigma de computação na periferia da rede leva as computações e o armazena- mento para além dos centros de dados, para mais perto dos dispositivos dos utilizadores finais onde os dados são gerados e consumidos. Assim, permitindo a execução de certos componentes de sistemas direta e cooperativamente em dispositivos na periferia da rede. Esta tese foca-se no desenho e avaliação de soluções resilientes e eficientes para arma- zenamento e disseminação de dados em ambientes pervasivos de computação na periferia da rede, operando com ou sem acesso à infraestrutura de rede. Em linha com esta dico- tomia, o nosso objetivo pode ser dividido em dois cenários específicos. O primeiro está relacionado com a ausência de infraestrutura de rede e o fornecimento de um sistema efêmero de armazenamento e disseminação de dados para redes de dispositivos móveis co-localizados. O segundo diz respeito à existência de acesso à infraestrutura de rede e aos recursos de computação na periferia da rede correspondentes. Primeiramente, a tese apresenta armazenamento reativo ciente do tempo (ARCT), um modelo reativo de armazenamento e disseminação de dados com percepção intrínseca do tempo, que explora sinergias entre o substrato de armazenamento e o paradigma pu- blicação/subscrição, e permite consultas num escopo de tempo específico. De seguida, descreve em mais detalhe: i) Thyme, um sistema de armazenamento e disseminação de dados para ambientes sem fios na periferia da rede, que implementa ARCT; ii) Pars- ley, uma tabela de dispersão distribuída flexível e resiliente baseada em grupos, com realocação preventiva de nós e um mecanismo de particionamento dinâmico de dados; e iii) Thyme GardenBed, um sistema para armazenamento e disseminação de dados em redes multi-regionais na periferia da rede, que faz uso de interações entre dispositivos e com a periferia da rede. As soluções desenvolvidas apresentam baixos custos, proporcionando tempos de res- posta adequados para uso interativo e baixo consumo de energia, demonstrando serem práticas nas mais diversas situações. Estas soluções também exibem boas propriedades de balanceamento de carga e tolerância a faltas
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