Comparison studies of MANET-satellite and MANET-cellular networks integrations

A mobile ad hoc network (MANET) is a self-configuring infrastructure-less network. Taking advantage of spontaneous and infrastructure-less behavior, MANET can be integrated with satellite network to provide world-wide communication for emergency and disaster relieve services and can also be integrated with cellular network for mobile data offloading. To achieve different purposes, different architecture of integrated system, protocols and mechanisms are designed. For emergency services, ubiquitous and robust communications are of paramount importance. For mobile data offloading services, emphasis is amount of offloaded data, limited storage and energy of mobile devices. It is important to study the common features and distinguish of the architecture and service considerations for further research in the two integrated systems. In this paper, we study common issues and distinguish between two systems in terms of routing protocol, QoS provision, energy efficiency, privacy protection and resource management. The future research can benefit from taking advantage of the similarity of two systems and address the relevant issues

Flooding Data in a Cell: Is Cellular Multicast Better than Device-to-Device Communications?

International audienceA natural method to disseminate popular data on cellular networks is to use multicast. Despite having clear advantages over unicast, multicast does not offer any kind of reliability and could result costly in terms of cellular resources in the case at least one of the destinations is at the edge of the cell (i.e., with poor radio conditions). In this paper, we show that, when content dissemination tolerates some delay, providing device-to-device communications over an orthogonal channel increases the efficiency of multicast, concurring also to offload part of the traffic from the infrastructure. Our evaluation simulates an LTE macro-cell with mobile receivers and reveals that the joint utilization of device-to-device communications and multicasting brings significant resource savings while increasing the cellular throughput

Content-centric wireless networks with limited buffers: when mobility hurts

We analyze throughput–delay scaling laws of mobile ad hoc networks under a content-centric traffic scenario, where users are mainly interested in retrieving contents cached by other nodes. We assume limited buffer size available at each node and Zipf-like content popularity. We consider nodes uniformly visiting the network area according to a random-walk mobility model, whose flight size varies from the typical distance among the nodes (quasi-static case) up to the edge length of the network area (reshuffling mobility model). Our main findings are: 1) the best throughput–delay tradeoffs are achieved in the quasi-static case: increasing the mobility degree of nodes leads to worse and worse performance; ii) the best throughput–delay tradeoffs can be recovered by power control (i.e., by adapting the transmission range to the content) even in the complete reshuffling case

DROiD: Adapting to Individual Mobility Pays Off in Mobile Data Offloading

International audienceCellular operators count on the potentials of offloading techniques to relieve their overloaded data channels. Beyond standard access point-based offloading strategies, a promising alternative is to exploit opportunistic direct communication links between mobile devices. Nevertheless, achieving efficient device- to-device offloading is challenging, as communication opportunities are, by nature, dependent on individual mobility patterns. We propose, design, and evaluate DROiD (Derivative Reinjection to Offload Data), an original method to finely control the distribution of popular contents throughout a mobile network. The idea is to use the infrastructure resources as seldom as possible. To this end, DROiD injects copies through the infrastructure only when needed: (i) at the beginning, in order to trigger the dissemination, (ii) if the evolution of the opportunistic dissemination is below some expected pace, and (iii) when the delivery delay is about to expire, in order to guarantee 100% diffusion. Our strategy is particularly effective in highly dynamic scenarios, where sudden creation and dissolution of clusters of mobile nodes prevent contents to diffuse properly.We assess the performance of DROiD by simulating a traffic information service on a realistic large-scale vehicular dataset composed of more than 10,000 nodes. DROiD substantially outperforms other offloading strategies, saving more than 50% of the infrastructure traffic even in the case of tight delivery delay constraints. DROiD allows terminal- to-terminal offloading of data with very short maximum reception delay, in the order of minutes, which is a realistic bound for cellular user acceptance

A New Competitive Ratio for Network Applications with Hard Performance Guarantee

Online algorithms are used to solve the problems which need to make decisions without future knowledge. Competitive ratio is used to evaluate the performance of an online algorithm. This ratio is the worst-case ratio between the performance of the online algorithm and the offline optimal algorithm. However, the competitive ratios in many current studies are relatively low and thus cannot satisfy the need of the customers in practical applications. To provide a better service, a practice for service provider is to add more redundancy to the system. Thus we have a new problem which is to quantify the relation between the amount of increased redundancy and the system performance. In this dissertation, to address the problem that the competitive ratio is not satisfactory, we ask the question: How much redundancy should be increased to fulfill certain performance guarantee? Based on this question, we will define a new competitive ratio showing the relation between the system redundancy and performance of online algorithm compared to offline algorithm. We will study three applications in network applications. We propose online algorithms to solve the problems and study the competitive ratio. To evaluate the performances, we further study the optimal online algorithms and some other commonly used algorithms as comparison. We first study the application of online scheduling for delay-constrained mobile offloading. WiFi offloading, where mobile users opportunistically obtain data through WiFi rather than through cellular networks, is a promising technique to greatly improve spectrum efficiency and reduce cellular network congestion. We consider a system where the service provider deploys multiple WiFi hotspots to offload mobile traffic with unpredictable mobile users’ movements. Then we study online job allocation with hard allocation ratio requirement. We consider that jobs of various types arrive in some unpredictable pattern and the system is required to allocate a certain ratio of jobs. We then aim to find the minimum capacity needed to meet a given allocation ratio requirement. Third, we study online routing in multi-hop network with end-to-end deadline. We propose reliable online algorithms to schedule packets with unpredictable arriving information and stringent end-to-end deadline in the network

모바일 소셜네트워크에서 사용자간 기회적인 공유기반트래픽 오프로딩

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

Multiple Mobile Data Offloading Through Delay Tolerant Networks

To cope with the explosive traffic demands and limited capacity provided by the current cellular networks, Delay Tolerant Networking (DTN) is used to migrate traffic from the cellular networks to the free and high capacity device-todevice networks. The current DTN-based mobile data offloading models do not address the heterogeneity of mobile traffic and are based on simple network assumptions. In this paper, we establish a mathematical framework to study the problem of multiple mobile data offloading under realistic network assumptions, where 1) mobile data is heterogeneous in terms of size and lifetime, 2) mobile users have different data subscribing interests, and 3) the storage of offloading helpers is limited. We formulate the maximum mobile data offloading as a Submodular Function Maximization problem with multiple linear constraints of limited storage and propose greedy, approximated and optimal algorithms for different offloading scenarios. We show that our algorithms can effectively offload data to DTNs by extensive simulations which employ real traces of both humans and vehicles