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Disseminating Multilayer Multimedia Content Over Challenged Networks

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Abstract

Mobile devices are getting increasingly popular all over the world. Mobile users in developing countries, however, rarely have Internet access, which puts them at economic and social disadvantages compared to their counterparts in developed countries. We propose mBridge: a distributed system to disseminate multimedia content to mobile users with intermittent Internet access and opportunistic ad-hoc connectivity. By disseminating various multimedia content, such as news reports, notification messages, targeted advertisements, movie trailers, and TV shows, mBridge aims to eliminate the digital divide. We formulate an optimization problem to compute personalized distribution plans for individual mobile users, to maximize the overall user experience under various resource constraints. Our formulation jointly considers the characteristics of multimedia content, mobile users, and intermittent networks. We present an efficient distribution planning algorithm to solve our problem, and we develop several online heuristics to adapt to the system and network dynamics. We implement a prototype system and demonstrate that our algorithm outperforms the existing algorithms by up to 206%, 472% and 188% in terms of user experience, disk efficiency, and energy efficiency, respectively. In addition, we conduct trace-driven simulations to rigorously evaluate the proposed system in different environments and for large-scale deployments. Our simulation results demonstrate that the proposed algorithm substantially outperforms the closest ones in the literature in all performance measures. We believe that mBridge can allow multimedia content providers to reach out to more mobile users, and mobile users to access multimedia content without always-on Internet access.

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Cooperation among devices is an important part of green communication. As one of the core techniques of 5G technology, device-to-device (D2D) technology is able to improve spectrum efficiency and take advantage of the neighborhood information. While most of the existing work focuses on D2D pairs, clustering technology can bring benefits, especially in energy efficiency. In this article we focus on the benefits of energy saving when location-aware devices cooperate. More specifically, the green communication of location-aware devices is discussed from two aspects: the exploration of energy and the exploitation of energy. The exploration of energy refers to harvesting energy from transmitted signals, providing a dependable energy source. The exploitation of energy, on the other hand, refers to an efficient tactic to use the accumulated energy based on location-aware clustering technology. Combining the two technologies, communication among location-aware devices is coordinated to be energy efficient and highly sustainable.
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Cellular network is widely used and device-to-device (D2D)-assisted approaches have been proposed for improving performance on spectrum efficiency, overall throughput and energy efficiency. However, few of them have considered the downlink transmission for multiple concurrent devices from an energy efficiency perspective. In this paper, we focus on a D2D-assisted cellular communication in video stream sharing scenario. Two energy saving solutions for downlink transmission are proposed with constraint on D2D cluster’s energy consumption. We take peak signal-to-noise ratio (PSNR) as the measurement for video quality and consider both the downlink transmission energy and reception energy. In particular, we propose the D2D cluster formation approach and the D2D caching performance both for the purpose of energy saving, with distributed merge-and-split algo- rithm adopted from the perspective of coalition game theory and a relaxation factor defined to give constraints on total energy consumption for each cluster. Both D2D cluster and D2D caching approaches are effective for energy saving for the BS combined with all user devices; however, D2D cluster brings an unfairness problem between the cluster head and other cluster nodes. Therefore, we compare the two approaches on energy saving performance as well as fairness measurement. Moreover, a centralized algorithm for D2D cluster is also proposed as a benchmark for the distributed D2D cluster algorithm. Simulation result shows con- siderable amount of energy saving in the proposed D2D cluster and caching assisted cellular network for video stream sharing problem.
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Wearable cameras are very useful for crowdsensing since they enhance the participation of crowds with less user interventions on manipulating cameras. However, stored videos are large and may fill up the storage space very soon, leading to dropped videos. In this paper, we propose Adaptive Transcoding Algorithm (ATA) to optimally transcode the stored videos on wearable cameras under resource constraints. In particular, we formulate an adaptive transcoding problem with empirical video transcoding and transmission models to maximize the overall perceived quality of video. The objective of our problem is to select a video representation (frame rate, resolution, and quantization parameter) that minimizes the quality degradation when transcoding the stored videos. We conduct extensive simulations using real datasets to compare the performance of our proposed ATA against other algorithms. The simulation results show that our ATA algorithm: (i) outperforms other baseline algorithms averagely 12 dB in terms of PSNR (Peak Signal-to-Noise Ratio), (ii) spends only 13% energy consumption on transcoding with efficient transcoding decisions, and (iii) achieves nearly 4 times of improvement on delay than the baseline.
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This paper provides an overview of Scalable High efficiency Video Coding (SHVC), the scalable extensions of the High Efficiency Video Coding (HEVC) standard, published in the second version of HEVC. In addition to the temporal scalability already provided by the first version of HEVC, SHVC further provides spatial, signal-to-noise ratio, bit depth, and color gamut scalability functionalities, as well as combinations of any of these. The SHVC architecture design enables SHVC implementations to be built using multiple repurposed single-layer HEVC codec cores, with the addition of interlayer reference picture processing modules. The general multilayer high-level syntax design common to all multilayer HEVC extensions, including SHVC, MV-HEVC, and 3D HEVC, is described. The interlayer reference picture processing modules, including texture and motion resampling and color mapping, are also described. Performance comparisons are provided for SHVC versus simulcast HEVC and versus the scalable video coding extension to H.264/advanced video coding.
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With mobile video increasingly becoming an important driver of mobile device usage, the battery consumption of mobile devices will be dominated by video delivery and playback. In this paper, we develop battery efficient video download techniques that vary video download rate dynamically, including stopping video download at times, depending on buffer levels of the mobile device and the channel conditions experienced, to maximize battery life while ensuring no degradation in user experience. The proposed dynamic video download rate adaptation techniques enable the base station to adapt the Multi Input Multi Output (MIMO) transceiver configurations to reduce battery load required by MIMO components on the mobile device. Experiments conducted under various channel conditions demonstrate that the proposed battery efficient video download techniques can significantly outperform other video download techniques in terms of battery lifetime while maintaining user experience. In order to further enhance battery life, we propose to utilize video bit rate adaptation, in addition to download rate adaptation and MIMO reconfiguration. The proposed battery aware bit rate adaptation techniques take into account the mobile device battery and buffer levels, and network load and channel conditions experienced, to maximize battery lifetime (hence video viewing time) while ensuring desired level of video experience (measured in terms of video quality and stalls experienced). We propose a new metric termed “Video Experience Longevity (VEL)” which quantifies the performance of the proposed bit rate adaptation techniques in terms of video viewing time and video experience. Extensive experiments conducted under variable network load and channel conditions demonstrate that the proposed battery aware bit rate adaptation techniques can significantly outperform other bit rate adaptation techniques in terms of battery lifetime and VEL metric while ensuring desired level of video- experience.
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With multimedia dominating the digital contents, Device-to-Device (D2D) communication has been proposed as a promising data offloading solution in the big data area. As the quality of experience (QoE) is a major determining factor in the success of new multimedia applications, we propose a QoEdriven cooperative content dissemination (QeCS) scheme in this work. Specifically, all users predict the QoE of the potential connections characterized by the mean opinion score (MOS), and send the results to the content provider (CP). Then CP formulates a weighted directed graph according to the network topology and MOS of each potential connection. In order to stimulate cooperation among the users, the content dissemination mechanism is designed through seeking 1-factor of the weighted directed graph with the maximum weight thus achieving maximum total user MOS. Additionally, a debt mechanism is adopted to combat the cheat attacks. Furthermore, we extend the proposed QeCS scheme by considering a constrained condition to the optimization problem for fairness improvement. Extensive simulation results demonstrate that the proposed QeCS scheme achieves both efficiency and fairness especially in large scale and density networks.
Conference Paper
We present Select&Spray, a novel publish/subscribe communication architecture that extends end mobile user reachability in order to minimize their experienced disconnection times from core infrastructure. Within our architecture, we propose a Select&Spray algorithm that exploits space syntax concepts by interacting with the prebuilt environment in order to better guide forwarding decisions. We adopt a data-driven approach utilizing real mobility traces gathered in different venues to evaluate our algorithms. Our results show that Select&Spray is more efficient in guiding messages towards the more suitable nodes in order to reach the destination. Our algorithm helps extend the reach of data dissemination to more than 20% of the interested destinations within very short delays and outperforms two state of the art infrastructure offloading algorithms, MadNet and Push&Track by 15%.
Conference Paper
Efficient web caching in mobile apps eliminates unnecessary network traffic, reduces web accessing latency, and improves smartphone battery life. However, recent research has indicated that current mobile apps suffer from poor implementations of web caching. In this work, we first conducted a comprehensive survey of over 1000 Android apps to identify how different types of mobile apps perform in web caching. Based on our analysis, we designed CacheKeeper, an OS web caching service transparent to mobile apps for smartphones. CacheKeeper can not only effectively reduce overhead caused by poor web caching of mobile apps, but also utilizes cross-app caching opportunities in smartphones. Furthermore, CacheKeeper is backward compatible, meaning that existing apps can take advantage of CacheKeeper without any modifications. We have implemented a prototype of CacheKeeper in Linux kernel. Evaluation on 10 top ranked Android apps shows that our CacheKeeper prototype can save 42% networks traffic with real user browsing behaviors and increase web accessing speed by 2x under real 3G settings. Experiments also show that our prototype incurs negligible overhead in most aspects on cache misses.
Conference Paper
We design, implement, and evaluate a middleware system, HybCAST, that leverages a hybrid cellular and ad hoc network to disseminate rich contents from a source to all mobile devices in a predetermined region. HybCAST targets information dissemination over a range of scenarios (e.g., military operations, crisis alerting, and popular sporting events) in which high reliability and low latency are critical and existing fixed infrastructures such as wired networks, 802.11 access points are heavily loaded or partially destroyed. HybCAST implements a suite of protocols that: (i) structures the hybrid network into a hierarchy of two-level ad hoc clusters for better scalability, (ii) employ both data push and pull mechanisms for high reliability and low latency dissemination of rich content, and (iii) implement a near-optimal gateway selection algorithm to minimize the transmission redundancy. To demonstrate its practicality and efficiency, we have implemented and deployed the HybCAST middleware on several Android smart phones and an in-network Linux machine that acts as a dissemination server. The system is evaluated via real experiments using a UMTS network and extensive packet-level simulations. Our experimental results from a live network show that HybCAST achieves 100% reliability with shorter latencies and lower overall energy consumption. Simulation results confirm that HybCAST outperforms other state-of-the-art systems in the literature. For example, HybCAST exhibits a 5 times reduction in the dissemination latencies as compared to other hybrid dissemination protocols, while its energy consumption is a third of a cellular-only dissemination system. Furthermore, the simulation results demonstrate that HybCAST scales well and maintains good performance under varying numbers of mobile devices, diverse content sizes, and device mobility.
Conference Paper
Despite the plethora of opportunistic forwarding solutions offered by the research community, we revisit this domain from a new perspective by exploiting the concept of space syntax to enable deployable solutions in large scale urban environments. We present a set of algorithms that build upon space syntax, which predicts natural movement patterns by interacting with pre-built static environments. We design these algorithms for three assumption categories that represent the spectrum of assumptions regarding the underlying environment and node capabilities. We adopt a data-driven approach to evaluate the performance of our algorithms when compared to other state-of-the-art solutions within each representative category that make similar assumptions. Overall, our results show the great promise space syntax based algorithms have for efficiently guiding messages towards the destination. We show 5% to 20% success rate improvement compared to selected well known state-of-the-art forwarding algorithms within each assumption category while reducing the cost in terms of message replicas by up to 10%.
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We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate the problem of optimally choosing the mobile devices that will serve as gateways from the cellular to the ad hoc network, the ad hoc routes from the gateways to individual devices, and the layers to deliver on these ad hoc routes. We develop a Mixed Integer Linear Program (MILP)-based algorithm, called POPT, to solve this optimization problem. We then develop a Linear Program (LP)-based algorithm, called MTS, for lower time complexity. While the MTS algorithm achieves close-to-optimum video quality and is more efficient than POPT in terms of time complexity, the MTS algorithm does not run in real time for hybrid networks with large numbers of nodes. We, therefore, propose a greedy algorithm, called THS, which runs in real time even for large hybrid networks. We conduct extensive packet-level simulations to compare the performance of the three proposed algorithms. We found that the THS algorithm always terminates in real time, yet achieves a similar video quality to MTS. Therefore, we recommend the THS algorithm for video dissemination over hybrid cellular and ad hoc networks.
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Disruption tolerant networks (DTNs) are characterized by low node density, unpredictable node mobility, and lack of global network information. Most of current research efforts in DTNs focus on data forwarding, but only limited work has been done on providing efficient data access to mobile users. In this paper, we propose a novel approach to support cooperative caching in DTNs, which enables the sharing and coordination of cached data among multiple nodes and reduces data access delay. Our basic idea is to intentionally cache data at a set of network central locations (NCLs), which can be easily accessed by other nodes in the network. We propose an efficient scheme that ensures appropriate NCL selection based on a probabilistic selection metric and coordinates multiple caching nodes to optimize the tradeoff between data accessibility and caching overhead. Extensive trace-driven simulations show that our approach significantly improves data access performance compared to existing schemes.
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To improve rendered video quality and serve more receivers, peer-to-peer (P2P) video-on-demand streaming systems usually deploy seed servers. These servers complement the limited upload capacity offered by peers. In this paper, we are interested in optimally managing the capacity of seed servers, especially when scalable video streams are served to peers. Scalable video streams are encoded in multiple layers to support heterogeneous receivers. We show that the problem of optimally allocating the seeding capacity to serve scalable streams to peers is NP-complete. We then propose an approximation algorithm to solve it. Using the proposed allocation algorithm, we develop an analytical model to study the performance of P2P video-on-demand streaming systems and to manage their resources. The analysis also provides an upper bound on the maximum number of peers that can be admitted to the system in flash crowd scenarios. We validate our analysis by comparing its results to those obtained from simulations. Our analytical model can be used by administrators of P2P streaming systems to estimate the performance and video quality rendered to users under various network, peer, and video characteristics.
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The fundamental challenge in opportunistic networking is when and how to forward a message. Rank-based forwarding, one of the most promising methods for addressing this challenge, ranks nodes based on their social profiles or contact history in order to identify the most suitable forwarders. While these forwarding techniques have demonstrated great performance trends, we observe that they fail to efficiently forward messages in large scale networks. In this paper, we demonstrate using real mobility traces, the weakness of existing rank-based forwarding algorithms in large scale communities. We propose strategies for partitioning large communities into sub-communities based on geographic locality or social interests. We also propose exploiting particular nodes, named MultiHomed nodes, in order to disseminate messages across these sub-communities. We introduce CAF, a Community Aware Forwarding framework, which is designed to be integrated with state-of-the-art rank-based forwarding algorithms, in order to improve their performance in large scale networks. We use real mobility traces to evaluate our proposed techniques. Our results empirically show a delivery success rate increase of up to 40%, along with 5% to 30% improved success delivery rates compared to state-of-the-art rank-based forwarding algorithms; these results are obtained while incurring a marginal increase in cost which is less than 10%. We finally propose an extension of the original framework called Community Destination Aware Framework (CDAF). Assuming that the source node can determine the destination’s community, CDAF further reduces the cost of CAF by a factor of 2 while maintaining similar success rates.
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Video streaming is one of the increasingly popular, as well as demanding, applications on smartphones today. In this paper, we consider a group of smartphone users, within proximity of each other, who are interested in watching the same video from the Internet at the same time. The common practice today is that each user downloads the video independently using her own cellular connection, which often leads to poor quality. We design, implement, and evaluate a novel system, MicroCast, that uses the resources on all smartphones of the group in a cooperative way so as to improve the streaming experience. Each phone uses simultaneously two network interfaces: the cellular to connect to the video server and the WiFi to connect to the rest of the group. Key ingredients of our design include the following. First, we propose a scheduling algorithm, MicroDownload, that decides which parts of the video each phone should download from the server, based on the phones' download rate. Second, we propose a novel all-to-all local dissemination scheme, MicroNC-P2, for sharing content among group members, which outperforms state-of-the-art peer-to-peer schemes in our setting. MicroNC-P2 is designed to exploit WiFi overhearing and network coding, based on a local packet broadcast framework, MicroBroadcast, which we developed specifically for Android phones. We evaluate MicroCast on a testbed consisting of seven Android phones, and we show that it brings significant performance benefits without battery penalty.
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Communication in mobile opportunistic networks is primarily achieved through a variety of store-carry-and-forward techniques, where node mobility is exploited for end-to-end data delivery. The main routing challenges these networks face is determining when to forward a message and which nodes to forward it to, ultimately resulting in varying delay and cost trade-offs. Routing solutions to date heavily rely on assumptions regarding the underlying environment and node capabilities, which may be unrealistic in many cases. In this paper, we propose building upon Space Syntax in order to make forwarding decisions with more realistic assumptions about the underlying environment. Space Syntax metrics have long been used in the field of architecture to model natural mobility patterns by analyzing spacial configurations. To adapt Space Syntax to opportunistic routing, we propose our popularity index metric, which is based on core Space Syntax metrics. This popularity index depends on factors in the environment that do not frequently change, and therefore, can be more realistically adopted and deployed when compared to other opportunistic routing algorithms. We introduce two simple forwarding algorithms based on the popularity index and compare their performance to other approaches. Our initial evaluation shows that Space Syntax based routing performs relatively well compared to state-of-the-art solutions with the added advantage of being more realistic and as a result easier to deploy.
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Practical video streaming systems all use some form of progressive downloading to let users download the video at a faster rate than the playback rate. Since users may quit before viewing the complete video, however, much of the downloaded video may be "wasted". To the extent that users' departure behavior can be predicted, smart progressive downloading can be used to significantly improve performance for fixed server bandwidth. Through measurement, we extract certain user behavior properties for implementing such smart progressive downloading, and demonstrate its advantage using prototype implementation as well as simulations.
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We propose a new behavior-oriented communication paradigm in mobile networks, profile-cast, motivated by tight user-network coupling in mobile societies. In this novel paradigm, messages are sent to sender-specified target profiles, instead of machine IDs. We present a systematic framework for such services. First, we analyze the spatio-temporal stability of user mobility profiles constructed from empirical data sets, and they turn out to be surprisingly stable. The similarity of the current mobility profile of a user to its future mobility profile remains above 0.6 for five weeks, while the correlation coefficient of the similarity metrics between a user pair at different time instants is above 0.5 for two weeks. Second, we present a protocol for the profile-cast service, named CSI, and provide a fully distributed solution utilizing behavioral profile space gradients and small world structures to selectively diffuse information across the network towards the intended recipients. Leveraging stability in user behaviors, the two modes of CSI achieve good performance compared to the theoretical optimal protocols. Both CSI:Target mode and CSI:Dissemination mode achieve more than 94% delivery ratio. Comparing with the delay-optimal protocol, they show no more than 47% and 32% more delay, respectively, with at most 10% more transmission overhead. Comparing with the overhead-optimal protocol, they use no more than 7% more overhead while achieving dramatic improvement in delay (up to 150% less). Both CSI:T and CSI:D significantly outperform the epidemic routing, using less than 7% overhead, and variants of random walk, where CSI:T doubles the delivery ratio using less overhead, and CSI:D shows at least 50% less delay under similar overhead. We believe the profile-cast paradigm would enable many behavior-oriented services efficiently, such as targeted announcements and profile-based alert notifications, in various mobile networks.
Conference Paper
Mobile wireless networks frequently possess, at the same time, both dense and sparse regions of connectivity; for example, due to a heterogeneous node distribution or radio propagation environment. This paper is about modeling both the mobility and the formation of clusters in such networks, where nodes are concentrated in clusters of dense connectivity, interspersed with sparse connectivity. Uniformly dense and sparse networks have been extensively studied in the past, but not much attention has been devoted to clustered networks. We present a new mobility model for clustered networks, which is important for the design and evaluation of routing protocols. We refer to our model as Heterogeneous Random Walk (HRW). This model is simple, mathematically tractable, and it captures the phenomenon of emerging clusters, observed in real partitioned networks. We provide a closed-form expression for the stationary distribution of node position and we give a method for "perfect simulation". Moreover, we provide evidence, based on mobility traces, for the main macroscopic characteristics of clustered networks captured by the proposed mobility model. In particular, we show that in some scenarios, nodes have statistically very similar mobility patterns. Also, we discuss cluster dynamics and the relationship between node speed and node density.
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Disruption-tolerant networks (DTNs) differ from other types of networks in that capacity is created by the movements of network participants. This implies that understanding and influencing the participants’ motions can have a significant impact on network performance. In this paper, we introduce the routing protocol MORA, which learns structure in the movement patterns of network participants and uses it to enable informed message passing. We also propose the introduction of autonomous agents as additional participants in DTNs. These agents adapt their movements in response to variations in network capacity and demand. We use multi-objective control methods from robotics to generate motions capable of optimizing multiple network performance metrics simultaneously. We present experimental evidence that these strategies, individually and in conjunction, result in significant performance improvements in DTNs.
Conference Paper
Even though human movement and mobility patterns have a high degree of freedom and variation, they also exhibit structural patterns due to geographic and social constraints. Using cell phone location data, as well as data from two online location-based social networks, we aim to understand what basic laws govern human motion and dynamics. We find that humans experience a combination of periodic movement that is geographically limited and seemingly random jumps correlated with their social networks. Short-ranged travel is periodic both spatially and temporally and not effected by the social network structure, while long-distance travel is more influenced by social network ties. We show that social relationships can explain about 10% to 30% of all human movement, while periodic behavior explains 50% to 70%. Based on our findings, we develop a model of human mobility that combines periodic short range movements with travel due to the social network structure. We show that our model reliably predicts the locations and dynamics of future human movement and gives an order of magnitude better performance than present models of human mobility.
Conference Paper
We consider a mobile ad hoc network setting where Blue- tooth enabled mobile devices communicate directly with other devices as they meet opportunistically. We design and im- plement a novel mobile social networking middleware named MobiClique. MobiClique forms and exploits ad hoc social networks to disseminate content using a store-carry-forward technique. Our approach distinguishes itself from other mo- bile social software by removing the need for a central server to conduct exchanges, by leveraging existing social networks to bootstrap the system, and by taking advantage of the so- cial network overlay to disseminate content. We also propose an open API to encourage third-party application develop- ment. We discuss the system architecture and three exam- ple applications. We show experimentally that MobiClique successfully builds and maintains an ad hoc social network leveraging contact opportunities between friends and people sharing interest(s) for content exchanges. Our experience also provides insight into some of the key challenges and short-comings that researchers face when designing and de- ploying similar systems.