Following fast growth of cellular networks, more users have drawn attention to the contradiction between dynamic user data traffic and static data plans. To address this important but largely unexplored issue, in this paper, we design a new data plan sharing system named Prometheus, which is based on the scenario that some smartphone users have surplus data traffic and are willing to help others download data. To realize this system, we first propose a mechanism that incorporates LT codes into UDP. It is robust to transmission errors and encourages more concurrent transmissions and forwardings. It also can be implemented easily with low implementation complexity. Then we design an incentive mechanism using a Stackelberg game to choose assistant users ( @math ), all participants will gain credits in return, which can be used to ask for future help when they need to download something. Finally real environment experiments are conducted and the results show that users in our Prometheus not only can manage their surplus data plan more efficiently, but also achieve a higher speed download rate.
Many researchers in this field have turned their research on streaming application. Instead of sending the stream independently to each mobile device, the server distributes the video packets among the devices, over a long-range wireless link using WLAN technology; the devices then exchange the received packets each other over short-range wireless links @cite_8 @cite_9 .
@cite_9 @cite_8
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A promising approach for power reduction in mobile devices is peer-to-peer cooperation. In this paper, we present a testbed system implementation to evaluate the performance of an infrastructure controlled cooperative video streaming architecture. A number of mobile devices in close proximity are connected to the Internet through a wireless access point and are all requesting the same video stream from a dedicated server. Instead of sending the stream independently to each device, the server distributes the video packets among the devices, over a long-range wireless link using WLAN technology; the devices then exchange the received packets among each other over short-range wireless links using Bluetooth technology. The implemented testbed is used to experimentally demonstrate the power reduction gains in mobile devices and to derive an analytical model that relates power consumption to various design and system parameters. Today’s Internet has witnessed an increase in the popularity of mobile video streaming, which is expected to exceed 3 4 of the global mobile data traffic by 2019. To satisfy the considerable amount of mobile video requests, video service providers have been pushing their content delivery infrastructure to edge networks—from regional content delivery network (CDN) servers to peer CDN servers (e.g., smartrouters in users’ homes)—to cache content and serve users with storage and network resources nearby. Among the edge network content caching paradigms, Wi-Fi access point caching and cellular base station caching have become two mainstream solutions. Thus, understanding the effectiveness and performance of these solutions for large-scale mobile video delivery is important. However, the characteristics and request patterns of mobile video streaming are unclear in practical wireless network. In this paper, we use real-world data sets containing 50 million trace items of nearly 2 million users viewing more than 0.3 million unique videos using mobile devices in a metropolis in China over two weeks, not only to understand the request patterns and user behaviors in mobile video streaming, but also to evaluate the effectiveness of Wi-Fi and cellular-based edge content caching solutions. To understand the performance of edge content caching for mobile video streaming, we first present temporal and spatial video request patterns, and we analyze their impacts on caching performance using frequency-domain and entropy analysis approaches. We then study the behaviors of mobile video users, including their mobility and geographical migration behaviors, which determine the request patterns. Using trace-driven experiments, we compare strategies for edge content caching, including least recently used (LRU) and least frequently used (LFU), in terms of supporting mobile video requests. We reveal that content, location, and mobility factors all affect edge content caching performance. Moreover, we design an efficient caching strategy based on the measurement insights and experimentally evaluate its performance. The results show that our design significantly improves the cache hit rate by up to 30 compared with LRU LFU. Today's video delivery solutions for mobile terminals often use the HTTP Live Streaming (HLS) protocol, which has two interesting features: firstly, the video is divided into playable segments of a certain length, which allows to download and buffer segments before they are required for playback. And secondly, those segments can be available in different quality levels, which can be selected according to the available transmission capacity. Combining these features with scheduling and channel capacity prediction of wireless transmissions into a cross-layer scheduling approach could improve the QoE for users by reducing playback interruptions and by providing the best possible video quality depending on the user's wireless channel capacity. In this paper we propose a mixed integer quadratically constrained program (MIQCP) to implement the aforementioned cross-layer scheduling approach. We evaluate its performance compared to greedy strategies to assess the potential for a future polynomial time implementation. Video on-demand streaming from Internet-based servers is becoming one of the most important services offered by wireless networks today. In order to improve the area spectral efficiency of video transmission in cellular systems, small cells heterogeneous architectures (e.g., femtocells, WiFi off-loading) are being proposed, such that video traffic to nomadic users can be handled by short-range links to the nearest small cell access points (referred to as “helpers”). As the helper deployment density increases, the backhaul capacity becomes the system bottleneck. In order to alleviate such bottleneck we propose a system where helpers with low-rate backhaul but high storage capacity cache popular video files. Files not available from helpers are transmitted by the cellular base station. We analyze the optimum way of assigning files to the helpers, in order to minimize the expected downloading time for files. We distinguish between the uncoded case (where only complete files are stored) and the coded case, where segments of Fountain-encoded versions of the video files are stored at helpers. We show that the uncoded optimum file assignment is NP-hard, and develop a greedy strategy that is provably within a factor 2 of the optimum. Further, for a special case we provide an efficient algorithm achieving a provably better approximation ratio of 1-(1-1 d )d, where d is the maximum number of helpers a user can be connected to. We also show that the coded optimum cache assignment problem is convex that can be further reduced to a linear program. We present numerical results comparing the proposed schemes.