Showing papers on "Upload published in 2014"

deepTools: a flexible platform for exploring deep-sequencing data

Abstract: We present a Galaxy based web server for processing and visualizing deeply sequenced data. The web server’s core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straightforward, yet highly customizable manner. In addition, we offer several tools for the analysis of files containing aligned reads and enable efficient and reproducible generation of normalized coverage files. As a modular and open-source platform, deepTools can easily be expanded and customized to future demands and developments. The deepTools webserver is freely available at http://deeptools.ie-freiburg.mpg. de and is accompanied by extensive documentation and tutorials aimed at conveying the principles of deep-sequencing data analysis. The web server can be used without registration. deepTools can be installed locally either stand-alone or as part of Galaxy.

Fog Computing and Smart Gateway Based Communication for Cloud of Things

Abstract: With the increasing applications in the domains of ubiquitous and context-aware computing, Internet of Things (IoT) are gaining importance. In IoTs, literally anything can be part of it, whether it is sensor nodes or dumb objects, so very diverse types of services can be produced. In this regard, resource management, service creation, service management, service discovery, data storage, and power management would require much better infrastructure and sophisticated mechanism. The amount of data IoTs are going to generate would not be possible for standalone power-constrained IoTs to handle. Cloud computing comes into play here. Integration of IoTs with cloud computing, termed as Cloud of Things (CoT) can help achieve the goals of envisioned IoT and future Internet. This IoT-Cloud computing integration is not straight-forward. It involves many challenges. One of those challenges is data trimming. Because unnecessary communication not only burdens the core network, but also the data center in the cloud. For this purpose, data can be preprocessed and trimmed before sending to the cloud. This can be done through a Smart Gateway, accompanied with a Smart Network or Fog Computing. In this paper, we have discussed this concept in detail and present the architecture of Smart Gateway with Fog Computing. We have tested this concept on the basis of Upload Delay, Synchronization Delay, Jitter, Bulk-data Upload Delay, and Bulk-data Synchronization Delay.

STITCH 4: integration of protein–chemical interactions with user data

Abstract: STITCH is a database of protein-chemical interactions that integrates many sources of experimental and manually curated evidence with text-mining information and interaction predictions. Available at http://stitch.embl.de, the resulting interaction network includes 390 000 chemicals and 3.6 million proteins from 1133 organisms. Compared with the previous version, the number of high-confidence protein-chemical interactions in human has increased by 45%, to 367 000. In this version, we added features for users to upload their own data to STITCH in the form of internal identifiers, chemical structures or quantitative data. For example, a user can now upload a spreadsheet with screening hits to easily check which interactions are already known. To increase the coverage of STITCH, we expanded the text mining to include full-text articles and added a prediction method based on chemical structures. We further changed our scheme for transferring interactions between species to rely on orthology rather than protein similarity. This improves the performance within protein families, where scores are now transferred only to orthologous proteins, but not to paralogous proteins. STITCH can be accessed with a web-interface, an API and downloadable files.

NetworkAnalyst - integrative approaches for protein–protein interaction network analysis and visual exploration

Abstract: Biological network analysis is a powerful approach to gain systems-level understanding of patterns of gene expression in different cell types, disease states and other biological/experimental conditions. Three consecutive steps are required - identification of genes or proteins of interest, network construction and network analysis and visualization. To date, researchers have to learn to use a combination of several tools to accomplish this task. In addition, interactive visualization of large networks has been primarily restricted to locally installed programs. To address these challenges, we have developed NetworkAnalyst, taking advantage of state-of-the-art web technologies, to enable high performance network analysis with rich user experience. NetworkAnalyst integrates all three steps and presents the results via a powerful online network visualization framework. Users can upload gene or protein lists, single or multiple gene expression datasets to perform comprehensive gene annotation and differential expression analysis. Significant genes are mapped to our manually curated protein-protein interaction database to construct relevant networks. The results are presented through standard web browsers for network analysis and interactive exploration. NetworkAnalyst supports common functions for network topology and module analyses. Users can easily search, zoom and highlight nodes or modules, as well as perform functional enrichment analysis on these selections. The networks can be customized with different layouts, colors or node sizes, and exported as PNG, PDF or GraphML files. Comprehensive FAQs, tutorials and context-based tips and instructions are provided. NetworkAnalyst currently supports protein-protein interaction network analysis for human and mouse and is freely available at http://www.networkanalyst.ca.

Dynamic Searchable Encryption via Blind Storage

Abstract: Dynamic Searchable Symmetric Encryption allows a client to store a dynamic collection of encrypted documents with a server, and later quickly carry out keyword searches on these encrypted documents, while revealing minimal information to the server. In this paper we present a new dynamic SSE scheme that is simpler and more efficient than existing schemes while revealing less information to the server than prior schemes, achieving fully adaptive security against honest-but-curious servers. We implemented a prototype of our scheme and demonstrated its efficiency on datasets from prior work. Apart from its concrete efficiency, our scheme is also simpler: in particular, it does not require the server to support any operation other than upload and download of data. Thus the server in our scheme can be based solely on a cloud storage service, rather than a cloud computation service as well, as in prior work. In building our dynamic SSE scheme, we introduce a new primitive called Blind Storage, which allows a client to store a set of files on a remote server in such a way that the server does not learn how many files are stored, or the lengths of the individual files, as each file is retrieved, the server learns about its existence (and can notice the same file being downloaded subsequently), but the file's name and contents are not revealed. This is a primitive with several applications other than SSE, and is of independent interest.

Dynamic Searchable Encryption via Blind Storage.

Abstract: Dynamic Searchable Symmetric Encryption allows a client to store a dynamic collection of encrypted documents with a server, and later quickly carry out keyword searches on these encrypted documents, while revealing minimal information to the server. In this paper we present a new dynamic SSE scheme that is simpler and more efficient than existing schemes while revealing less information to the server than prior schemes, achieving fully adaptive security against honest-but-curious servers. We implemented a prototype of our scheme and demonstrated its efficiency on datasets from prior work. Apart from its concrete efficiency, our scheme is also simpler: in particular, it does not require the server to support any operation other than upload and download of data. Thus the server in our scheme can be based solely on a cloud storage service, rather than a cloud computation service as well, as in prior work. In building our dynamic SSE scheme, we introduce a new primitive called Blind Storage, which allows a client to store a set of files on a remote server in such a way that the server does not learn how many files are stored, or the lengths of the individual files; as each file is retrieved, the server learns about its existence (and can notice the same file being downloaded subsequently), but the file’s name and contents are not revealed. This is a primitive with several applications other than SSE, and is of independent interest.

Systems and methods for supporting downloadable applications on a portable client device

Abstract: Systems and methods for downloading customized applications from a server are described. In some embodiments, a server receives a request from a client device to download an application. The server identifies a type of the client device and a user characteristic. In response to the request, the server obtains a customized environment file associated with the user characteristic for the application, where the customized environment file defines an interface appearance of the application. The server sends to the client device, the customized environment file and the application appropriate for the type of the client device, such that the customized environment file gives the application running on the client device an appearance associated with the user characteristics. Other embodiments are also described.

VAMPS: a website for visualization and analysis of microbial population structures

Abstract: The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 105–108 reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu ) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators’ private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.

Identity-based remote data possession checking in public clouds

Abstract: Checking remote data possession is of crucial importance in public cloud storage It enables the users to check whether their outsourced data have been kept intact without downloading the original data The existing remote data possession checking (RDPC) protocols have been designed in the PKI (public key infrastructure) setting The cloud server has to validate the users' certificates before storing the data uploaded by the users in order to prevent spam This incurs considerable costs since numerous users may frequently upload data to the cloud server This study addresses this problem with a new model of identity-based RDPC (ID-RDPC) protocols The authors present the first ID-RDPC protocol proven to be secure assuming the hardness of the standard computational Diffie-Hellman problem In addition to the structural advantage of elimination of certificate management and verification, the authors ID-RDPC protocol also outperforms the existing RDPC protocols in the PKI setting in terms of computation and communication

Private Information Retrieval for Coded Storage

Abstract: Private information retrieval scheme for coded data storage is considered in this paper. We focus on the case where the size of each data record is large and hence only the download cost (but not the upload cost for transmitting retrieval queries) is of interest. We prove that the tradeoff between storage cost and retrieval/download cost depends on the number of data records in the system. We also propose a fairly general class of linear storage codes and retrieval schemes and derive conditions under which our retrieval schemes are error-free and private. Tradeoffs between the storage cost and retrieval costs are also obtained. Finally, we consider special cases when the underlying storage code is based on an MDS code. Using our proposed method, we show that a randomly generated retrieval scheme is indeed very likely to be private and error-free.

Video and motion event integration system

Abstract: Enables intelligent synchronization and transfer of generally concise event videos synchronized with motion data from motion capture sensor(s) coupled with a user or piece of equipment Greatly saves storage and increases upload speed by uploading event videos and avoiding upload of non-pertinent portions of large videos Provides intelligent selection of multiple videos from multiple cameras covering an event at a given time, for example selecting one with least shake Enables near real-time alteration of camera parameters during an event determined by the motion capture sensor, and alteration of playback parameters and special effects for synchronized event videos Creates highlight reels filtered by metrics and can sort by metric Integrates with multiple sensors to save event data even if other sensors do not detect the event Also enables analysis or comparison of movement associated with the same user, other user, historical user or group of users

InterMine: extensive web services for modern biology.

Abstract: InterMine (www.intermine.org) is a biological data warehousing system providing extensive automatically generated and configurable RESTful web services that underpin the web interface and can be re-used in many other applications: to find and filter data; export it in a flexible and structured way; to upload, use, manipulate and analyze lists; to provide services for flexible retrieval of sequence segments, and for other statistical and analysis tools. Here we describe these features and discuss how they can be used separately or in combinations to support integrative and comparative analysis.

Methods and systems for background uploading of media files for improved user experience in production of media-based products

Abstract: Methods and systems for background uploading of media files are presented. Background uploading improves efficiency and user-experience in creating media-based projects online. In one embodiment, a user selects original media files at a user-device for an upload. The user-device at first resizes the original files to resized files and uploads them to a server along with meta-data, and at second the original files start uploading in the background computer process. The user is provided the resized images to create a project. The server converts each resized media file into compressed media files, and provides the compressed files to the user to continue or finish building the project, during which the user-device renders to the user an illusionary impression of a completed upload of the original files when the original files are still uploading. Finally, the user-device completes the upload of the original files to the server.

Demonstration of the Myria big data management service

Abstract: In this demonstration, we will showcase Myria, our novel cloud service for big data management and analytics designed to improve productivity. Myria's goal is for users to simply upload their data and for the system to help them be self-sufficient data science experts on their data -- self-serve analytics. Using a web browser, Myria users can upload data, author efficient queries to process and explore the data, and debug correctness and performance issues. Myria queries are executed on a scalable, parallel cluster that uses both state-of-the-art and novel methods for distributed query processing. Our interactive demonstration will guide visitors through an exploration of several key Myria features by interfacing with the live system to analyze big datasets over the web.

Incremental proxy re-encryption scheme for mobile cloud computing environment

Abstract: Due to the limited computational capability of mobile devices, the research organization and academia are working on computationally secure schemes that have capability for offloading the computational intensive data access operations on the cloud/trusted entity for execution. Most of the existing security schemes, such as proxy re-encryption, manager-based re-encryption, and cloud-based re-encryption, are based on El-Gamal cryptosystem for offloading the computational intensive data access operation on the cloud/trusted entity. However, the resource hungry pairing-based cryptographic operations, such as encryption and decryption, are executed using the limited computational power of mobile device. Similarly, if the data owner wants to modify the encrypted file uploaded on the cloud storage, after modification the data owner must encrypt and upload the entire file on the cloud storage without considering the altered portion(s) of the file. In this paper, we have proposed an incremental version of proxy re-encryption scheme for improving the file modification operation and compared with the original version of the proxy re-encryption scheme on the basis of turnaround time, energy consumption, CPU utilization, and memory consumption while executing the security operations on mobile device. The incremental version of proxy re-encryption scheme shows significant improvement in results while performing file modification operations using limited processing capability of mobile devices.

Indicating unavailability of an uploaded video file that is being bitrate encoded

Abstract: A system for indicating the unavailability of an already uploaded video file is provided. The system includes an advertiser system providing a graphical user interface for uploading a video file to a database and an ad serving system communicatively coupled to the database that receives the uploaded video file. A creative asset processing system is communicatively coupled to the ad serving system and advertiser system and receives the uploaded video file to process the uploaded video file by performing bit rate encoding on the uploaded video file. The bit rate encoding generates a plurality of encoded video files of the uploaded video file having respective bitrates. The advertiser system displays a set of menu options on the graphical user interface for each of the encoded video files.

Video internet video monitoring method and system, protocol conversion server, and video internet server

Abstract: The embodiment of the invention provides a video internet video monitoring method and system, a protocol conversion server and a video internet server, and aims to solve the problem that shortage of staff in a monitoring center results in negligence in viewing monitoring video signals and causes potential safety hazards. The method includes: the protocol conversion server after powering on and initialization is connected with the video network server; a data request including authentication information is sent to a monitoring front-end, and a monitoring video data packet sent by the monitoring front-end is received; the monitoring video data packet is converted into a video network video data packet including path information; and according to the path information, the video network video data packet is through the video network uploaded to the video network server, wherein the video network server is used to send the video network video data packet to a corresponding channel of a digital TV set top box. According to the invention, the staff not belonging to the monitoring center are enabled to watch the monitoring video through the digital television, so that the problem that the shortage of staff in the monitoring center results in negligence in viewing monitoring video signals and causes potential safety hazards is avoided.

System and method for providing cloud printing service

Abstract: Provided is an image forming system operable to provide a cloud printing service, the image forming system comprising: a transmitting device operable to transmit content by designating a target phone number; a cloud printing server operable to receive the target phone number and the content from the transmitting device; a receiving device assigned with the target phone number and operable to receive an upload notification of the content with respect to the target phone number from the cloud printing server; and an image forming device operable to print the content by receiving the content from the cloud printing server, wherein the cloud printing server transmits the content to the image forming device registered in the target phone number when the cloud printing service is requested for the content to the target phone number.

Exploration of geo-tagged photos through data mining approaches

Abstract: With the development of web technique and social network sites human now can produce information, share with others online easily. Photo-sharing website, Flickr, stores huge number of photos where people upload and share their pictures. This research proposes a framework that is used to extract associative points-of-interest patterns from geo-tagged photos in Queensland, Australia, a popular tourist destination hosting the great Barrier Reef and tropical rain forest. This framework combines two popular data mining techniques: clustering for points-of-interest detection, and association rules mining for associative points-of-interest patterns. We report interesting experimental results and discuss findings.

Security protection between users and the mobile media cloud

Abstract: Mobile devices such as smartphones are widely deployed in the world, and many people use them to download/upload media such as video and pictures to remote servers. On the other hand, a mobile device has limited resources, and some media processing tasks must be migrated to the media cloud for further processing. However, a significant question is, can mobile users trust the media services provided by the media cloud service providers? Many traditional security approaches are proposed to secure the data exchange between mobile users and the media cloud. However, first, because multimedia such as video is large-sized data, and mobile devices have limited capability to process media data, it is important to design a lightweight security method; second, uploading and downloading multi-resolution images/videos make it difficult for the traditional security methods to ensure security for users of the media cloud. Third, the error-prone wireless environment can cause failure of security protection such as authentication. To address the above challenges, in this article, we propose to use both secure sharing and watermarking schemes to protect user's data in the media cloud. The secure sharing scheme allows users to upload multiple data pieces to different clouds, making it impossible to derive the whole information from any one cloud. In addition, the proposed scalable watermarking algorithm can be used for authentications between personal mobile users and the media cloud. Furthermore, we introduce a new solution to resist multimedia transmission errors through a joint design of watermarking and Reed- Solomon codes. Our studies show that the proposed approach not only achieves good security performance, but also can enhance media quality and reduce transmission overhead.

Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure

Abstract: Circadian biology is a major area of research in many species. One of the key objectives of data analysis in this field is to quantify the rhythmic properties of the experimental data. Standalone software such as our earlier Biological Rhythm Analysis Software Suite (BRASS) is widely used. Different parts of the community have settled on different software packages, sometimes for historical reasons. Recent advances in experimental techniques and available computing power have led to an almost exponential growth in the size of the experimental data sets being generated. This, together with the trend towards multinational, multidisciplinary projects and public data dissemination, has led to a requirement to be able to store and share these large data sets. BioDare (Biological Data repository) is an online system which encompasses data storage, data sharing, and processing and analysis. This chapter outlines the description of an experiment for BioDare, how to upload and share the experiment and associated data, and how to process and analyze the data. Functions of BRASS that are not supported in BioDare are also briefly summarized.

4D Reconstruction of Tangible Cultural Heritage Objects from Web-Retrieved Images

Abstract: The number of digital images that are available online today has reached unprecedented levels. Recent statistics showed that by the end of 2013 there were over 250 billion photographs stored in just one of the major social media sites, with a daily average upload of 300 million photos. These photos, apart from documenting personal lives, often relate to experiences in well-known places of cultural interest, throughout several periods of time. Thus from the viewpoint of Cultural Heritage professionals, they constitute valuable and freely available digital cultural content. Advances in the fields of Photogrammetry and Computer Vision have led to significant breakthroughs such as the Structure from Motion algorithm which creates 3D models of objects using their 2D photographs. The existence of powerful and affordable computational machinery enables the reconstruction not only of single structures such as artefacts, but also of entire cities. This paper presents an overview of our methodology for producing co...

Dynamic uploading protocol

Abstract: A dynamic uploading protocol comprises an input interface configured to receive a manifest comprising a plurality of events which may be uploaded; wherein the manifest additionally comprises sensor information relating to each of the plurality of events. The system for a dynamic uploading protocol additionally comprises a processor configured to determine whether to upload additional information about each event, wherein determining whether to upload additional information about each event is based at least in part on the sensor information and contextual information. The system for a dynamic uploading protocol additionally comprises an output interface configured to request the additional information. The system for a dynamic uploading protocol additionally comprises a memory coupled to the processor and configured to provide the processor with instructions.

GTube: geo-predictive video streaming over HTTP in mobile environments

Abstract: Mobile video streaming sometimes suffers from playback interruptions which are typically due to considerable network bandwidth variations that a user may experience when s/he travels along a route. Segmented adaptive HTTP streaming that switches between video streams encoded at different bitrates -- and hence different quality levels -- can be used to alleviate the issues of variable bandwidth. An important issue with respect to users' perceived experience is how the system schedules the quality levels to match the end-to-end network bandwidth capacity. It is very beneficial if the application can estimate the future network conditions in advance, and therefore perform quality control and buffer control wisely.This work describes GTube, a video streaming system for receivers equipped with a GPS positioning sensor in mobile environments. The available network bandwidth for each location is collected by mobile users and then this data along with the measured locations are uploaded and recorded in a server. Mobile devices that stream video can send queries to the server in order to better predict the near-future bandwidth availability and plan quality adaptations accordingly.

Secure semantic expansion based search over encrypted cloud data supporting similarity ranking

Abstract: With the advent of cloud computing, more and more information data are outsourced to the public cloud for economic savings and ease of access. However, the privacy information has to be encrypted to guarantee the security. To implement efficient data utilization, search over encrypted cloud data has been a great challenge. The existing solutions depended entirely on the submitted query keyword and didn't consider the semantics of keyword. Thus the search schemes are not intelligent and also omit some semantically related documents. In view of the deficiency, as an attempt, we propose a semantic expansion based similar search solution over encrypted cloud data. Our solution could return not only the exactly matched files, but also the files including the terms semantically related to the query keyword. In the proposed scheme, a corresponding file metadata is constructed for each file. Then both the encrypted metadata set and file collection are uploaded to the cloud server. With the metadata set, the cloud server builds the inverted index and constructs semantic relationship library (SRL) for the keywords set. After receiving a query request, the cloud server first finds out the keywords that are semantically related to the query keyword according to SRL. Then both the query keyword and the extensional words are used to retrieve the files. The result files are returned in order according to the total relevance score. Eventually, detailed security analysis shows that our solution is privacy-preserving and secure under the previous searchable symmetric encryption (SSE) security definition. Experimental evaluation demonstrates the efficiency and effectives of the scheme.

On the Dynamics of Social Media Popularity: A YouTube Case Study

Abstract: Understanding the factors that impact the popularity dynamics of social media can drive the design of effective information services, besides providing valuable insights to content generators and online advertisers. Taking YouTube as case study, we analyze how video popularity evolves since upload, extracting popularity trends that characterize groups of videos. We also analyze the referrers that lead users to videos, correlating them, features of the video and early popularity measures with the popularity trend and total observed popularity the video will experience. Our findings provide fundamental knowledge about popularity dynamics and its implications for services such as advertising and search.

A tunable proof of ownership scheme for deduplication using Bloom filters

Abstract: Deduplication is a widely used technique in storage services, since it affords a very efficient usage of resources—being especially effective for consumer-grade storage services (e.g. Dropbox). Deduplication has been shown to suffer from several security weaknesses, the most severe ones enabling a malicious user to obtain possession of a file it is not entitled to. Standard solutions to this problem require users to prove possession of data prior to its upload. Unfortunately, the schemes proposed in the literature are very taxing on either the server or the client side. In this paper, we introduce a novel solution based on Bloom filters that provides a flexible, scalable, and provably secure solution to the weaknesses of deduplication, and that overcomes the deficiencies of existing approaches. We provide a formal description of the scheme, a thorough security analysis, and compare our solution against multiple existing ones, both analytically and by means of extensive benchmarking. Our results confirm the quality and viability of our approach.

Privacy-Preserving High-Quality Map Generation with Participatory Sensing

Abstract: Accurate maps are increasingly important with the growth of smart phones and the development of location-based services. Several crowdsourcing based map generation protocols have been proposed that rely on volunteers to provide their traces. Being creative, however, those methods pose a significant threat to user privacy as the traces can easily imply user behavior patterns. On the flip side, crowdsourcing-based map generation method does need individual locations. To address the issue, we present a systematic participatory-sensing-based high-quality map generation scheme, PMG, that meets the privacy demand of individual users. In this approach, individual users merely need to upload unorganized sparse location points so as to reduce the risk of exposing privacy, while the server generates accurate maps with unorganized points, instead of user traces. Experiments show that our solution is able to generate high-quality maps for a real environment that is robust to noisy data. The difference between the ground-truth map and the produced map is < 10m ,e ven when the collected locations are about 32m apart after clustering for the purpose of removing noise.

Compact video signatures for near-duplicate detection on mobile devices

Abstract: In this paper, we focus on generating compact but efficient video signatures on mobile devices so that users quickly know whether there are near-duplicates in the social network systems when they upload a video. For this, the proposed method employs the idea of inverted index that is one of the most popular text retrieval methods. Experimental results show that our method can achieve similar results compared with state-of-the-art method whereas it requires low memory and computation cost.

INDAPSON: An incentive data plan sharing system based on self-organizing network

Abstract: The contradiction between dynamic user traffic and fixed data plans has drawn increasing attention in the field of mobile applications. In this paper we build a data plan sharing system named INDAPSON to consider a scenario where some smartphone users have surplus data traffic and are willing to help others download data. Virtual credits can be gained as reward, which can be used to ask for future help in downloading. To realize this model, we make the following contributions: 1) A dynamic self-organization strategy to adapt to mobile terminals; 2) An incentive mechanism named RAP to encourage participation; 3) Power-saving strategies to reduce power consumption. The main advantage of our system is that users gain improvement in download rate while being able to convert their surplus data traffic to virtual credits. The results of experiment and simulation show that users in our system can manage their surplus data plan more efficiently while a high- speed download rate can be achieved. I. INTRODUCTION With the rapid development of mobile computing, today's mobile terminals, such as smart phones and tablets, are be- coming more and more powerful and can offer people with highly convenient Internet access. Using mobile terminals to get Internet services is becoming increasingly important in people's daily life. People can browse webs or download data anytime and anywhere through their cellular connections. Indeed, cellular data traffic is growing rapidly these years. However, we have to notice that there exist many drawbacks of today's mobile data service, and we are interested in the following two common problems: Firstly, we notice a problem that many ISPs don't provide unlimited data plans, and overuse is of high cost. For users who prefer tiered data plans with a limited amount of data, their network usage is always dynamic while their data plan is fixed. Sometimes their data plans are overused but underused at other times. Thus users have to pay attention on their data usage. Secondly, with the increasing demand of data download through cellular connections, downstream rate offered by current cellular networks is insufficient to meet users' de- mand. Furthermore, the data rate of cellular network fluctuates severely over time. As a result, people often fail to get high quality of Internet service. Thus, it is of great significance to figure out an effective mechanism to make use of idle wireless interfaces and improve cellular bandwidth without unacceptable expense to update the infrastructures of ISPs. In this paper, we propose a novel INcentive DAta Plan Shar- ing system based on Self-Organizing Network (INDAPSON) to tackle the two problems mentioned above. Our proposal is based on two observations: 1) some users still have under-used data plan while some other users overuse their data plan. 2) people often stay together in daily life - for instance family members in houses, co-workers in meeting rooms, passengers on buses etc. These observations provide opportunities for our solution. The two goals that our system aims to achieve are 1) meeting users' dynamic traffic requirements and 2) increasing the download data rate. In order to discriminate different participators, we classify users into three types in our system: • Primary user: user who needs to download data from the Internet. • Assistant user: user who helps a download user download data from the Internet. • Detected user: user who acts as a candidate for assistant user. Our system fits a scenario where assistant or detected users have idle cellular links or are willing to deal with their surplus data traffic, and it works as follows: one primary user initiates the construction of a local wireless network, the members of which are called detected users. Several assistant users are cho- sen from the detected users to help the primary user download data from the Internet through their cellular connections, and then relay data segments arrived to the primary user through WiFi connections. Since the low downstream rate of cellular networks is the bottleneck of system performance, we run multiple threads on primary user to receive data from different sources (server and peers) simultaneously, avoiding block on single cellular connection. After a cooperation, records for the whole download process are uploaded to a management server on the Internet. With a pricing scheme called Reputation Adaptive Pricing (RAP) applied, a primary user can pay a certain amount of virtual credits to assistant users, which can be used to purchase the help from other users next time. One important feature of INDAPSON is that users do not necessarily know the existence of each other or are interested in the same data. They simply keep our application running in the background of their smartphones all the time without other manipulations. Some of previous works have discussed on the cooperative download within a small user group, where