Our implementation was designed to work on \textbf{GNU/Linux} distributions, so our back end dependencies, such as FFmpeg, has been chosen based on this. However we tried as much as possible to choose them such that they also run on other operating systems, such as Windows. Thus, porting P2P-Tube for them should be easy, but until this point creating a cross-platform implementation was not a priority for us.
+\begin{figure}[h]
+ \begin{center}
+ \includegraphics[width=\columnwidth]{img/living-lab-site.jpg}
+ \end{center}
+ \caption{UPB Living Lab Site -- An Implementation of P2P-Tube}
+ \label{fig:living-lab-site}
+\end{figure}
+
+We are using P2P-Tube in our university for P2P-Next Living Lab Site (see Figure \ref{fig:living-lab-site}) as a test bed for the Next-Share technology.
+
\subsection{Web Application Front End}
\label{subsec:front-end}
\subsection{Searching Video Assets}
\label{subsec:searching}
+As stated before the default user interface of the platform provides a search box in the page header along with an options list for narrowing results to a specific category.
+
+The search functionality depends on MySQL Full-Text functions \cite{mysql-fulltext}, thus the search query language is similar. Two modes of full-text searching are used from MySQL: natural language full-text search and boolean full-text search.
+
+\textit{Natural language full-text search} allows users to enter space separated keywords that are matched against table rows. Searching is performed only in table columns that are indexed for full-text search, so we are indexing \texttt{title}, \texttt{description} and \texttt{tags} columns from \texttt{videos} table. What MySQL calls natural language is in fact vector space search, which calculates the relevance of each result row against the query with some variation of \textit{tf-idf} formula \cite{tf-idf}, one of the most popular used in information retrieval. This kind of searching performs well on our video set of about 120 items. However, natural language search mode has some problems. For instance, any word shorter than four characters is not indexed, so a query like \textit{``let it be''} or \textit{``git c repo''} wouldn't retrieve anything. Also, wild cards, quotations and boolean operators like \textit{and}, \textit{or}, \textit{not} are not supported.
+
+To handle this problem P2P-Tube's search feature also uses MySQL's \textit{boolean full-text search} functions. This mode allows users to enter special characters at the beginning of the keyword from the search query. For example $+$ and $-$ operators indicate if a word is required to be present or absent, respectively, in the results. A full reference of the operators supported can be found in MySQL documentation \cite{mysql-boolean-search}. Boolean search mode is only used when at least one of this operators is present in the search query, otherwise natural search mode is used. Boolean search mode offers a little bit more flexibility to the user, but on the other hand it has a big disadvantage, results are not ordered by their relevance. Instead of assigning a relevance score for each row, this mode adds one for each match of a column and zero otherwise. We weighted columns differently to mark their importance. We mark \texttt{title} as the most important column of the \texttt{video} table with respect to searching, by weighting it with 50\% of the total weight. \texttt{tags} column gets 30\% and description gets 20\%. So if a query matches against the title, 0.5 instead of 1 is added to the relevance, if tags matches, 0.3 is added and if description matches, 0.2 is added.
+
+Like natural language mode, boolean mode also skips words with less than 4 characters, so in our implementation we also search for word fragments in the indexed columns. To support this we use the SQL keyword \texttt{LIKE} along with strings of words containing character \texttt{\%} at the beginning and at the end. If such fragments are matched they affect very little the relevance because the weights of matching columns \texttt{title}, \texttt{tags} and \texttt{description} are very small, being 25\%, 15\% and 10\%, respectively. So, a query string \textit{``let it be''} will match a Beatles' video with the same name, but will also match videos containing \textit{``letter''}, because \textit{``let''} from the query is a fragment of \textit{``letter''}.
+
+For our small video set the search feature performs well without any performance issues. For future work we are planning to use more advanced search tools such as Lucene or Solr from Apache Software Foundation.
+
\subsection{Video Widget}
\label{subsec:video-widget}
-TODO
+Next-Share browser plugins do not provide an user interface to control and monitor playing of video assets. Users need at least a play button in order to start watching. However, browsers typically offer play controls for HTML5 video tags, but their functionality is limited and depends on the browser, making video tags look browser dependent. While SwarmPlayer has some kind of user interface by using HTML5, NextSharePC is based on VLC browser plugin, which does not come with any interface.
+
+\begin{figure}[h]
+ \begin{center}
+ \includegraphics[width=\columnwidth]{img/nsvideo-widget.jpg}
+ \end{center}
+ \caption{\textit{NS Video} Widget}
+ \label{fig:nsvideo-widget}
+\end{figure}
+
+We decided to create a browser widget, based on jQueryUI that can be used with both Next-Share plugins. Besides this functionality our widget, named \textbf{NS Video} (Next-Share Video), can be used without Next-Share technology for playing ``pure'' HTML5 videos and to control ``pure'' VLC plugins. A snapshot of the widget be seen in Figure \ref{fig:nsvideo-widget}. It was designed as a separate component of P2P-Tube and it can be used in any other web application, just like any jQueryUI widget. It is a widget combined from other standard jQueryUI widgets like buttons, sliders and check boxes and it uses jQueryUI's CSS framework.
+
+HTML5 triggers events for the video tag, so for example when the video finishes playing an event is triggered. This simplified a lot the widget implementation for SwarmPlayer. This was not the case with NextSharePC, which uses VLC and does not trigger any events. To solve this problems we used JavaScript timers which check plugin's state periodically and applies the appropriate actions.
+
+The widget contains two \textit{interfacing objects} (which have the same interface), one for HTML5 (named \texttt{html5}) and one for VLC (named \texttt{vlc}). With this two objects the widget's interfacing with to the two different video technologies is simplified. If a future extension for another technology, other than HTML5 and VLC, is required, a developer only needs to implement the methods of a new interfacing object.
\subsection{Content Ingestion Back End}
\label{subsec:back-end}
-TODO
+Content Ingestion Server is written in Python, mainly because of the need of using threads. A master thread takes the role of a producer by receiving requests from clients and submitting them to a job queue. The consumer is a worker thread which gets jobs from the queue and executes them, using a first-come first-served servicing policy. If the queue is empty the worker waits without blocking until a new job is available.
-\subsection{Front End and Back End Communication}
-\label{subsec:communication}
+Client requests are received by the master through a RESTful web service. This functionality was implemented with \textbf{Web.py} \cite{webpy}, a lightweight web framework for Python. Simpler messages, like the one which requests CIS's load are implemented with HTTP GET methods, but more complex ones which require structured data format use POST methods. The posted data is encoded with JSON (JavaScript Object Notation) which allows messages to be formated as an imbrication of lists and dictionaries.
-The web server needs to communicate with Content Ingestion Server, whether or not through a CIS Load Balancer (CIS-LB), by sending a content ingestion request. By using a web service for this communication the implementation overhead is reduced. Sending HTTP requests from the PHP web server application is much more easy then creating a custom new protocol. The same applies at the other communication point, the Python server, where requests are received by Web.py framework, which makes HTTP methods processing extremely easy.
+CIS implementation depends on NextShareCore library for the functionalities of creating and seeding torrent files. As stated before this library is also written in Python, so that was another motivation for writing CIS in this programming language. NextShareCore provides an efficient implementation of seeding by using threads.
-If another framework decides to use our solution based on CIS machines, interoperability is simplified by using web service interfaces, no matter what programming language is used for web server application.
+Besides creating torrents and seeding, a content ingestion job also needs to transfer locally raw video files from the web server, to transcode them to destination formats, to extract image thumbnails and to transfer back torrent files and image thumbnails to the web server. For this purpose all this features use a pluggable interface. In \texttt{api} package, file \texttt{base.py} contains this interfaces detailed below:
-\subsection{Programming Languages, Frameworks}
-\label{subsec:langs-and-frameworks}
+\begin{itemize}
+ \item \textbf{\texttt{BaseFileTransferer}} abstracts file transfers between CIS and web server.
+ \item \textbf{\texttt{BaseTranscoder}} abstracts video asset transcoding, so raw video files can be transcoded to destination formats by using an implementation of this base class.
+ \item \textbf{\texttt{BaseThumbExtractor}} abstracts image thumbnails extraction from video assets. Multiple extraction policies can be provided. A thumbnail can be extracted from a specific position from the video given in seconds, from random a position or summary thumbnails can be extracted, where a series of thumbnails by taking several snapshots are captured.
+ \item \textbf{\texttt{BaseAVInfo}} abstracts a tool for retrieving information about a video asset. Currently this interface can be used to get the duration of a video.
+\end{itemize}
-Content Ingestion Server is written in Python, mainly because of the need of using threads. A master thread takes the role of a producer by receiving requests from clients and submitting them to a job queue. The consumer is a worker thread which gets jobs from the queue and executes them, using a first-come first-server servicing policy. If the queue is empty the worker waits without blocking until a new job is available. Client requests are received by the master with the aid of Web.py, a lightweight web framework \cite{webpy}.
+Developers can extend this interface classes with their own implementation. In CIS configuration file (\texttt{config.py}) system administrators can choose between several alternative implementations of a feature. Currently file transfers are done with FTP (File Transfer Protocol) \cite{ftp} with class \texttt{FTPFileTransferer} which extends \texttt{BaseFileTransferer}. Standard FTP Python libraries are used for this purpose. FTP uses two ports for communication between client and server, one corresponding to the control channel, the other one to the data channel. The control channel could transfer sensitive information, thus TLS (Transport Layer Security) \cite{tls} is used for encryption. Developers are encouraged to implement other alternative protocols for file transfers. For example, we are planning an rsync \cite{rsync} implementation which recovers better from failures and checks data integrity. Despite the fact that FTP is less advanced than rsync, we decided to implement it because of its popularity.
-\subsection{The Choice for the Web Service}
-\label{subsec:securing-cis}
+Our \texttt{BaseTranscoder} implementation, \texttt{FFmpegTranscoder}, uses \textit{FFmpeg} \cite{ffmpeg} a software solution for recording, converting and streaming audio and video. Transconding is possible between almost any formats, by using third-party libraries. Being written in C, CIS forks a new process when using FFmpeg, and creates a pipe for monitoring standard output and standard error. Porting P2P-Tube to Windows should be easy because FFmpeg also works on this operating system.
-Our choice between a SOAP web service and a simple RESTful web service was based on our needs. We wanted to make a server with a low communication overhead and SOAP has the disadvantage of consuming more computational resources when processing requests. Our messages that need to be passed through different services have a simple structure.
+FFmpeg can also be used for extracting thumbnails, so we used the same software for implementing \texttt{FFmpegThumbExtractor}, which extends \texttt{BaseThumbExtractor}. Information about a video asset can be obtained with \texttt{FFprobeAVInfo}, an implementation of \texttt{BaseAVInfo} base class, which uses ffprobe an utility from FFmpeg software package.
-The \textit{get load request} does not have any parameters, so a simple HTTP GET request is sufficient and any extra data transmitted as XML with SOAP is redundant.
+\textbf{CIS-LB} (CIS -- Load Balancer) usually lays on the same machine with a web server and also communicates with it via web services. Thus, we implemented CIS-LB in Python, using Web.py as CIS. Messages received from a web server are forwarded to a CIS from the pool by using a load balancing policy. Policies are implemented as pluggable interfaces exactly as features of CIS are. Three possible policies can be used:
-\textit{Content ingestion request} is a message with a greater complexity. The name of the uploaded file located on the web server needs to be transmitted, along with video formats information such as containers, codecs used, resolutions, frame rates, aspect ratios, audio sampling rates and bit rates. All these information would fit well as parameters in a SOAP message. However encoding then in a JSON seemed to be a much simpler solution. Both PHP and Python offer functions that convert their primitive types and data structures, like lists and dictionaries, into JSON strings. XML messages have a greater verbosity comparing to JSON messages. Features like XML tag attributes are not required for our application.
+\begin{itemize}
+ \item \textbf{Random}: choose a random CIS from the pool and forward the request from web server to it.
+ \item \textbf{Optimum}: send a get load request to each CIS, calculate which one is the least loaded and forward the request from web server to it.
+ \item \textbf{Randomized Suboptimal}: choose $k$ random CIS machines, send a get load request to each one, calculate which one is the least loaded and forward the request from the web server to it.
+\end{itemize}
-We expect web servers and their CIS Load Balancers to know CIS peers in advance. So there is no need for discovery services that could provide contact information for new CIS peers. This would reduce administrative control and would raise security concerns like discovering malicious CIS peers. So there is no need for service discovery features like UDDI from SOAP ecosystem.
+The \textit{optimum policy} is slower because it must wait until all CIS machines respond to get load request, so although it finds the best solution it does not scale for systems with a big number of CIS machines. This policy is recommended for small scale systems. The \textit{random policy} is the fastest, but it doesn't found the best solution, but it loads each CIS machine with equal probability, providing a good load balancing. It is recommended for big systems. \textit{Randomized suboptimal policy} is a compromise between optimum policy and random policy and is recommended for medium sized systems. The choice between the three policies not only depends on the number of CIS machines from the system, but also on the size of the raw video files that need to be processed.
-Services functionality does not need to be described because it is expected to be known in advance by the client application, so SOAP's WSDL feature is not needed.
+\subsection{Front End and Back End Communication}
+\label{subsec:communication}
-The simplicity of our web services and our need for a low communication footprint suggest us to use a RESTful web service with JSON encoded information when the POST method is needed. SOAP extra features like WSDL and UDDI are not required for our application, giving us another reason to exclude it as a candidate.
+The web server needs to communicate with Content Ingestion Server, whether or not through a CIS Load Balancer (CIS-LB), by sending a content ingestion request. By using a web service for this communication implementation overhead is reduced. Sending HTTP requests from the PHP web server application is much more easy then creating a custom new protocol. The same applies at the other communication point, the Python server, where requests are received by Web.py framework, which makes HTTP methods processing extremely easy.
-\subsection{Securing Content Ingestion Server}
-\label{subsec:securing-cis}
+If another video platform decides to use our solution based on CIS machines, interoperability is simplified by using web service interfaces, no matter what programming language is used for web server application.
-As pointed in the previous section, we require a low communication overhead. In Section \ref{subsec:ws-sec-perf} we have shown that WS-Security needs more processing time for message parsing. But is this worth it?
+\subsection{The Choice for the Web Service Type}
+\label{subsec:web-service}
-WS-Security offers end-to-end security, but P2P-Tube web servers and CIS peers are designed to be tightly coupled, usually being in the same data center or under the authority of the same organization. All these components communicate directly without proxies. So a simple point-to-point communication over HTTPS could be enough for our application.
+Our choice between a SOAP web service and a simple RESTful web service was based on our needs. We wanted to make a server with a low communication overhead and SOAP has the disadvantage of consuming more computational resources when processing requests. Our messages that need to be passed through different services have a simple structure.
-The additional overhead of WS-Security against TLS/SSL solution is a price to pay for the advantage of an end-to-end communication. However, our solution is not designed to use proxies. So HTTPS with TLS or SSL is enough for our application and is much more easy to implement. Usually any library that supports HTTP also supports HTTPS. On the server side two additional informations need to be passed: server's certificate and its private key.
+The \textit{get load request} does not have any parameters, so a simple HTTP GET request is sufficient and any extra data transmitted as XML with SOAP is redundant.
-Because CIS communication with a CIS-LB or with a web server can be encrypted, authentication information can be added into messages when using the HTTP POST methods. CIS requires an user name and a password for content ingestion requests.
+\textit{Content ingestion request} is a message with a greater complexity. The name of the uploaded file located on the web server needs to be transmitted, along with video formats information such as containers, codecs used, resolutions, frame rates, aspect ratios, audio sampling rates and bit rates. All these information would fit well as parameters in a SOAP message. However encoding them in a JSON seemed to be a much simpler solution. Both PHP and Python offer functions that convert their primitive types and data structures, like lists and dictionaries, into JSON strings. XML messages have a greater verbosity comparing to JSON messages. Features like XML tag attributes are not required for our application.
-If CIS, CIS-LB and web server peers are located in the same data center which is secured and isolated from the exterior, secure communication between them might not be required. Taking into account the fact that HTTPS doubles communication overhead, the system administrator must think twice before securing services' communication.
+We expect web servers and their CIS Load Balancers to know CIS machines in advance. So there is no need for discovery services that could provide contact information for new CIS machines. This would reduce administrative control and would raise security concerns like discovering malicious CIS machines. So there is no need for service discovery features like UDDI from SOAP ecosystem.
-File transfer between web server and CIS is made through a pluggable interface. Other protocols like FTP \cite{ftp}, scp \cite{scp} and rsync \cite{rsync} can be used. We currently implemented an FTP interface, where the control channel is encrypted using TLS. Data channel does not require encryption if the files are not secret. Securing this channel would substantially increase resource usage. We are planning to implement a rsync file transfer interface too. This protocol is secured by default because is built over SSH. It also has the advantage of reducing the amount of data sent over the network by transferring only the differences between files.
+Services functionality does not need to be described because it is expected to be known in advance by the client application, so SOAP's WSDL feature is not needed.
+The simplicity of our web services and our need for a low communication footprint suggested us to use a RESTful web service with JSON encoded information when the POST method is needed. SOAP extra features like WSDL and UDDI are not required for our application, giving us another reason to exclude it as a candidate.
\ No newline at end of file
projects / living-lab-site.git / blobdiff