HYBRID PULL PUSH PEER TO PEER VIDEO STREAMING

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HYBRID PULL PUSH PEER TO PEER VIDEO STREAMING

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HYBRID PULL PUSH PEER TO PEER VIDEO STREAMING

VIETNAM NATIONAL UNIVERSITY, HANOI STUDENT SCIENTIFIC RESEARCH CONTEST 2012 PROJECT: HYBRID PULL PUSH PEER TO PEER VIDEO STREAMING Student: Trinh Hai Hoa Class: K53CA Supervisor: Dr Nguyen Dai Tho Gender: Male Faculty: Computer Science ABSTRACT The Peer to Peer Streaming System is using more popular in this world but most of that existing systems still can provide the services for non-interactive environment on the Internet Besides, there are many ways to deal with P2P system, which a regular way is the usage of pull and push protocols Some researches have investigated on these two protocols and how to interleave them to obtain the better performances of real time streaming in peer to peer network In these works, they used pull protocol as to retrieve pieces of data and push protocol as to spread the data to the entire network These two protocols were set to two-phase cycle which continuously switches from one push to one pull and so on The problem is how we know exactly that interleaving protocols like that will give best performances or doing more pull then switch to some push is better In this paper, we consider a two pull and one push cycle and test its performance on many kinds of configured network with simulator environment PROJECT SUMMARY Project: Hybrid Pull-Push Peer to Peer Video Streaming Research time: 11/2011 – 3/2012 Motivation Out motivation is to determine a best scenario in interleaving pull protocol and push protocol using in video streaming The research is around the work of choose a suitable number of pull request before switching to send a suitable number of push request Main content In this project, we focus on the main properties of interleaving pull-push protocol, depend on the piece and neighborhood selection policies; following up by performance of peersim simulator to examine the research Research result - Experience three scenarios of interleaving a number of pull and push request - with different type of networks in the event – based mechanism With the result, the original scenario is still the best choice Table of contents Table of figures I INTRODUCTION Nowadays, peer to peer network is becoming more and more necessary for streaming in human life due to some disadvantage of client-server model before While clientserver model must need a server to control the network, and cannot spent the power of clients computer, therefore, it cause waste to the network resources Oppositely, peer to peer network can build easily on the Internet, does not need much resources but it still can serve millions users in the world This kind of network use clients as the peer to spread streaming data to other peers that connected to them The most important thing is these peers can exchange data themselves and does not need a server to control their work, that make constructing the network is faster and also easy to upgrade Besides the power of peer to peer system, along the development of the Internet, many different P2P system were build for file-sharing like Napster, Gnutella, Kazaa or for delivery content and video like Skype…etc Therefore, human requirement for streaming system is harder day by day, especially on streaming delay and bandwidth In order to improve the performance of peer to peer system, researchers make a lot of works on these existing networks, about the network topology and the fundamental properties of them, which are mentioned in [1] In the paper the author showed that application can be file-based or stream-based The file-based services can be used only when the total file is transferred, so that average throughput and also total delay are the concern of performance In the stream-based application, the key is how to minimum the throughput and the latency of streaming information Besides, in peer to peer network, the data can be split to many smaller chunks or pieces, which make easier transmission, also called chunk-based system The chunk-based peer to peer network overlay can be classified into three main classes: Push: One peer (parent) can pass a piece to its children (another peer) without asking them which one to push Therefore, it is efficiently when multiples pieces is push only to same peer but others never arrive in the non-structured system Push is popular for the structured or tree-based network model that has long-lasting relationship between peers Pull: One peer (child) instead of waiting for chunks pushed by their parent, it actively asks for pieces from other peer (parent) but also without knowledge of which chunks their parent have Thus, the requested pieces may be server or not, in the worse case, the child cannot found that piece in any of their parent, then the data is missing at last Pull system can deal with unstructured network, where the peer can seek for multiple parents, exchange the information they have, and then complete the request data Status-based: The peer exchange status signal to describe the download process For example, zero for a missed chunk and one for available chunk An interesting approach is interleaving the two protocols above, pull protocol and push protocol to make a combined protocol which can give better delay guaranteed There are a few paper concerns about combining pull and push protocol, such as [3] and [4] However, they used pull system to fill the entire stream data or building a structured tree in network and push system to spread data content faster These works does not consider about how to interleave these two protocol mechanisms [1] provided a way to interleave two protocols and give examination on testing in simulation using a piece selection policy Depend on that, [2] make some improvements on the selection policies, which give better performance for the peer to peer network, especially the total delay and completion time Nevertheless, in this interleaving method, also the other combination methodologies, the researchers only work on one to one protocol, that means the system did a pull and switch to push, so on Therefore, a problem can be seen here is: “Is the one to one pull push combination system best for chunk based peer to peer network?” Along the result of one to one interleaving mechanisms given in [1] and [2], this paper will more on simulation, and examine the different configure of peer to peer network with two pull and one push strategy, then determine which is better between this and the original one pull to one push above The organization of remain parts is as follow In Section II, we describe the piece selection policies of interleaving mechanism Some brief description about Peersim-the Simulator using in this paper include in section III Section IV presents the result from simulation and the last part, Section V will conclude the paper and give our future works II PIECES SELECTION POLICY First, we consider that the network has only one source to produce the chunks from total data to spread to other neighborhood The produced pieces can be exchange independently through the network, which are generated from source at a constant rate, push to other peers with the determined streaming rate as simulation At network nodes (normal peers) the pieces can be push away to its neighbor, or can be pulled by its neighbor too That means each node alternate the cycle with pull and pushes mechanism, switch between two modes, fill up their data and also spread data to other nodes Each node has its own contact list with size k, which is the ID of neighborhood node that can be received the pull and push requests from it However, a node can be received request from another node that is not in its contact list In normal combination, the pieces selection policies are: - - Pull mode: a node P takes a neighbor Q and a piece randomly then send request to pull that piece from neighbor Q Q will accept the pull request if it has available upload bandwidth and the requested pieces, otherwise, the request will be refused Push mode: a node P selects a piece and push to a random neighborhood Q The neighbor Q also download that piece if it does not have it at that time and not downloading other pieces, otherwise, the request will be refused The policy above has the problem when randomly select piece and neighbor, the efficiency is not much Therefore, in [1], the author gave the better pieces selection strategy as below: - In pull mode, a node P asks its neighbor for the lowest sequence number pieces, in order to full fill the information holes in stream data - In the push mode, a node P pushes the pieces with highest sequence number among the pieces which it received via push from its neighbor Here is the pseudo code of the algorithm presented in [1] for sending the pull or push request by a node: Figure : Sending out request interleaving algorithm 10 Nevertheless, the policy in [1] got problem that neighborhood selection is still random Thus, in research of hybrid pull and push protocol, [2] studied about a better way to choose the neighbor as long as using the pieces selection strategies in [1] In this work, they provide a parameter called pushmaxID, which is an array in each node to store the maximum ID of the chunks that exchanged between this node and its neighborhoods Depend on that parameter, each node can determine which neighbor has better chance to have the chunks it need to pull or better chance to need the chunks it want to push Here are the algorithm graphs given in [2]: 12 Figure : Push Cycle with full action The given policies are: - Pull mode: a node P chooses the chunk with lowest sequence number to pull After that, it chooses the neighbor in contact list which has pushmaxID bigger than the ID of the needed piece If the pushmaxID is zero or there are no satisfied neighbors, the algorithm returns a random neighborhood to salvage the cycle 13 - III Push mode: a node P chooses the chunk with highest sequence number it has to push After that, it chooses the neighbor in contact list which has the pushmaxID smaller than the ID of the pushed piece If there are no satisfied neighbors, the algorithm will return a random neighborhood to salvage the cycle SIMULATION Introduction to Peersim [6]: In [1] and [2] the researchers use peersim as the simulator to examine their works Peersim is a java-based system which allows users to configure much kind of networks and simulation scenes All we need to is set up the parameters in configuration file then let the simulator the rest Besides, Peersim is the modulo-design, thus, developers can add more class or module to support their own purpose, like building a new protocol or else Simulation model: Peersim support two kind of simulation model, which are cycle based and event based In cycle based model, all nodes are synchronized and they work in cycle In each cycle, each node is activated continuously and a node can only be activated when there are no others nodes are working Therefore, this model can help abstract protocols can easily be constructed and executed The second kind is event based model, which has the independency between all nodes All nodes can be work simultaneously and follow the protocol rules The node can add event into the queue of simulation cycle depend on the configuration These events can affect other nodes This model must be configuring some mandatory parameters such as switch time delay, event processing protocol, network size, control protocol…etc Peersim Interfaces: The important interfaces of Peersim are: Control, Node, Protocol, Linkable, CDProtocol and EDProtocol 14 o Control Interface: include two main classes: Initializers and Observers The Initializers class configure the initial parameters of simulation and the Observers class is used to monitor all the actions caused by simulator o Node Interface: set up the network node and based attributes such as network address, protocol In simulation, nodes can be add or remove automatically o Protocol Interface: use to identify the type of protocol, linking method between nodes and provide ways for nodes to access their neighborhood o Linkable Interface: identify whether the connection between network nodes is symmetric or asymmetric o CDProtocol Interface: use for cycle based simulation model o EDProtocol Interface: use for event based simulation model Peersim Classes: o OverlayGrap: use for construct the linking methodology between network nodes, which implements Linkable Interface In simulation, OverlayGrap is edited to build a symmetric k level network with N nodes o Transport: a general transmission interface that help delivery the information from source to other nodes Besides, there is a class called UniformRandomTransport which help configure reliable transmission protocol This class has two important parameters: minimum and maximum value of packet latency UnreliableTransport: allows combination with other Transport classes, for example, UniformRandomTransport, to simulate the loss of information The parameter “Drop probability” in configuration file determines the probability that information can be loss during the simulation o Message: also known as the simple events, which can be add o queue in a somehow delay The simulator will execute each event continuously in queue follow the simulation time with a suitable protocol 15 IV EXPERIMENTS Parameter for evaluating the performance There are three main performance attributes: o Completion time: is the time that a node receives all pieces of data, count for all nodes in the network o Maximum delay: especially in live streaming, the piece latency is so important as the primary index of the performance We compute the delay for each node with all pieces The maximum delay is the highest value of delay between all nodes, computed by the formula: o Successful delivery rate: because each peer alternately execute the pull and push action, thus, we compute the successful rate of these two protocol over the pieces: Configuration file We can easily configure the simulation by changing the parameters values in the configuration file: ### Simulation seed SEED 8789789465436 ### MAX Simulation time CYCLE SIZE*CHUNKS*NEW_CHUNK_DELAY ### Verbosity level DEBUG ### Number of nodes in the network SIZE 10000 ### Number of chunks to transmit CHUNKS 500 ### Chunk size in bits CHUNK_SIZE 40000 ### Time in milliseconds to produce a new chunk NEW_CHUNK_DELAY 300 16 ### Nodes degree DEGREE 32 ### Message delay: and max MINDELAY MAXDELAY 25 ### Observer Step in milliseconds OBSERVER_STEP 10000 ## Time in millisecond needed for a node to switch between states: ## push -> pull and vice-versa SWITCHTIME ### Maximum number of push and pull attempts PUSHRETRY PULLRETRY ## Dropping rate [0:1] ## Currently, this protocol does not implement any form of "message recovery" ## therefor we are working on reliable channel DROP ## Maximum number of active connections in upload and download ## Active means that the node issues either a push or pull to a target node ## push for upload and pull for download ACT_UP ACT_DW ## Maximum number of passice connections in upload and download ## Passive means that the node is the target node which receives either a push or pull request ## therefor it will either receive a chunk via push or satisfy a pull request PAS_DW PAS_UP ## Window size for either push or pull active message, ## the node either proposes PUSH_WIN chunks in push ## or PULL_WIN for pull PUSH_WIN 10 PULL_WIN 10 #- - - - - - P R O T O C O L S - - - - - -# #############Random Generator############# random p4s.util.RandomRLC random.seed SEED ##########Simulator parameter######### network.size SIZE simulation.endtime CYCLE 17 simulation.experiments simulation.timebits 16 simulation.logtime OBSERVER-STEP simulation.stdout p4s.util.PrintLogs ## Overlay network used protocol.link RandomizedNeighbor protocol.link.capacity DEGREE ## Protocol used for chunks distribution protocol.int Alternate protocol.int.linkable link protocol.int.transport urt ## Transport protocol used protocol.urt UniformRandomTransportP4S protocol.urt.mindelay MINDELAY protocol.urt.maxdelay MAXDELAY ## Bandwidth protocol used protocol.bwp bandwidth.BandwidthAwareProtocol #- - - - - - I N I T I A L I Z E R S - - - - - -# ## Overlay network initializer init.rndlink WireKOutUnd init.rndlink.k DEGREE init.rndlink.protocol link ## Bandwidth protocol initializer init.bwi bandwidth.BandwidthAwareInitializer init.bwi.protocol bwp init.bwi.debug DEBUG ## CDF of bandwidth distribution ## separeted by commas: ## 128000,180000,290000 ## 0.3,0.7,1 init.bwi.uploadBw 128000,180000,256000 init.bwi.downloadBw 640000,640000,640000 init.bwi.bandwidthPr 0.3,0.7,1 init.bwi.active_upload ACT_UP init.bwi.active_download ACT_DW init.bwi.passive_upload PAS_UP init.bwi.passive_download PAS_DW 18 ## the following two parameters indicate the source upload/download bandwidth ## download is useless at the source, but it exists :) #init.bwi.srcup 128000 #init.bwi.srcdw 640000 ## Chunk distribution protocol initializer init.ii AlternateInitializer init.ii.protocol int init.ii.bandwidth bwp init.ii.chunks CHUNKS init.ii.chunk_size CHUNK_SIZE init.ii.push_retry PUSHRETRY init.ii.pull_retry PULLRETRY init.ii.switchtime SWITCHTIME init.ii.debug DEBUG init.ii.push_window PUSH_WIN init.ii.pull_window PULL_WIN ## - no knowledge on neighbors buffer states ## - total knowledge on neighbors buffer state ## - hybrid knowledge on neighbors buffer state init.ii.neighborsknow init.ii.degree DEGREE ## Initializers order include.init rndlink bwi ii #- - - - - - C O N T R O L S - - - - - -# ## Control that produces chunks at the source control.00 SourceObserver control.00.protocol int control.00.step NEW_CHUNK_DELAY ## Control collects statistics on the operation performed by ## peers in the chunk distribution process control.04 OperationObserver control.04.protocol int control.04.step OBSERVER_STEP/5 control.04.size SIZE control.04.chunks CHUNKS ## Write results at the end of each experiment control.04.FINAL control.04.debug DEBUG 19 ## Control collects statistics on the time in ## which peers receives chunks control.08 ChunksObserver control.08.protocol int control.08.step OBSERVER_STEP control.08.size SIZE control.08.chunks CHUNKS control.08.degree DEGREE ## Write results at the end of each experiment control.08.FINAL control.08.debug DEBUG Simulation experiments In this paper, we consider the piece selection policy implemented in [2], which provide a neighbor selection strategy depend on pushmaxID value We run the simulation for three scenarios: one pull then one push, one pull then two push and two pull then one push; on three different networks: first has 1000 nodes, contact list size is 16 and number of chunks is 500; second has 5000 nodes, contact list size is 24 and number of chunks is 500; third has 10000 nodes, contact list size is 32 and number of chunks is 500 The performance was computed with three main attributes: completion time, maximum delay and successful delivery rate then draw graph follow the cumulative distribution function (CDF) using gnuplot[5] tool 20 a Completion time Figure : Overall completion time of 1000 – 500 – 16 network For the first network with small number of nodes, we can see the performance of one pull-two push and two pull-one push scenarios is nearly the same Compare to results from the original one pull-one push, the completion time is less stable when the minimum completion time is 77 cycles but the maximum is 85 cycles Besides, the scenario one pull-one push still has little better completion time Figure : Overall completion time of 5000 – 500 – 24 network 21 The second network has some different performance compare to the first one The one pull-two push has smallest minimum completion time but the first scenario is still the most stable one Figure : Overall completion time of 10000 – 500 – 32 network The performance for the third network also has not much difference Therefore, for the completion time, the original scenario one pull – one push has got the best effect b Maximum delay Same as the completion time, in the first network, performance of chunk delivery delay of first scenario one pull – one push is better than the others; this indicated that for small network, first scenario is still the best choice For the second network with 5000 nodes, the maximum delay is increased a little bit but still shows the clear different between the two scenarios we consider with the original one 22 Figure : Chunk delivery delay of 1000 – 500 – 16 network In the last one, 10000 nodes network, there is a clear difference that the distance between three scenarios is narrowing Perhaps for the bigger network, the maximum delay is stable for every scenario Figure : Chunk delivery delay of 5000 – 500 – 24 network 23 Figure : Chunk delivery delay of 10000 – 500 – 32 network c Successful delivery rate For the 1000 nodes and 5000 nodes network, the simulation results shown that the scenario two pull – one push is much worse than the others, while the one pull – one push and one pull – two push is nearly the same performance 24 Figure : Successful delivery ratio of 1000 – 500 – 16 network Figure : Successful delivery ratio of 5000 – 500 – 24 network However, for the biggest network with 10000 nodes, the original scenario one pull – one push present the worse performance than others while successful delivery ratio is fluctuated around 24% to 39%, smaller than the remain strategies 25 Figure : Successful delivery ratio of 10000 – 500 – 32 network V CONCLUSION AND FUTURE APPROACH This paper has given the idea of interleaving pull and push protocols in interactive environment on network Follow the research of [1] and [2] we have two strategies for select pieces and neighbor to execute a pull or a push The first one in [1] is randomly take a neighborhood then pull the lowest sequence numbered chunk or push the highest sequence numbered chunks that node has, exchange the information with the chosen neighbor This scenario has weak point that random will cause waste in bandwidths and cycle while the node cannot find the suitable neighbor to the action The second one in [2] using another parameter called pushmaxID to determine the neighbor with greater aptitude to have or need the pieces that a node chose to push or pull by the same piece selection policy like [1] Nevertheless, there is a question raised that the scenario of switching between one pull and one push in protocol of these research, is it the best? In this paper, we examine two more scenarios that one pull – two push and two pull – one push then compare the performance to the original one After experience on three different networks, we conclude that using one pull then one push in cycle time can the better performance 26 In the future approach, we hope to simulate with more pull and more push scenario to specify the conclusion above is precise VI REFERENCES: [1] Alessandro Russo, Damiano Carra, Renato Lo Cigno, "On Some Fundamental Properties of P2P Push/Pull Protocols" 1-4244-2426-9/08/$20.00 ©2008 IEEE [2] PHÂN BỔ LUỒNG TRUYỀN THÔNG ĐA PHƯƠNG TIỆN NGANG HÀNG THEO PHƯƠNG THỨC KÉO ĐẨY – Luận văn thạc sĩ – Nguyễn Thị Thu Hải – Đại học Công Nghệ - 2009 [3] M Zhang, Q Zhang, and S Yang, “Understanding the Power ofPull-based Streaming Protocol: Can We Do Better?” IEEE Journal onSelected Areas in Communications, Dec 2007 [4] T Locher, R Meier, S Schmid, and R Wattenhofer, “Push-to-Pull Peer-to-Peer Live Streaming,” in Proc DISC, Sept 2007 [5] Gnuplot http://cs.ecs.baylor.edu/~donahoo/tools/gnuplot [6] PeerSim: A peer-to-peer simulator http://PeerSim.sourceforge.net ... Project: Hybrid Pull- Push Peer to Peer Video Streaming Research time: 11/2011 – 3/2012 Motivation Out motivation is to determine a best scenario in interleaving pull protocol and push protocol using... real time streaming in peer to peer network In these works, they used pull protocol as to retrieve pieces of data and push protocol as to spread the data to the entire network These two protocols... chunk-based peer to peer network overlay can be classified into three main classes: Push: One peer (parent) can pass a piece to its children (another peer) without asking them which one to push Therefore,

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Mục lục

  • I. INTRODUCTION

  • II. PIECES SELECTION POLICY

  • III. SIMULATION

    • 1. Introduction to Peersim [6]:

    • 2. Simulation model:

    • 3. Peersim Interfaces:

    • 4. Peersim Classes:

    • IV. EXPERIMENTS

      • 1. Parameter for evaluating the performance

      • 2. Configuration file

      • 3. Simulation experiments

        • a. Completion time

        • b. Maximum delay

        • c. Successful delivery rate

        • V. CONCLUSION AND FUTURE APPROACH

        • VI. REFERENCES:

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