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How To Make Bittorrent 7.7 Download !EXCLUSIVE! Faster
DOWNLOAD ->->->-> https://urloso.com/2tg76r
Greetings! I've been a Bittorrent user for like 3 years but this is the first time i need to post. Usually my bittorrent worked fine, but like a week from now it's been horribly slow; it randomly shows parts of the torrents i'm downloading as red (not available) and i'm also having the slow speed issue described on this post, it can stay at 0.1-1 for like 5 minutes and then go back to not downloading
I already made sure to tell bittorrent where the new downloads should be located and actually managed to get a few, but then it decided to work randomly according to its own whims. By the way i already tried adding an excemption on firewall and even entirely disabling it (VIPRE firewall); windows firewall is shut down also.
Recently i download a file (5GB) my download speed was normal 190250 kbps but today i downloaded another file and it becam 0.110kbps i dont know why but my internet is fine i can download files at normal speed w/o the use of bittorrent but when i try to torrent something the download speed dramatically drops.
I am having this problem also. I have a Mac and Bittorrent version 7.4.1. A week ago I was getting speeds of 1.5-2.2 mb/s and this week a file will get to about 400 kb/s and then the speed will plummet to 5-7 kb/s within a few seconds. I have not changed settings in the program, but there was an update that I installed to Bittorrent a few days ago. I consider myself a seasoned bittorrent user and do not have any firewall blocks and I am downloading files with 1000+ seeds and connect to 100+ rather quickly still but the speed does not increase. I can get the speed to increase if I quit Bittorrent and relaunch it but the increase again only lasts a few seconds and is not anywhere close to what I was getting. Please, oh, please, someone have a solution for me. This is so frustrating!!!
Sequential writes to disk can be done in much higher speeds than that, but bittorrent downloading is done \"rarest first\" which has a close to random write pattern. Such writes can be more than hundred times slower than sequential writes.
BitTorrent is a peer-to-peer client used to transfer large amounts of data over the internet through the BitTorrent protocol. The protocol works by connecting users directly whereby they share segments of a file; as they download files they are also uploading in parallel which works great to efficiently manage bandwidth and increase the speed at which files are transferred. The BitTorrent client was the very first application created for the BitTorrent protocol and was designed in 2001 with version 1.0 released in July of that year. Overall the following versions have always had a good reputation for ease of use especially for beginners; ensuring stability, performance and being light on PC resources. The user interface has been through many modifications to improve usability and includes a number of options to manage your downloads/uploads and provides efficient data on your downloads such as number of peers and speed. Since version 6.0, BitTorrent has become a rebranded version of Other Internet SoftwareAres GalaxyAzureusBearshareBitCometBitlordBitSpiritCuteMXDC++eDonkey2000eMuleiMeshKazaaKazaa LiteLimeWireLphantBitTorrent Commentsvar disqus_shortname = 'oldversion';var disqus_identifier = 'windows/bittorrent';var disqus_url = ' ';(function() {var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true;dsq.src = 'http://' + disqus_shortname + '.disqus.com/embed.js';(document.getElementsByTagName('head')[0] document.getElementsByTagName('body')[0]).appendChild(dsq);})();Please enable JavaScript to view the comments powered by Disqus.blog comments powered by Disqus Top 5 Contributorssofiane41,005 PointsPKO1716,000 Pointssafarisilver13,345 Pointsalpha110,985 PointsMatrixisme9,755 PointsSee More Users Upload SoftwareGet points for uploading software and use them to redeem prizes!
Bittorrent protocol has strict rules involving how the downloading is achived, to get more, you attract the better peers by giving more. With optimally tuned clients on an identical swarm with the same randomly connected peers, all bittorrent clients will perform equally. With \"out of box\" settings one client may perform better with a specific type of connections and a different client with another type of connection, but what makes bitcomet different is that we have developed cross-protocol downloading which allows the bitcomet peer to source the data from outside the bittorrent swarm. This not only helps the bitcomet peer, but benefits the entire swarm and in some cases can revive a dead or dying torrent without seeders. Many times an unseeded task will not complete, but if a bitcomet peer is able to complete the download from non-bittorrent sources, it can then become a seeder and revive the dead torrent. This makes the bitcomet peer a valuable asset to the entire community.
5. LTseed (Long Term Seed), a protocol developed by and proprietary to bitcomet which enables bitcomet peers to share files previously downloaded. This occurs only when the bandwidth isn't needed for traditional bittorrent downloading and can greatly accelerate the downloads.
The combination of these sources can dramatically increase your performance and in addition bitcomet is also developing server-assisted downloading referred to as VIP acceleration. When this works properly it uses state of the art highspeed commercial servers that run the tasks on your behalf and sends you the completed files via LTseed protocol. Besides increasing the speed, this can also make you anonymous to the swarm. I mentioned \"when it works\" because it's gotten off to a rocky start and has spent a couple years in beta testing phase but it's slowly developing. When initially released free trials were available to all, which was an epic fail just as it would be if you opened a new fastfood resturant and offered free hamburgers and had lines backed up for miles and not even your paying customers could get a meal, so we had to put strict restrictions on the free trial, at first limited to longstanding members with 80,000 points or more which was gradually reduced to 40,000 and I'm sure it will be further reduced as development continues.Plans start at $5 and you can sign up at vip.bitcomet.com. I'd recommend if you try it that you consider the purchase a donation, as it's definitely not bug free but it has improved vastly. This is a costly system to implement and develop and the fees are designed to keep it self sufficient and we all have high hopes that it will be, but it's had a rough beginning but if you understand how it works and where it can and cannot help you, it can be a good tool to use, but even without VIP BitComet can outperform other clients (as you've witnessed).
Abstract:Scalable distribution of large files has been the area of muchresearch and commercial interest in the past few years. In this paper,we describe the CoBlitz system, which efficiently distributes largefiles using a content distribution network (CDN) designed for HTTP. Asa result, CoBlitz is able to serve large files without requiring anymodifications to standard Web servers and clients, making it aninteresting option both for end users as well as infrastructureservices. Over the 18 months that CoBlitz and its partner service,CoDeploy, have been running on PlanetLab, we have had the opportunityto observe its algorithms in practice, and to evolve its design. Thesechanges stem not only from observations on its use, but also from abetter understanding of their behavior in real-world conditions. Thisutilitarian approach has led us to better understand the effects ofscale, peering policies, replication behavior, and congestion, givingus new insights into how to better improve their performance. Withthese changes, CoBlitz is able to deliver in excess of 1 Gbps onPlanetLab, and to outperform a range of systems, including researchsystems as well as the widely-used BitTorrent.1 IntroductionMany new content distribution networks (CDNs) have recently beendeveloped to focus on areas not generally associated with``traditional'' Web (HTTP) CDNs. These systems often focus ondistributing large files, especially in flash crowd situations where anews story or software release causes a spike in demand. These newapproaches break away from the ``whole-file'' data transfer model, thecommon access pattern for Web content. Instead, clients downloadpieces of the file (called chunks, blocks, or objects) and exchangethese chunks with each other to form the complete file. The mostwidely used system of this type is BitTorrent (12),while related research systems include Bullet (20),Shark (2), and FastReplica (9).Using peer-to-peer systems makes sense when the window of interest inthe content is short, or when the content provider cannot affordenough bandwidth or CDN hosting costs. However, in other scenarios, amanaged CDN service may be an attractive option, especially forbusinesses that want to offload their bandwidth but want morepredictable performance. The problem arises from the fact that HTTPCDNs have not traditionally handled this kind of traffic, and are notoptimized for this workload. In an environment where objects average10KB, and where whole-file access is dominant, suddenly introducingobjects in the range of hundreds of megabytes may have undesirableconsequences. For example, CDN nodes commonly cache popular objects inmain memory to reduce disk access, so serving several large files atonce could evict thousands of small objects, increasing their latencyas they are reloaded from disk.To address this problem, we have developed the CoBlitz large filetransfer service, which runs on top of the CoDeeN content distributionnetwork, an HTTP-based CDN. This combination provides severalbenefits: (a) using CoBlitz to serve large files is as simple aschanging its URL - no rehosting, extra copies, or additional protocolsupport is required; (b) CoBlitz can operate with unmodified clients,servers, and tools like curl or wget, providing greater ease-of-usefor users and for developers of other services; (c) obtaining maximumper-client performance does not require multiple clients to bedownloading simultaneously; and (d) even after an initial burst ofactivity, the file stays cached in the CDN, providing latecomers withthe cached copy.From an operational standpoint, this approach of running a large-filetransfer service on top of an HTTP content distribution network alsohas several benefits: (a) given an existing CDN, the changes tosupport scalable large-file transfer are small; (b) no dedicatedresources need to be devoted for the large-file service, allowing itto be practical even if utilization is low or bursty; (c) thealgorithmic changes to efficiently support large files also benefitsmaller objects.Over the 18 months that CoBlitz and its partner service, CoDeploy,have been running on PlanetLab, we have had the opportunity to observeits algorithms in practice, and to evolve its design, both to reflectits actual use, and to better handle real-world conditions. Thisutilitarian approach has given us a better understanding of theeffects of scale, peering policies, replication behavior, andcongestion, giving us new insights into how to improve performance andreliability. With these changes, CoBlitz is able to deliver in excessof 1 Gbps on PlanetLab, and to outperform a range of systems,including research systems as well as BitTorrent.In this paper, we discuss what we have learned in the process, and howthe observations and feedback from long-term deployment have shapedour system. We discuss how our algorithms have evolved, both toimprove performance and to cope with the scalability aspects of oursystem. Some of these changes stem from observing the real behavior ofthe system versus the abstract underpinnings of our originalalgorithms, and others from observing how our system operates whenpushed to its limits. We believe that our observations will be usefulfor three classes of researchers: (a) those who are consideringdeploying scalable large-file transfer services; (b) those trying tounderstand how to evaluate the performance of such systems, and; (c)those who are trying to capture salient features of real-worldbehavior in order to improve the fidelity of simulators and emulators.2 BackgroundIn this section, we provide general information about HTTP CDNs, theproblems caused by large files, and the history of CoBlitz andCoDeploy. 2.1 HTTP Content Distribution NetworksContent distribution networks relieve Web congestion by replicatingcontent on geographically-distributed servers. To provide loadbalancing and to reduce the number of objects served by each node,they use partitioning schemes, such as consistenthashing (17), to assign objects to nodes. CDNnodes tend to be modified proxy servers that fetch files on demand andcache them as needed. Partitioning reduces the number of nodes thatneed to fetch each object from the origin servers (or other CDNnodes), allowing the nodes to cache more objects in main memory,eliminating disk access latency and improving throughput.In this environment, serving large files can cause several problems.Loading a large file from disk can temporarily evict several thousandsmall files from the in-memory cache, reducing the proxy'seffectiveness. Popular large files can stay in the main memory for alonger period, making the effects more pronounced. To get a sense ofthe performance loss that can occur, one can examine results from theProxy Cacheoffs (25), which show that the same proxies,when operating as ``Web accelerators,'' can handle 3-6 times therequest rate than operating in ``forward mode,'' with much largerworking sets. So, if a CDN node suddenly starts serving a data setthat exceeds its physical memory, its performance will dropdramatically, and latency rises sharply. Bruce Maggs, Akamai's VP ofResearch, states:``Memory pressure is a concern for CDN developers, because for optimallatency, we want to ensure that the tens of thousands of popularobjects served by each node stay in the main memory. Especially inenvironments where caches are deployed inside the ISP, any increase inlatency caused by objects being fetched from disk would be anoticeable degradation. In these environments, whole-file caching oflarge files would be a concern (21).''Akamai has a service called EdgeSuite Net Storage,where large files reside in specialized replicated storage, and areserved to clients via overlay routing (1).We believe that this service demonstratesthat large files are a qualitatively different problem forCDNs.2.2 Large-file SystemsAs a result of these problems and other concerns, most systems toscalably serve large files departed from the use of HTTP-based CDNs.Two common design principles are evident in these systems: treat largefiles as a series of smaller chunks, and exchange chunks betweenclients, instead of always using the origin server. Operating onchunks allows finer-grained load balancing, and avoids the trade-offsassociated with large-file handling in traditional CDNs. Fetchingchunks from other peers not only reduces load on the origin, but alsoincreases aggregate capacity as the number of clients increases.We subdivide these systems based on their inter-client communicationtopology. We term those that rely on greedy selection or all-to-allcommunication as examples of the swarm approach, while thosethat use tree-like topologies are termed stream systems.Swarm systems, such as BitTorrent (12) andFastReplica (9), preceded stream systems, and scaleddespite relatively simple topologies. BitTorrent originally used aper-file centralized directory, called a tracker, that lists clientsthat are downloading or have recently downloaded the file. Clients usethis directory to greedily find peers that can provide them withchunks. The newest BitTorrent can operate with tracker informationshared by clients. In FastReplica, all clients are known at the start,and each client downloads a unique chunk from the origin. The clientsthen communicate in an all-to-all fashion to exchange chunks. Thesesystems reduce link stress compared to direct downloads from theorigin, but some chunks may traverse shared links repeatedly ifmultiple clients download them.The stream systems, such as ESM (10),SplitStream (8), Bullet (20),Astrolabe (30), and FatNemo (4) addressthe issues of load balancing and link stress by optimizing thepeer-selection process. The result generates a tree-like topology (ora mesh or gossip-based network inside the tree), which tends to stayrelatively stable during the download process. The effort intree-building can produce higher aggregate bandwidths, suitable fortransmitting the content simultaneously to a large number ofreceivers. The trade-off, however, is that the higher link utilizationis possible only with greater synchrony. If receivers are onlyloosely synchronized and chunks are transmitted repeatedly on somelinks, the transmission rate of any subtrees using those nodes alsodecreases. As a result, these systems are best suited for synchronousactivity of a specified duration.2.3 CoBlitz, CoDeploy, and CoDeeNFigure 1:Operational model for CoBlitz improvementThis paper discusses our experience running two large-filedistribution systems, CoBlitz and CoDeploy, which operate on top ofthe CoDeeN content distribution network. CoDeeN is a HTTP CDN thatruns on every available PlanetLab node, with access restrictions inplace to prevent abuse and to comply with hosting site policies. Ithas been in operation for nearly three years, and currently handlesover 25 million requests per day. To use CoDeeN, clients configuretheir browsers to use a CoDeeN node as a proxy, and all of their Webtraffic is then handled by CoDeeN. Note that this behavior is onlypart of CoDeeN as a policy decision - CoBlitz does not requirechanging any browser setting.Both CoBlitz and CoDeploy use the same infrastructure, which we callCoBlitz in the rest of this paper for simplicity. The main differencebetween the two is the access mechanism - CoDeploy requires theclient to be a PlanetLab machine, while CoBlitz is publiclyaccessible. CoDeploy was launched first, and allows PlanetLabresearchers to use a local instance of CoDeeN to fetch experimentfiles. CoBlitz allows the public to access CoDeploy by providing asimpler URL-based interface. To use CoBlitz, clients prepend theoriginal URL with :3125/ and fetch itlike any other URL. A customized DNS server maps the namecoblitz.codeen.org to a nearby PlanetLab.In 18 months of operation, the system has undergone three sets ofchanges: scaling from just North American PlanetLab nodes to all ofPlanetLab, changing the algorithms to reduce load at the originserver, and changing the algorithms to reduce overall congestion andincrease performance. Our general mode of operation is shown inFigure 1, and consists of four steps: (1)deploy the system, (2) observe its behavior in actual operation, (3)determine how the underlying algorithms, when exposed to the realenvironment, cause the behaviors, and (4) adapt the algorithms to makebetter decisions using the real-world data. We believe this approachhas been absolutely critical to our success in improving CoBlitz, aswe describe later in this paper.3 Design of Large File SplittingBefore discussing CoBlitz's optimizations, we first describe how wehave made HTTP CDNs amenable to handling large files. Our approachhas two components: modifying large file handling to efficientlysupport them on HTTP CDNs, and modifying the request routing for theseCDNs to enable more swarm-like behavior under heavy load. Though webuild on the CoDeeN CDN, we do not believe any of these changes areCoDeeN-specific - they could equally be applied to otherCDNs. Starting from an HTTP CDN maintains compatibility with standardWeb clients and servers, whereas starting with a stream-oriented CDNmight require more effort to efficiently support standard Web traffic.3.1 RequirementsWe treat large files as a set of small files that can be spread acrossthe CDN. To make this approach as transparent as possible to clientsand servers, the dynamic fragmentation and reassembly of these smallfiles is performed inside the CDN, on demand. Each CDN node has anagent that accepts clients' requests for large files and converts theminto a series of requests for pieces of the file. Pieces arespecified using HTTP1.1 byte ranges (14), which theApache Web server has supported since August 1996 (version 1.2), andwhich appeared in other servers in the same timeframe. After theserequests are injected into the CDN, the results are reassembled by theagent and passed to the client. For simplicity, this agent occupies adifferent port number than regular CoDeeN requests. The process hassome complications, mostly related to the design of traditional CDNs,limitations of HTTP, and the limitations of standard HTTP proxies(which are used as the CDN nodes). Some of these problems include:Figure 2:The client-facing agent converts asingle request for a large file into a series of requests for smallerfiles. The new URLS are only a CDN-internal representation - neitherthe client nor the origin server see them.Chunk naming - If chunks are named using the original URL,all of a file's chunks will share the same name, and will be routedsimilarly since CDNs hash URLs for routing (31,16). Since we want to spread chunks across the CDN, we mustuse a different chunk naming scheme.Range caching - We know of no HTTP proxies that cache arbitrary ranges of Web objects, though some can serve ranges fromcached objects, and even recreate a full object from all of itschunks. Since browsers are not likely to ask for arbitrary anddisjoint pieces of an object, no proxies have developed the necessarysupport. Since we want to cache at the chunk level instead of the filelevel, we must address this limitation.Congestion - During periods of bursty demand and heavysynchrony, consistent hashing may produce roving instantaneouscongestion. If many clients at different locations suddenly ask forthe same file, a lightly-loaded CDN node may see a burst of request.If the clients all ask for another file as soon as the first downloadcompletes, another CDN node may become instantly congested. Thisbursty congestion prevents using the aggregate CDN bandwidtheffectively over short time scales. 153554b96e
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