(1) The appearance of P2P.
P2P file downloading (e.g., music, video, graphic, etc.) has become very popular internet application. It consumes the biggest portion of bandwidth in broadband. In North America and Europe, P2P service’s Bit Torrent accounts for averagely 37% of Upstream (Top 1 rank) on fixed network. It effects on both the bandwidth usage management and low internet speeds.
(2) The specialized analysis technique regarding P2P Traditional traffic analysis technique approaches the port based analysis. However it is less accurate to identify P2P traffic because P2P traffic frequently disguises its existence by arbitrary port. To overcome misclassification of P2P based on L4 level of port analysis, packetLiner provides DPI based signature matching and heuristic behavior analysis techniques to reach the high accuracy of P2P identification. While the network links are congested, P2P traffic tends to unfairly steal bandwidth from other internet applications and tries to avoid congestion by multiple techniques for efficiently transferring data between peers. packetLiner provides the multiple techniques to detect P2P traffic’s congestion avoidance.
- Detection of tracker(Server) and trakerless(Peer) - Detection of IPv6 tunneling (Toredo, 6 to 4) - Detection of encrypted traffic
[ Detection technique of Tracker & Trackerless ]
(3) The P2P control packetLiner enforces policy technics such as shaping, rate limited and block on classified P2P services. These enforcements alleviate the network congestion by optimizing the number of P2P connections and the volume of the P2P traffic in the existing bandwidth. A network operator enables to achieve subscribers’ QoS (Quality of Service) and reasonable CAPEX & OPEX management.
Smart management of grid delivery networks
(1) The appearance of KGRID As the file sharing services are dramatically increasing, the types of file sharing are generally divided into two ways. First way is to download the data from content providers’ web server in their data center, called CDN (Content Delivery Network). And second way is to download the data from Peer to Peer (P2P). Recently, the combination of CDN and P2P is frequently shown in the network, called KGRID. The problem of this KGRID is to consume the large amount of bandwidth and result in lower quality of internet service to subscribers.
[ The combination of CDN & P2P, called KGRID ]
(2)The specialized analysis technique regarding KGRID KGRID services include their own content providers (e.g., Amazon, Dropbox, Google driver, etc.) but the information of content providers on the services tends to change in a short term. Therefore, there is the limit to identify KGRID services by the information of the content providers only. To increase the high accuracy of KGRID classification, packetLiner has found that KGRID services, in common, use grid delivery network solution such as KGRID, TGRID, TGSM, etc. packetLiner differently approaches to identify KGRID services by the types of traffic downloading such as KGRID CDN Download, KGRID Peer Download and KGRID Index.
(3) The KGRID service control packetLiner enforces the policy technics of rate limit and shaping on the types of KGIRD traffic downloading. These enforcements alleviate the network congestion by allocating an appropriate amount of bandwidth and improve QoS.
[ packetLiner policy enforcements on KGIRD service ]