Design and Analysis of Hincent, Quick Content Distribution With Priorities and High Incentives

Abstract

Existing literature shows that Peer-to-Peer (P2P) content sharing can result in significant scalability gains in addition to assisting content distribution networks (CDNs). However, currently proposed CDN and P2P hybrid schemes do not provide accurate and efficient incentives to attract and maintain more peers. Besides, they do not use efficient prioritized congestion control and content source selection mechanisms to reduce content transfer time. We present Hincent, a quick content distribution protocol, which uses efficient prioritized rate allocation and content selection algorithms offering high incentives to participating peers. The fair incentives attract more peers which securely download and distribute contents. This in turn can benefit content providers and network operators. The Hincent rate allocations results in quicker content transfer time when compared with existing schemes. Hincent also employs effective rate enforcement mechanisms without requiring changes to the TCP/IP stack or to existing routers. Unlike existing centralized schemes such as YouTube, the design allows peers to have full control of (their) contents while sharing them with others using personal web servers. We have also briefly describe how Hincent can be implemented using surrogate (cloud or cloudlet) servers with OpenFlow vSwitches. We have implemented Hincent in the NS2 simulator. Our detailed trace-based experiments show that Hincent outperforms existing schemes in terms of file download time and throughput by up to 30% on average. The results also demonstrate that Hincent obtains fair uplink prices for the uploaders and fair cost for the downloaders maintaining an overall system fairness. Besides, the results show the efficient Hincent enforcements of the prioritized allocations. Our Hincent implementation using an Apache SQL Server with PHP in Linux virtual machines demon- strates that Hincent content index management mechanisms are scalable.