Paper Info
Title
Grade to the Edge: How Many Unreliable Nodes Does It Take to Break a Content Delivery Network?
Abstract
Delivering content from a network via a client-server architecture is expensive not only for content owners but also for network operators. Moving content closer to the end user is already used in Content Delivery Networks (CDN). Multi-Access Edge Computing (MEC) enables us to shift the content even closer by using the storage of end users. But, due to the large media files, storage and transport costs for peers increase significantly. Network Coding can reduce these costs. However, peers in CDNs tend to be highly fluctuating and often need to be restored, making continuous availability of data at the network edge a problem. While for uncoded data, individual packets lost due to peer failures can be tracked to determine availability, the availability of coded data is currently distinguished only in two cases: either there are still enough linearly independent packets to decode the file, or there are not. However, we have found that the network’s combined coded cache loses quality over time due to recovery. This quality loss, which we refer to as grade, can be measured by very cost-effective monitoring. If the grade falls below a certain limit, we can intervene in the network by performing a cache refresh to prevent data becoming unavailable preemptively. In this paper, we present the cases in which such monitoring is useful, how the grade is calculated, and when a cache refresh is necessary. The results show that we can reduce network traffic by up to 34% with minimal storage costs through efficient monitoring.
Year
DOI
Venue
2022
10.1109/WoWMoM54355.2022.00068
2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)
Keywords
DocType
ISBN
CDN,Network Coding,RLNC,Distributed Storage,Reliability,Monitoring,IPFS
Conference
978-1-6654-0877-6
Citations 
PageRank 
References 
0
0.34
8
Authors
5
Name
Order
Citations
PageRank
Sandra Zimmermann100.34
Paul Schwenteck200.34
Juan A. Cabrera300.34
Giang T. Nguyen400.34
Frank H. P. Fitzek5706123.89