Distributed Online En-Route Caching

Content caching at intermediate nodes is an effective way to optimize the operations of Computer networks, so that future requests can be served without going back to the origin of the content. Several caching techniques have been proposed in literature, including techniques that require major chang...

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Veröffentlicht in:IEEE transactions on parallel and distributed systems Jg. 27; H. 12; S. 3455 - 3468
Hauptverfasser: Gharaibeh, Ammar, Khreishah, Abdallah, Khalil, Issa, Wu, Jie
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithm design and analysis
Algorithms
asymptotic optimality
Asymptotic properties
Cache storage
Caching
caching incentive
competitive ratio
Complexity theory
Computer architecture
Computer networks
Current measurement
En-route caching
Nodes
Optimization
Quality of service
TCP/IP (protocol)
TCPIP
ISSN:1045-9219, 1558-2183
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Zusammenfassung:Content caching at intermediate nodes is an effective way to optimize the operations of Computer networks, so that future requests can be served without going back to the origin of the content. Several caching techniques have been proposed in literature, including techniques that require major changes to the Internet architecture. In this work, we present a low complexity, distributed, and online caching algorithm based on content popularity. Our algorithm performs en-route caching using a simple cost-reward comparison. Therefore, it can be integrated with the current TCP/IP model. We use the concept of competitive ratio to measure the performance of any online caching algorithm, in terms of traffic savings, with respect to the performance of the optimal offline algorithm that has a complete knowledge of the future. We show that under our settings, no online algorithm can achieve a better competitive ratio than Ω(logn), where n is the number of nodes in the network. Furthermore, we show that under realistic scenarios, our algorithm has an asymptotically optimal competitive ratio in terms of the number of nodes in the network. We also study several extensions to the basic algorithm and show their effectiveness through extensive simulations.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2016.2547396