Recent proposals for network virtualization provide a promising way to overcome the Internet ossification. The key idea of network virtualization is to build a diversified Internet to support a variety of network services and architectures through a shared substrate. A major challenge in network virtualization is the assigning of substrate resources to virtual networks (VN) efficiently and on-demand. This paper focuses on two versions of the VN assignment problem: VN assignment without reconfiguration (VNA-I) and VN assignment with reconfiguration (VNAII). For the VNA-I problem, we develop a basic scheme as a building block for all other advanced algorithms. Subdividing heuristics and adaptive optimization strategies are then presented to further improve the performance. For the VNA-II problem, we develop a selective VN reconfiguration scheme that prioritizes the reconfiguration of the most critical VNs. Extensive simulation experiments demonstrate that the proposed algorithms can achieve good performance under a wide range of network conditions.

Algorithms for Assigning Substrate Network Resources to Virtual Network Components

In-network caching necessitates the transformation of centralised operations of traditional, overlay caching techniques to a decentralised and uncoordinated environment. Given that caching capacity in routers is relatively small in comparison to the amount of forwarded content, a key aspect is balanced distribution of content among the available caches. In this paper, we are concerned with decentralised, real-time distribution of content in router caches. Our goal is to reduce caching redundancy and in turn, make more efficient utilisation of available cache resources along a delivery path.Our in-network caching scheme, called ProbCache, approximates the caching capability of a path and caches contents probabilistically in order to: i) leave caching space for other flows sharing (part of) the same path, and ii) fairly multiplex contents of different flows among caches of a shared path.We compare our algorithm against universal caching and against schemes proposed in the past for Web-Caching architectures, such as Leave Copy Down (LCD). Our results show reduction of up to 20% in server hits, and up to 10% in the number of hops required to hit cached contents, but, most importantly, reduction of cache-evictions by an order of magnitude in comparison to universal caching.

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Probabilistic in-network caching for information-centric networks

Object replication strategies in content distribution networks

This paper studies the problem of where to place network caches. Emphasis is given to caches that are transparent to the clients since they are easier to manage and they require no cooperation from the clients. Our goal is to minimize the overall flow or the average delay by placing a given number of caches in the network. We formulate these location problems both for general caches and for transparent en-route caches (TERCs), and identify that, in general, they are intractable. We give optimal algorithms for line and ring networks, and present closed form formulae for some special cases. We also present a computationally efficient dynamic programming algorithm for the single server case. This last case is of particular practical interest. It models a network that wishes to minimize the average access delay for a single web server. We experimentally study the effects of our algorithm using real web server data. We observe that a small number of TERCs are sufficient to reduce the network traffic significantly. Furthermore, there is a surprising consistency over time in the relative amount of web traffic from the server along a path, lending a stability to our TERC location solution. Our techniques can be used by network providers to reduce traffic load in their network.

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The cache location problem

Being able to identify the groups of clients that are responsible for a significant portion of a Web site's requests can be helpful to both the Web site and the clients. In a Web application, it is beneficial to move content closer to groups of clients that are responsible for large subsets of requests to an origin server. We introduce clusters---a grouping of clients that are close together topologically and likely to be under common administrative control. We identify clusters using a ``network-aware" method, based on information available from BGP routing table snapshots.

/pdf/on-network-aware-clustering-of-web-clients-4pzdtwszo2.pdf

On network-aware clustering of Web clients

Caching improves network and system performance for WWW browsing. The way caches are currently deployed requires clients or caches to be aware of the location of nearby caches. This creates management and connguration problems, which may also lead to performance bottlenecks. In contrast, Transparent en-route caches (TERC) are devices that are placed at appropriate locations within the network and work obliviously. A TERC snaps web requests and web data. If the requested item exists in the TERC's memory, the data is sent to the requester, otherwise the request is transparently forwarded up the routing path. In this work, we study the important problem of where to place network caches, and in particular, TERCs. This problem is intractable for general networks, and thus we concentrate on regular topologies namely lines and rings. We give both a general dynamic programming algorithm, and closed formulas for some special cases. Our results demonstrate both the signiicant saving achieved by using TERCs, and the importance of placing the caches in the optimal locations.

P. Krishnan

Papers

The cache location problem

Transparent en-route cache location for regular networks.

Synthesis, crystallization, spectroscopic analysis, NLO, HOMO-LUMO, and LDT of a single crystal of thiourea manganese (II) sulfate