4,426 research outputs found
System Support for Managing Invalid Bindings
Context-aware adaptation is a central aspect of pervasive computing
applications, enabling them to adapt and perform tasks based on contextual
information. One of the aspects of context-aware adaptation is reconfiguration
in which bindings are created between application component and remote services
in order to realize new behaviour in response to contextual information.
Various research efforts provide reconfiguration support and allow the
development of adaptive context-aware applications from high-level
specifications, but don't consider failure conditions that might arise during
execution of such applications, making bindings between application and remote
services invalid. To this end, we propose and implement our design approach to
reconfiguration to manage invalid bindings. The development and modification of
adaptive context-aware applications is a complex task, and an issue of an
invalidity of bindings further complicates development efforts. To reduce the
development efforts, our approach provides an application-transparent solution
where the issue of the invalidity of bindings is handled by our system,
Policy-Based Contextual Reconfiguration and Adaptation (PCRA), not by an
application developer. In this paper, we present and describe our approach to
managing invalid bindings and compare it with other approaches to this problem.
We also provide performance evaluation of our approach
On the Intrinsic Locality Properties of Web Reference Streams
There has been considerable work done in the study of Web reference streams: sequences of requests for Web objects. In particular, many studies have looked at the locality properties of such streams, because of the impact of locality on the design and performance of caching and prefetching systems. However, a general framework for understanding why reference streams exhibit given locality properties has not yet emerged.
In this work we take a first step in this direction, based on viewing the Web as a set of reference streams that are transformed by Web components (clients, servers, and intermediaries). We propose a graph-based framework for describing this collection of streams and components. We identify three basic stream transformations that occur at nodes of the graph: aggregation, disaggregation and filtering, and we show how these transformations can be used to abstract the effects of different Web components on their associated reference streams. This view allows a structured approach to the analysis of why reference streams show given properties at different points in the Web.
Applying this approach to the study of locality requires good metrics for locality. These metrics must meet three criteria: 1) they must accurately capture temporal locality; 2) they must be independent of trace artifacts such as trace length; and 3) they must not involve manual procedures or model-based assumptions. We describe two metrics meeting these criteria that each capture a different kind of temporal locality in reference streams. The popularity component of temporal locality is captured by entropy, while the correlation component is captured by interreference coefficient of variation. We argue that these metrics are more natural and more useful than previously proposed metrics for temporal locality.
We use this framework to analyze a diverse set of Web reference traces. We find that this framework can shed light on how and why locality properties vary across different locations in the Web topology. For example, we find that filtering and aggregation have opposing effects on the popularity component of the temporal locality, which helps to explain why multilevel caching can be effective in the Web. Furthermore, we find that all transformations tend to diminish the correlation component of temporal locality, which has implications for the utility of different cache replacement policies at different points in the Web.National Science Foundation (ANI-9986397, ANI-0095988); CNPq-Brazi
Optimal Content Placement for En-Route Web Caching
This paper studies the optimal placement of web files for en-route web caching. It is shown that existing placement policies are all solving restricted partial problems of the file placement problem, and therefore give only sub-optimal solutions. A dynamic programming algorithm of low complexity which computes the optimal solution is presented. It is shown both analytically and experimentally that the file-placement solution output by our algorithm outperforms existing en-route caching policies. The optimal placement of web files can be implemented with a reasonable level of cache coordination and management overhead for en-route caching; and importantly, it can be achieved with or without using data prefetching
Cache policies for cloud-based systems: To keep or not to keep
In this paper, we study cache policies for cloud-based caching. Cloud-based
caching uses cloud storage services such as Amazon S3 as a cache for data items
that would have been recomputed otherwise. Cloud-based caching departs from
classical caching: cloud resources are potentially infinite and only paid when
used, while classical caching relies on a fixed storage capacity and its main
monetary cost comes from the initial investment. To deal with this new context,
we design and evaluate a new caching policy that minimizes the overall cost of
a cloud-based system. The policy takes into account the frequency of
consumption of an item and the cloud cost model. We show that this policy is
easier to operate, that it scales with the demand and that it outperforms
classical policies managing a fixed capacity.Comment: Proceedings of IEEE International Conference on Cloud Computing 2014
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