7,155 research outputs found
Characterizing a Meta-CDN
CDNs have reshaped the Internet architecture at large. They operate
(globally) distributed networks of servers to reduce latencies as well as to
increase availability for content and to handle large traffic bursts.
Traditionally, content providers were mostly limited to a single CDN operator.
However, in recent years, more and more content providers employ multiple CDNs
to serve the same content and provide the same services. Thus, switching
between CDNs, which can be beneficial to reduce costs or to select CDNs by
optimal performance in different geographic regions or to overcome CDN-specific
outages, becomes an important task. Services that tackle this task emerged,
also known as CDN broker, Multi-CDN selectors, or Meta-CDNs. Despite their
existence, little is known about Meta-CDN operation in the wild. In this paper,
we thus shed light on this topic by dissecting a major Meta-CDN. Our analysis
provides insights into its infrastructure, its operation in practice, and its
usage by Internet sites. We leverage PlanetLab and Ripe Atlas as distributed
infrastructures to study how a Meta-CDN impacts the web latency
Efficient Subgraph Matching on Billion Node Graphs
The ability to handle large scale graph data is crucial to an increasing
number of applications. Much work has been dedicated to supporting basic graph
operations such as subgraph matching, reachability, regular expression
matching, etc. In many cases, graph indices are employed to speed up query
processing. Typically, most indices require either super-linear indexing time
or super-linear indexing space. Unfortunately, for very large graphs,
super-linear approaches are almost always infeasible. In this paper, we study
the problem of subgraph matching on billion-node graphs. We present a novel
algorithm that supports efficient subgraph matching for graphs deployed on a
distributed memory store. Instead of relying on super-linear indices, we use
efficient graph exploration and massive parallel computing for query
processing. Our experimental results demonstrate the feasibility of performing
subgraph matching on web-scale graph data.Comment: VLDB201
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
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