1,721,037 research outputs found
Matching the business perspectives of providers and customers in future cloud markets
No full textTo date a few, big providers dominate the market of Cloud resources. They provide proprietary solutions through inflexible pricing and SLA schemes. On the research side, the community is working to define specifications and standards on several aspects of the cloud technology. When standards will get mature, interoperability among clouds will be a reality. Customers will be no more locked-up to any proprietary technology and new players will have the chance to enter the market. The competition challenge will be played on the real capability of providers to accommodate customers’ requests in a flexible way and to supply high and differentiated QoS levels. In this market scenario a mechanism must be devised to support the matchmaking between what providers offer and what customers’ applications demand. In this work we propose the definition of a semantic model that helps customers and providers to characterize their demands/offers, and provide semantic tools performing the matchmaking in such a way to maximize both the provider’s profit and the customer’s utility. The proposal has been validated by running tests on a software prototype of the discovery framewor
A cost-based approach to vertical handovers' policies between WiFi and GPRS
Full text linkTo implement seamless mobility inside an integrated, multiple (e.g., GPRS/WiFi) access system, a vertical
handover policy has to be devised. This is usually done at the mobile terminal, allowing it to be customized from an
end-user’s perspective, in order to fit individual needs/preferences. We propose a new approach in taking vertical
handover decisions, which are not anymore exclusively based on the knowledge of the available access networks ’
characteristics but also on higher level parameters which fall in the transport and application layers. To this extent,
in this paper a model has been realized and simulations have been run in order to evaluate the impact of the vertical
handover and its frequency on a set of typical user’s network applications/services. We also take into account the
user preferences in terms of cost and quality of service. We believe this approach reflects the optimal settings from
the user’s point of view with regard to his running services and applications. Our aim is to understand how to define
a metric to be used in order to devise a solution which should try to balance the overall cost of vertical handovers
with the actual benefits they bring to actual user’s networking needs. This way, each mobile user could
autonomously apply the handover decision policy, which is more convenient to his specific need
A semantic discovery frame work to support supply-demand matchmaking in cloud service markets
No full textA semantic model to support advanced supply-demand matchmaking in future cloud resources market
No full textMatchmaking semantic security policies in heterogeneous clouds
No full textThe adoption of the cloud paradigm to access IT resources and services has posed many security issues which need to be cared of. Security becomes even a much bigger concern when services built on top of many commercial clouds have to interoperate. Among others, the value of the service delivered to end customers is strongly affected by the security of network which providers are able to build in typical SOA contexts. Currently, every provider advertises its own security strategy by means of proprietary policies, which are sometimes ambiguous and very often address the security problem from a non-uniform perspective. Even policies expressed in standardized languages do not appear to fit a dynamic scenario like the SOA’s, where services need to be sought and composed on the fly in a way that is compatible with the end-to-end security requirements. We then propose an approach that leverages on the semantic technology to enrich standardized security policies with an ad-hoc content. The semantic annotation of policies enables machine reasoning which is then used for both the discovery and the composition of security-enabled services. In the presented approach the semantic enrichment of policies is enforced by an automatic procedure. We further developed a semantic framework capable of matchmaking in a smart way security capabilities of providers and security requirements of customers, and tested it on a use case scenari
MapReduce Join Across Geo-Distributed Data Centers
No full textMapReduce is with no doubt the parallel computation paradigm which has managed to interpret and serve at best the need, expressed in any field, of running fast and accurate analyses on Big Data. The strength of MapReduce is its capability of exploiting the computing power of a cluster of resources, by distributing the load on multiple computing units, and of scaling with the number of computing units. Today many data analysis algorithms are available in the MapReduce form: Data Sorting, Data Indexing, Word Counting, Relations Joining to name just a few. These algorithms have been observed to work fine in computing context where the computing units (nodes) connect by way of high performing network links (in the order of Gigabits per second). Unfortunately, when it comes to run MapReduce on nodes that are geographically distant to each other the performance dramatically degrades. Basically, in such scenarios the cost for moving data among nodes connected via geographic links counterbalances the benefit of parallelization. In this paper the issues of running MapReduce Joins in a geo-distributed computing context are discussed. Furthermore, we propose to boost the performance of the Join algorithm by leveraging a hierarchical computing approach
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