Skyline service selection method based on MapReduce and multi-target simulated annealing

A mapreduce framework and simulated annealing technology, applied in electrical components, transmission systems, etc., can solve the problems of low efficiency, difficult to deal with service selection technology, difficult to guarantee the quality of the optimal solution, etc., to improve efficiency and effect, and optimize global QoS. Effect

Active Publication Date: 2015-06-24
李金忠
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Problems solved by technology

With the increasing number of services and QoS attributes in the Internet, as well as the distributed nature of services in the real world, traditional service selection techniques are difficult to deal with, and its efficiency is low and the quality of its optimal solution is difficult to guarantee

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  • Skyline service selection method based on MapReduce and multi-target simulated annealing
  • Skyline service selection method based on MapReduce and multi-target simulated annealing
  • Skyline service selection method based on MapReduce and multi-target simulated annealing

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[0103] Such as Figure 5 As shown, assume that there is an abstract composite service instance composed of several abstract services, and each abstract service AS i can have n i candidate concrete services to complete the abstract service AS i The functions of these candidate specific services ws i Indexed in HDFS massive service pool. After the first stage of "screening massive services", each type of candidate specific WS i The number of the original n i reduced to m i First, the non-Skyline services of various services are eliminated, and the Skyline services of various services are left to form the Skyline service library. After the second stage of "preferred Skyline service", each abstract service AS i A corresponding specific service WS is selected i Finally, combine them into a specific combined service. At this stage, since each abstract service AS i Selected specific service WS i If they are different, they can be combined into a large number of specific co...

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Abstract

The invention relates to a Skyline service selection method based on MapReduce and multi-target simulated annealing. The method includes the steps of 1, screening mass services, to be specific, under a MapReduce frame, by Skyline calculation by a block nesting algorithm and a divide-and-conquer algorithm, screening services of high QoS (quality of service) from a mass service pool, and generating a Skyline service library; 2, optimally selecting the Skyline services, to be specific, under the MapReduce frame, by means of the multi-target simulated annealing algorithm, optimally selecting the Skyline services from the Skyline service library generated in the step 1, and generating a Pareto combination service set; 3, optimally selecting Pareto combination services, to be specific, by means of the Top-k query processing technique, according to user personalized QoS preferences, optimally selecting k Pareto combination services meeting user QoS constraints from the Pareto combination service set generated in the step 2. Compared with the prior art, method has the advantages such that efficiency and effect of selecting mass services can be greatly improved.

Description

technical field [0001] The invention relates to the technical field of network services, in particular to a Skyline service selection method based on MapReduce and multi-objective simulated annealing. Background technique [0002] With the rapid development of service computing, cloud computing, big data and other related technologies, the available services on the Internet (including grid services, web services, cloud services, etc.) have grown rapidly in type and explosively in number. Massive services distributed in different geographical locations and on different servers may be different services with the same or similar functions rather than different functional attributes (QoS). How to select the service with better QoS from the mass services with equivalent functions under the user's preference requirements to form a combined service with the best QoS to meet the user's QoS constraints and recommend it to the user in a personalized way has become an academic issue. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/08
CPCH04L41/5019H04L41/5041H04L67/51
Inventor 李金忠夏洁武谭云兰曾小荟李满华吴玉春王巧玲胡运全
Owner 李金忠
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