By David N. Blank-Edelman
I even have this e-book in EPUB and PDF as retail (no conversion).
If you do platforms management paintings of any style, you might want to take care of the growing to be complexity of your atmosphere and lengthening calls for in your time. Automating method management with Perl, moment variation, not just provides you with the ideal instruments on your activity, but in addition indicates the right way to method particular difficulties and to soundly automate habitual projects. up to date and improved to hide the newest working structures, applied sciences, and Perl modules, this version of the "Otter Book" may help you:
* deal with person debts
* visual display unit filesystems and procedures
* paintings with configuration records in very important codecs akin to XML and YAML
* Administer databases, together with MySQL, MS-SQL, and Oracle with DBI
* paintings with listing companies like LDAP and energetic listing
* Script e-mail protocols and junk mail regulate
* successfully create, deal with, and study log records Administer community identify and configuration companies, together with NIS, DNS and DHCP
* continue, video display, and map community companies, utilizing applied sciences and instruments comparable to SNMP, nmap, libpcap, GraphViz and RRDtool
* increase filesystem, strategy, and community protection
This version contains extra appendixes to get you in control on applied sciences reminiscent of XML/XPath, LDAP, SNMP, and SQL. With this ebook in hand and Perl on your toolbox, you are able to do extra with less--fewer assets, much less attempt, and much much less hassle.
Read or Download Automating System Administration with Perl: Tools to Make You More Efficient PDF
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Additional info for Automating System Administration with Perl: Tools to Make You More Efficient
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10. 11. 12. Select chromosomes for crossover operation with probability pc Apply mutation operator to the selected chromosome with mutation probability pm Evaluate fitness of new chromosomes t = t+1 end while [ ] 13. Select the best solution from population 14. end for 15. end Fig. 1 Chromosome Representation In proposed algorithm, the numerical feature values of all cluster centers are encoded into a real coded chromosome as a clustering solution. The length of a particular chromosome c is lc, given by lc = d 9 K where d is the dimension of the data and K is the number of cluster centers encoded in that chromosome.
To overcome from above-described drawbacks, some researchers have dedicated to applying genetic algorithms (GAs) to the cluster analysis. Genetic algorithms (GAs)  are randomized search and optimization techniques guided by the principles of evolution and natural genetics. A comparison of the performance of their algorithm, subsequently referred to as the GA-clustering algorithm, with that of the GCA algorithm is provided in . Lin et al.  presented a genetic clustering algorithm based on a binary chromosome representation.