Virtualization and Biometrics As Etzioni Article Review

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Some Key applications are:Physical Acces facility and secure-area access, time-and-attendance monitoring. Growth: Flat, starting at 13% of total market revenues and ending at 14%. Logical Access: PC, networks, mobile devices, kiosks, accounts. Growth: From 21% to 31% of total market revenues. Identity Services: Background check enrollment, credentialing, document issuance. Growth: Decline from 65% to 47% of total market revenues. Surveillance and Monitoring: Time and attendance, watchlists. Growth: From less than 1% to nearly 8% of total market revenue.

Virtualisation is the key technology to transform what's happening in the data centre and link it to external service providers using common technology, common formats, common shipping containers. Add information and security to the picture and we have an interesting view of the future of it, where we combine the attributes of what we like about data centres and what we like about clouds for fully virtualised assets in the data centre and compatible infrastructure that we can flex in and out of. A key aspect of this vision is to address what happens in the enterprise, on the device and the user experience, as well as with service providers. Three key technology areas that require addressing are the cloud operating system, what we need to do with networks and computing, and how does information infrastructure evolve and flex in this fully virtualised environment.The optimization of resource allocations through the use of virtualization has limits. Middleware may impose its own resource limits that cannot be overridden by the hypervisor. For instance, application servers may become constricted by such things as Java** Virtual Machine (JVM**) heap size restrictions or the number of allowed socket connections in a connection pool.19 in such cases, additional virtual cluster nodes may be needed to overcome the constraint.

The optimization of resource allocations through the use of virtualization has limits. Middleware may impose its own resource limits that cannot be overridden by the hypervisor. For instance, application servers may become constricted by such things as Java** Virtual Machine (JVM**) heap size restrictions or the number of allowed socket connections in a connection pool.19 in such cases, additional virtual cluster nodes may be needed to overcome the constraint.

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Physical resource consumption across virtual machines is cumulative, which has a number of implications. For instance, an OS such as Linux may automatically fill up any unused memory available to it with an I/O cache. Such a technique is reasonable in a standalone server environment, but in a virtual one it can needlessly consume resources that could better be used by other virtual cluster nodes. Hence, "right-sizing" virtual machine memory capacity becomes an important configuration consideration.

Likewise, availability management (and other system management) tools often depend on management agents running on each node to gather and report status back to a management server. These agents will typically consume some portion of a CPU even when the system they are monitoring is idle. On standalone systems, this is negligible. But even if one agent on each of 100 virtual machines is using only 1% of a physical processor, cumulatively the agents consume a full processor at idle. One solution is the use of management tools that operate at the hypervisor level rather than the individual guest level. Examples include IBM Operations Manager for z/VM and VMware VirtualCenter. A second possible solution is to use a tool whose agents operate with extremely low overhead (or only run if a particular resource has been consumed), such that even their accumulated processor usage will be tolerable. Alternatively, agents can be selectively deployed to only those virtual machines deemed the most critical.

An emerging virtualization optimization is to enable certain segments of memory to be directly shared between guests. This can be leveraged, for instance, to allow read-only Linux shared library files to be shared by all Linux guests, greatly reducing total real memory consumption.20 the impact, if any, of such memory sharing on guest availability in the face of various failure types is a topic for future work.

Reference

Etzioni, a. "Identification cards in America. " Society 36.5 (1999): 70-76. Social Science Module, ProQuest. Web. 4 Jun. 2010.

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