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The significance of load balancing parallel systems and applications has been recognized widely. Modern day multi-processor operating systems, for instance Windows Server, Solaris 10, Linux 2.6 and FreeBSD 7.2 utilize a two-level scheduling approach to enable efficient resource sharing. The first level uses a distributed run queue model with per core queues and fair scheduling policies to manage every core. However, the second level of load balancing re-disseminates tasks all over cores. The very first level is scheduling in time, the second scheduling in space. The executions in use share a similar design philosophy such as: • The threads are assumed to be independent • Locality is essential • The load is equated to queue length The present design of load balancing mechanisms integrates assumptions about the workload behavior. Interactive workloads are features by independent tasks that are quiescent for a long time span. Server workloads retain a huge number of threads that are mostly independent and utilize synchronization for mutual exclusion on the small shared data items and not for enforcing data or control dependence. In order to accommodate these workloads, the load balancing executions in use does not start threads on the new cores depending on the global system data. The common feature of the present load balancing designs offers the following features: • They are designed to conduct the best in the cases where the cores are frequently idle • The load balancing make use of a coarse-grained global optimality criterion Today service providers specializing in remote desktop solutions has come up with load balancing solutions that leverage the parallel multi-core processing to cost-efficiently drive industry-leading performance all over a rich server load balancing and application acceleration feature set for unparalleled total value of ownership. Available on application delivery controller hardware and engineered on modern day cloud, data center and virtual platforms these load balancers enhance application performance and speed up the ROI from smaller organizations to the huge service providers. Other advantages are: • Local and global server load balancer with multi-unit clustering for 99.999% application uptime and data center scalability • High-end application-fluent traffic management for optimized delivery of business critical applications and IP services • Helps to offload Web and application servers for maximized efficiency, capacity and return on investment • Application-specific certifications and configuration guides for quick deployment of optimized configurations Hence, the modern day load balancers provide a strategic point of control for optimizing the safety, accessibility and performance of enterprise applications, data center devices and IP data services.
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