Parameter Tuning for Scalable Multi-Resource Server Consolidation in Cloud Systems

Parameter Tuning for Scalable Multi-Resource Server Consolidation in Cloud Systems

Infrastructure as a Service cloud providers are increasingly relying on scalable and efficient Virtual Machines (VMs) placement as the main solution for reducing unnecessary costs and wastes of physical resources. However, the continuous growth of the size of cloud data centers poses scalability challenges to find optimal placement solutions. The use of heuristics and simplified server consolid...

Dynamic resource management in Cloud datacenters for Server consolidation

Cloud resource management has been a key factor for the cloud datacenters development. Many cloud datacenters have problems in understanding and implementing the techniques to manage, allocate and migrate the resources in their premises. The consequences of improper resource management may result into underutilized and wastage of resources which may also result into poor service delivery in the...

GA-Based Parameter Tuning for Multi-Agent Systems

The problem of determining the desired type and number of mobile agents on a network is not trivial. In fact, this issue of agent population composition is critical for optimal performance of agent based software systems. Too many agents will congest and slow down the network, whereas too few will create processing bottlenecks. The problem of agent population management is exacerbated on wirele...

Scalable Resource Management in Cloud Computing By

Scalable Resource Management in Cloud Computing

The exponential growth of data and application complexity has brought new challenges in the distributed computing field. Scientific applications are growing more diverse with various workloads, including traditional MPI high performance computing (HPC) to fine-grained loosely coupled many-task computing (MTC). Traditionally, these workloads have been shown to run well on supercomputers and high...