14,091 research outputs found
Load Balancing via Random Local Search in Closed and Open systems
In this paper, we analyze the performance of random load resampling and
migration strategies in parallel server systems. Clients initially attach to an
arbitrary server, but may switch server independently at random instants of
time in an attempt to improve their service rate. This approach to load
balancing contrasts with traditional approaches where clients make smart server
selections upon arrival (e.g., Join-the-Shortest-Queue policy and variants
thereof). Load resampling is particularly relevant in scenarios where clients
cannot predict the load of a server before being actually attached to it. An
important example is in wireless spectrum sharing where clients try to share a
set of frequency bands in a distributed manner.Comment: Accepted to Sigmetrics 201
A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing
The emergence of cloud computing based on virtualization technologies brings
huge opportunities to host virtual resource at low cost without the need of
owning any infrastructure. Virtualization technologies enable users to acquire,
configure and be charged on pay-per-use basis. However, Cloud data centers
mostly comprise heterogeneous commodity servers hosting multiple virtual
machines (VMs) with potential various specifications and fluctuating resource
usages, which may cause imbalanced resource utilization within servers that may
lead to performance degradation and service level agreements (SLAs) violations.
To achieve efficient scheduling, these challenges should be addressed and
solved by using load balancing strategies, which have been proved to be NP-hard
problem. From multiple perspectives, this work identifies the challenges and
analyzes existing algorithms for allocating VMs to PMs in infrastructure
Clouds, especially focuses on load balancing. A detailed classification
targeting load balancing algorithms for VM placement in cloud data centers is
investigated and the surveyed algorithms are classified according to the
classification. The goal of this paper is to provide a comprehensive and
comparative understanding of existing literature and aid researchers by
providing an insight for potential future enhancements.Comment: 22 Pages, 4 Figures, 4 Tables, in pres
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
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