35,327 research outputs found
Capacity and Stable Scheduling in Heterogeneous Wireless Networks
Heterogeneous wireless networks (HetNets) provide a means to increase network
capacity by introducing small cells and adopting a layered architecture.
HetNets allocate resources flexibly through time sharing and cell range
expansion/contraction allowing a wide range of possible schedulers. In this
paper we define the capacity of a HetNet down link in terms of the maximum
number of downloads per second which can be achieved for a given offered
traffic density. Given this definition we show that the capacity is determined
via the solution to a continuous linear program (LP). If the solution is
smaller than 1 then there is a scheduler such that the number of mobiles in the
network has ergodic properties with finite mean waiting time. If the solution
is greater than 1 then no such scheduler exists. The above results continue to
hold if a more general class of schedulers is considered.Comment: 30 pages, 6 figure
Dynamic Scheduling for Delay Guarantees for Heterogeneous Cognitive Radio Users
We study an uplink multi secondary user (SU) system having statistical delay
constraints, and an average interference constraint to the primary user (PU).
SUs with heterogeneous interference channel statistics, to the PU, experience
heterogeneous delay performances since SUs causing low interference are
scheduled more frequently than those causing high interference. We propose a
scheduling algorithm that can provide arbitrary average delay guarantees to SUs
irrespective of their statistical channel qualities. We derive the algorithm
using the Lyapunov technique and show that it yields bounded queues and satisfy
the interference constraints. Using simulations, we show its superiority over
the Max-Weight algorithm.Comment: Asilomar 2015. arXiv admin note: text overlap with arXiv:1602.0801
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
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