5,336 research outputs found
Clustering Algorithms for Scale-free Networks and Applications to Cloud Resource Management
In this paper we introduce algorithms for the construction of scale-free
networks and for clustering around the nerve centers, nodes with a high
connectivity in a scale-free networks. We argue that such overlay networks
could support self-organization in a complex system like a cloud computing
infrastructure and allow the implementation of optimal resource management
policies.Comment: 14 pages, 8 Figurs, Journa
Coalition Formation and Combinatorial Auctions; Applications to Self-organization and Self-management in Utility Computing
In this paper we propose a two-stage protocol for resource management in a
hierarchically organized cloud. The first stage exploits spatial locality for
the formation of coalitions of supply agents; the second stage, a combinatorial
auction, is based on a modified proxy-based clock algorithm and has two phases,
a clock phase and a proxy phase. The clock phase supports price discovery; in
the second phase a proxy conducts multiple rounds of a combinatorial auction
for the package of services requested by each client. The protocol strikes a
balance between low-cost services for cloud clients and a decent profit for the
service providers. We also report the results of an empirical investigation of
the combinatorial auction stage of the protocol.Comment: 14 page
A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications
Despite the numerous benefits brought by Device-to-Device (D2D)
communications, the introduction of D2D into cellular networks poses many new
challenges in the resource allocation design due to the co-channel interference
caused by spectrum reuse and limited battery life of User Equipments (UEs).
Most of the previous studies mainly focus on how to maximize the Spectral
Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we
study how to maximize each UE's Energy Efficiency (EE) in an
interference-limited environment subject to its specific Quality of Service
(QoS) and maximum transmission power constraints. We model the resource
allocation problem as a noncooperative game, in which each player is
self-interested and wants to maximize its own EE. A distributed
interference-aware energy-efficient resource allocation algorithm is proposed
by exploiting the properties of the nonlinear fractional programming. We prove
that the optimum solution obtained by the proposed algorithm is the Nash
equilibrium of the noncooperative game. We also analyze the tradeoff between EE
and SE and derive closed-form expressions for EE and SE gaps.Comment: submitted to IET Communications. arXiv admin note: substantial text
overlap with arXiv:1405.1963, arXiv:1407.155
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