7,920 research outputs found
Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities
Optimization of energy consumption in future intelligent energy networks (or
Smart Grids) will be based on grid-integrated near-real-time communications
between various grid elements in generation, transmission, distribution and
loads. This paper discusses some of the challenges and opportunities of
communications research in the areas of smart grid and smart metering. In
particular, we focus on some of the key communications challenges for realizing
interoperable and future-proof smart grid/metering networks, smart grid
security and privacy, and how some of the existing networking technologies can
be applied to energy management. Finally, we also discuss the coordinated
standardization efforts in Europe to harmonize communications standards and
protocols.Comment: To be published in IEEE Communications Surveys and Tutorial
Elastic Multi-resource Network Slicing: Can Protection Lead to Improved Performance?
In order to meet the performance/privacy requirements of future
data-intensive mobile applications, e.g., self-driving cars, mobile data
analytics, and AR/VR, service providers are expected to draw on shared
storage/computation/connectivity resources at the network "edge". To be
cost-effective, a key functional requirement for such infrastructure is
enabling the sharing of heterogeneous resources amongst tenants/service
providers supporting spatially varying and dynamic user demands. This paper
proposes a resource allocation criterion, namely, Share Constrained Slicing
(SCS), for slices allocated predefined shares of the network's resources, which
extends the traditional alpha-fairness criterion, by striking a balance among
inter- and intra-slice fairness vs. overall efficiency. We show that SCS has
several desirable properties including slice-level protection, envyfreeness,
and load driven elasticity. In practice, mobile users' dynamics could make the
cost of implementing SCS high, so we discuss the feasibility of using a simpler
(dynamically) weighted max-min as a surrogate resource allocation scheme. For a
setting with stochastic loads and elastic user requirements, we establish a
sufficient condition for the stability of the associated coupled network
system. Finally, and perhaps surprisingly, we show via extensive simulations
that while SCS (and/or the surrogate weighted max-min allocation) provides
inter-slice protection, they can achieve improved job delay and/or perceived
throughput, as compared to other weighted max-min based allocation schemes
whose intra-slice weight allocation is not share-constrained, e.g., traditional
max-min or discriminatory processor sharing
A multi-criteria BS switching-off algorithm for 5G heterogeneous cellular networks with hybrid energy sources
International audienceIn this paper, we study Base Station (BS) switching-off and offloading for next generation 5G heterogeneous (macro/femto) networks supplied with hybrid energy sources. This type of network will form the basis of the high-data rate energy- efficient cellular networks in the years to come. A novel generalized multimetric algorithm is presented. Our proposal is conceived to operate in highly heterogeneous Radio Access Network (RAN) environments, as expected for 5G, where BSs with different characteristics of coverage, radio resources and power consumption coexist. The approach uses a set of metrics with a modifiable priority hierarchy in order to filter, sort and select the BS neighbors, which receive traffic during redistribution and offloading of the BSs to be put into sleep mode. In our analysis, we study the impact of BS power model trends for active, idle and sleep modes on the BS switching-off. We highlight how the continuous evolution of BS components and the introduction of renewable energy technologies play a significant role to be considered in the decision making. The multimetric approach proposed makes it possible to define and accomplish defined network performance goals by adding specific emphasis on aspects like QoS, energy savings or green equipment utilization
User Association in 5G Networks: A Survey and an Outlook
26 pages; accepted to appear in IEEE Communications Surveys and Tutorial
Matching with Externalities for Context-Aware User-Cell Association in Small Cell Networks
In this paper, we propose a novel user-cell association approach for wireless
small cell networks that exploits previously unexplored context information
extracted from users' devices, i.e., user equipments (UEs). Beyond
characterizing precise quality of service (QoS) requirements that accurately
reflect the UEs' application usage, our proposed cell association approach
accounts for the devices' hardware type (e.g., smartphone, tablet, laptop).
This approach has the practical benefit of enabling the small cells to make
better informed cell association decisions that handle practical
device-specific QoS characteristics. We formulate the problem as a matching
game between small cell base stations (SBSs) and UEs. In this game, the SBSs
and UEs rank one another based on well-designed utility functions that capture
composite QoS requirements, extracted from the context features (i.e.,
application in use, hardware type). We show that the preferences used by the
nodes to rank one another are interdependent and influenced by the existing
network-wide matching. Due to this unique feature of the preferences, we show
that the proposed game can be classified as a many-to-one matching game with
externalities. To solve this game, we propose a distributed algorithm that
enables the players (i.e., UEs and SBSs) to self-organize into a stable
matching that guarantees the required applications' QoS. Simulation results
show that the proposed context-aware cell association scheme yields significant
gains, reaching up to 52% improvement compared to baseline context-unaware
approaches.Comment: 6 pages, 3 figures, conferenc
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