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A connection-level call admission control using genetic algorithm for MultiClass multimedia services in wireless networks
Call admission control in a wireless cell in a personal communication system (PCS) can be modeled as an M/M/C/C queuing system with m classes of users. Semi-Markov Decision Process (SMDP) can be used to optimize channel utilization with upper bounds on handoff blocking probabilities as Quality of Service constraints. However, this method is too time-consuming and therefore it fails when state space and action space are large. In this paper, we apply a genetic algorithm approach to address the situation when the SMDP approach fails. We code call admission control decisions as binary strings, where a value of â1â in the position i (i=1,âŠm) of a decision string stands for the decision of accepting a call in class-i; a value of â0â in the position i of the decision string stands for the decision of rejecting a call in class-i. The coded binary strings are feed into the genetic algorithm, and the resulting binary strings are founded to be near optimal call admission control decisions. Simulation results from the genetic algorithm are compared with the optimal solutions obtained from linear programming for the SMDP approach. The results reveal that the genetic algorithm approximates the optimal approach very well with less complexity
Unified and Distributed QoS-Driven Cell Association Algorithms in Heterogeneous Networks
This paper addresses the cell association problem in the downlink of a
multi-tier heterogeneous network (HetNet), where base stations (BSs) have
finite number of resource blocks (RBs) available to distribute among their
associated users. Two problems are defined and treated in this paper: sum
utility of long term rate maximization with long term rate quality of service
(QoS) constraints, and global outage probability minimization with outage QoS
constraints. The first problem is well-suited for low mobility environments,
while the second problem provides a framework to deal with environments with
fast fading. The defined optimization problems in this paper are solved in two
phases: cell association phase followed by the optional RB distribution phase.
We show that the cell association phase of both problems have the same
structure. Based on this similarity, we propose a unified distributed algorithm
with low levels of message passing to for the cell association phase. This
distributed algorithm is derived by relaxing the association constraints and
using Lagrange dual decomposition method. In the RB distribution phase, the
remaining RBs after the cell association phase are distributed among the users.
Simulation results show the superiority of our distributed cell association
scheme compared to schemes that are based on maximum signal to interference
plus noise ratio (SINR)
Cross-layer design of multi-hop wireless networks
MULTI -hop wireless networks are usually defined as a collection of nodes
equipped with radio transmitters, which not only have the capability to
communicate each other in a multi-hop fashion, but also to route each othersâ data
packets. The distributed nature of such networks makes them suitable for a variety of
applications where there are no assumed reliable central entities, or controllers, and
may significantly improve the scalability issues of conventional single-hop wireless
networks.
This Ph.D. dissertation mainly investigates two aspects of the research issues
related to the efficient multi-hop wireless networks design, namely: (a) network
protocols and (b) network management, both in cross-layer design paradigms to
ensure the notion of service quality, such as quality of service (QoS) in wireless mesh
networks (WMNs) for backhaul applications and quality of information (QoI) in
wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of
this Ph.D. dissertation, different network settings are used as illustrative examples,
however the proposed algorithms, methodologies, protocols, and models are not
restricted in the considered networks, but rather have wide applicability.
First, this dissertation proposes a cross-layer design framework integrating
a distributed proportional-fair scheduler and a QoS routing algorithm, while using
WMNs as an illustrative example. The proposed approach has significant performance
gain compared with other network protocols. Second, this dissertation proposes
a generic admission control methodology for any packet network, wired and
wireless, by modeling the network as a black box, and using a generic mathematical
0. Abstract 3
function and Taylor expansion to capture the admission impact. Third, this dissertation
further enhances the previous designs by proposing a negotiation process,
to bridge the applicationsâ service quality demands and the resource management,
while using WSNs as an illustrative example. This approach allows the negotiation
among different service classes and WSN resource allocations to reach the optimal
operational status. Finally, the guarantees of the service quality are extended to
the environment of multiple, disconnected, mobile subnetworks, where the question
of how to maintain communications using dynamically controlled, unmanned data
ferries is investigated
4. generĂĄciĂłs mobil rendszerek kutatĂĄsa = Research on 4-th Generation Mobile Systems
A 3G mobil rendszerek szabvĂĄnyosĂtĂĄsa a vĂ©gĂ©hez közeledik, legalĂĄbbis a meghatĂĄrozĂł kĂ©pessĂ©gek tekintetĂ©ben. EzĂ©rt lĂ©tfontossĂĄgĂș azon technikĂĄk, eljĂĄrĂĄsok vizsgĂĄlata, melyek a következĆ, 4G rendszerekben meghatĂĄrozĂł szerepet töltenek majd be. Több ilyen kutatĂĄsi irĂĄnyvonal is lĂ©tezik, ezek közĂŒl projektĂŒnkben a fontosabbakra koncentrĂĄltunk. A következĆben felsoroljuk a kutatott terĂŒleteket, Ă©s röviden összegezzĂŒk az elĂ©rt eredmĂ©nyeket. SzĂłrt spektrumĂș rendszerek KifejlesztettĂŒnk egy Ășj, rĂĄdiĂłs interfĂ©szen alkalmazhatĂł hĂvĂĄsengedĂ©lyezĂ©si eljĂĄrĂĄst. SzimulĂĄciĂłs vizsgĂĄlatokkal tĂĄmasztottuk alĂĄ a megoldĂĄs hatĂ©konysĂĄgĂĄt. A projektben kutatĂłkĂ©nt rĂ©sztvevĆ Jeney GĂĄbor sikeresen megvĂ©dte Ph.D. disszertĂĄciĂłjĂĄt neurĂĄlis hĂĄlĂłzatokra Ă©pĂŒlĆ többfelhasznĂĄlĂłs detekciĂłs technikĂĄk tĂ©mĂĄban. Az elĂ©rt eredmĂ©nyek Imre SĂĄndor MTA doktori disszertĂĄciĂłjĂĄba is beĂ©pĂŒltek. IP alkalmazĂĄsa mobil rendszerekben TovĂĄbbfejlesztettĂŒk, teszteltĂŒk Ă©s ĂĄltalĂĄnosĂtottuk a projekt keretĂ©ben megalkotott Ășj, gyƱrƱ alapĂș topolĂłgiĂĄra Ă©pĂŒlĆ, a jelenleginĂ©l nagyobb megbĂzhatĂłsĂĄgĂș IP alapĂș hozzĂĄfĂ©rĂ©si koncepciĂłt. A tĂ©makörben Szalay MĂĄtĂ© Ph.D. disszertĂĄciĂłja mĂĄr a nyilvĂĄnos vĂ©dĂ©sig jutott. Kvantum-informatikai mĂłdszerek alkalmazĂĄsa 3G/4G detekciĂłra Ăj, kvantum-informatikai elvekre Ă©pĂŒlĆ többfelhasznĂĄlĂłs detekciĂłs eljĂĄrĂĄst dolgoztunk ki. Ehhez Ășj kvantum alapĂș algoritmusokat is kifejlesztettĂŒnk. Az eredmĂ©nyeket nemzetközi folyĂłiratok mellett egy sajĂĄt könyvben is publikĂĄltuk. | The project consists of three main research directions. Spread spectrum systems: we developed a new call admission control method for 3G air interfaces. Project member Gabor Jeney obtained the Ph.D. degree and project leader Sandor Imre submitted his DSc theses from this area. Application of IP in mobile systems: A ring-based reliable IP mobility mobile access concept and corresponding protocols have been developed. Project member MĂĄtĂ© Szalay submitted his Ph.D. theses from this field. Quantum computing based solutions in 3G/4G detection: Quantum computing based multiuser detection algorithm was developed. Based on the results on this field a book was published at Wiley entitled: 'Quantum Computing and Communications - an engineering approach'
The Value-of-Information in Matching with Queues
We consider the problem of \emph{optimal matching with queues} in dynamic
systems and investigate the value-of-information. In such systems, the
operators match tasks and resources stored in queues, with the objective of
maximizing the system utility of the matching reward profile, minus the average
matching cost. This problem appears in many practical systems and the main
challenges are the no-underflow constraints, and the lack of matching-reward
information and system dynamics statistics. We develop two online matching
algorithms: Learning-aided Reward optimAl Matching () and
Dual- () to effectively resolve both challenges.
Both algorithms are equipped with a learning module for estimating the
matching-reward information, while incorporates an additional
module for learning the system dynamics. We show that both algorithms achieve
an close-to-optimal utility performance for any
, while achieves a faster convergence speed and a
better delay compared to , i.e., delay and convergence under
compared to delay and convergence under
( and are maximum estimation errors for
reward and system dynamics). Our results reveal that information of different
system components can play very different roles in algorithm performance and
provide a systematic way for designing joint learning-control algorithms for
dynamic systems
Online Independent Set Beyond the Worst-Case: Secretaries, Prophets, and Periods
We investigate online algorithms for maximum (weight) independent set on
graph classes with bounded inductive independence number like, e.g., interval
and disk graphs with applications to, e.g., task scheduling and spectrum
allocation. In the online setting, it is assumed that nodes of an unknown graph
arrive one by one over time. An online algorithm has to decide whether an
arriving node should be included into the independent set. Unfortunately, this
natural and practically relevant online problem cannot be studied in a
meaningful way within a classical competitive analysis as the competitive ratio
on worst-case input sequences is lower bounded by .
As a worst-case analysis is pointless, we study online independent set in a
stochastic analysis. Instead of focussing on a particular stochastic input
model, we present a generic sampling approach that enables us to devise online
algorithms achieving performance guarantees for a variety of input models. In
particular, our analysis covers stochastic input models like the secretary
model, in which an adversarial graph is presented in random order, and the
prophet-inequality model, in which a randomly generated graph is presented in
adversarial order. Our sampling approach bridges thus between stochastic input
models of quite different nature. In addition, we show that our approach can be
applied to a practically motivated admission control setting.
Our sampling approach yields an online algorithm for maximum independent set
with competitive ratio with respect to all of the mentioned
stochastic input models. for graph classes with inductive independence number
. The approach can be extended towards maximum-weight independent set by
losing only a factor of in the competitive ratio with denoting
the (expected) number of nodes
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