1,215 research outputs found
MAC design for WiFi infrastructure networks: a game-theoretic approach
In WiFi networks, mobile nodes compete for accessing a shared channel by
means of a random access protocol called Distributed Coordination Function
(DCF). Although this protocol is in principle fair, since all the stations have
the same probability to transmit on the channel, it has been shown that unfair
behaviors may emerge in actual networking scenarios because of non-standard
configurations of the nodes. Due to the proliferation of open source drivers
and programmable cards, enabling an easy customization of the channel access
policies, we propose a game-theoretic analysis of random access schemes.
Assuming that each node is rational and implements a best response strategy, we
show that efficient equilibria conditions can be reached when stations are
interested in both uploading and downloading traffic. More interesting, these
equilibria are reached when all the stations play the same strategy, thus
guaranteeing a fair resource sharing. When stations are interested in upload
traffic only, we also propose a mechanism design, based on an artificial
dropping of layer-2 acknowledgments, to force desired equilibria. Finally, we
propose and evaluate some simple DCF extensions for practically implementing
our theoretical findings.Comment: under review on IEEE Transaction on wireless communication
Towards Wireless Virtualization for 5G Cellular Systems
Although it has been defined as one of the most promising key enabling technologies for the forthcoming fifth generation cellular networks, wireless virtualization still has several challenges remaining to be addressed. Amongst those, resource allocation, which decides how to embed the different wireless virtual networks on the physical relying infrastructure, is the one receiving maximum attention. This project aims at finding the optimal resource allocation for each virtual network, in terms of channel resources, power levels and radio access technologies so that the data rate requested by each virtual network can be guaranteed and the global throughput efficiency can be maximized.Aunque haya sido definida como una de las tecnologías clave para el desarrollo de la nueva generación de sistemas móviles, la virtualización del acceso radio aún tiene muchos retos a investigar. Entre ellos, la distribución de los recursos, que tiene por objetivo encontrar el mejor encaje de las distintas redes virtuales en la infraestructura física que comparten, es el que está recibiendo la mayor atención. Este proyecto, tiene por objetivo encontrar la repartición óptima de los recursos, tanto a nivel de canal como de potencia y de tecnologías de acceso radio, para que los requisitos de las redes virtuales puedan ser garantizadas y la eficiencia global sea maximizada.Malgrat ha estat definida com una de les tecnologies claus de cara al desenvolupament de la propera cinquena generació de xarxes mòbils, la virtualització de l'accés radio encara té molts reptes oberts a fer front. Entre ells, la distribució de recursos, que té per objectiu buscar el millor encaix de les diferents xarxes virtuals en la infraestructura física que comparteixen, és la que està centrant la màxima atenció. Aquest projecte té per objectiu aconseguir la repartició òptima de recursos, pel que fa al canal, als nivells de potència i a les tecnologies radio disponibles, de manera que els requisits de cada xarxa virtual puguin ser garantits i que l'eficiència global pugui ser maximitzada
Joint Head Selection and Airtime Allocation for Data Dissemination in Mobile Social Networks
Mobile social networks (MSNs) enable people with similar interests to
interact without Internet access. By forming a temporary group, users can
disseminate their data to other interested users in proximity with short-range
communication technologies. However, due to user mobility, airtime available
for users in the same group to disseminate data is limited. In addition, for
practical consideration, a star network topology among users in the group is
expected. For the former, unfair airtime allocation among the users will
undermine their willingness to participate in MSNs. For the latter, a group
head is required to connect other users. These two problems have to be properly
addressed to enable real implementation and adoption of MSNs. To this aim, we
propose a Nash bargaining-based joint head selection and airtime allocation
scheme for data dissemination within the group. Specifically, the bargaining
game of joint head selection and airtime allocation is first formulated. Then,
Nash bargaining solution (NBS) based optimization problems are proposed for a
homogeneous case and a more general heterogeneous case. For both cases, the
existence of solution to the optimization problem is proved, which guarantees
Pareto optimality and proportional fairness. Next, an algorithm, allowing
distributed implementation, for join head selection and airtime allocation is
introduced. Finally, numerical results are presented to evaluate the
performance, validate intuitions and derive insights of the proposed scheme
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On Optimal and Fair Service Allocation in Mobile Cloud Computing
This paper studies the optimal and fair service allocation for a variety of
mobile applications (single or group and collaborative mobile applications) in
mobile cloud computing. We exploit the observation that using tiered clouds,
i.e. clouds at multiple levels (local and public) can increase the performance
and scalability of mobile applications. We proposed a novel framework to model
mobile applications as a location-time workflows (LTW) of tasks; here users
mobility patterns are translated to mobile service usage patterns. We show that
an optimal mapping of LTWs to tiered cloud resources considering multiple QoS
goals such application delay, device power consumption and user cost/price is
an NP-hard problem for both single and group-based applications. We propose an
efficient heuristic algorithm called MuSIC that is able to perform well (73% of
optimal, 30% better than simple strategies), and scale well to a large number
of users while ensuring high mobile application QoS. We evaluate MuSIC and the
2-tier mobile cloud approach via implementation (on real world clouds) and
extensive simulations using rich mobile applications like intensive signal
processing, video streaming and multimedia file sharing applications. Our
experimental and simulation results indicate that MuSIC supports scalable
operation (100+ concurrent users executing complex workflows) while improving
QoS. We observe about 25% lower delays and power (under fixed price
constraints) and about 35% decrease in price (considering fixed delay) in
comparison to only using the public cloud. Our studies also show that MuSIC
performs quite well under different mobility patterns, e.g. random waypoint and
Manhattan models
Sl-EDGE: Network Slicing at the Edge
Network slicing of multi-access edge computing (MEC) resources is expected to
be a pivotal technology to the success of 5G networks and beyond. The key
challenge that sets MEC slicing apart from traditional resource allocation
problems is that edge nodes depend on tightly-intertwined and
strictly-constrained networking, computation and storage resources. Therefore,
instantiating MEC slices without incurring in resource over-provisioning is
hardly addressable with existing slicing algorithms. The main innovation of
this paper is Sl-EDGE, a unified MEC slicing framework that allows network
operators to instantiate heterogeneous slice services (e.g., video streaming,
caching, 5G network access) on edge devices. We first describe the architecture
and operations of Sl-EDGE, and then show that the problem of optimally
instantiating joint network-MEC slices is NP-hard. Thus, we propose
near-optimal algorithms that leverage key similarities among edge nodes and
resource virtualization to instantiate heterogeneous slices 7.5x faster and
within 0.25 of the optimum. We first assess the performance of our algorithms
through extensive numerical analysis, and show that Sl-EDGE instantiates slices
6x more efficiently then state-of-the-art MEC slicing algorithms. Furthermore,
experimental results on a 24-radio testbed with 9 smartphones demonstrate that
Sl-EDGE provides at once highly-efficient slicing of joint LTE connectivity,
video streaming over WiFi, and ffmpeg video transcoding
Genetic Algorithm-based Mapper to Support Multiple Concurrent Users on Wireless Testbeds
Communication and networking research introduces new protocols and standards
with an increasing number of researchers relying on real experiments rather
than simulations to evaluate the performance of their new protocols. A number
of testbeds are currently available for this purpose and a growing number of
users are requesting access to those testbeds. This motivates the need for
better utilization of the testbeds by allowing concurrent experimentations. In
this work, we introduce a novel mapping algorithm that aims to maximize
wireless testbed utilization using frequency slicing of the spectrum resources.
The mapper employs genetic algorithm to find the best combination of requests
that can be served concurrently, after getting all possible mappings of each
request via an induced sub-graph isomorphism stage. The proposed mapper is
tested on grid testbeds and randomly generated topologies. The solution of our
mapper is compared to the optimal one, obtained through a brute-force search,
and was able to serve the same number of requests in 82.96% of testing
scenarios. Furthermore, we show the effect of the careful design of testbed
topology on enhancing the testbed utilization by applying our mapper on a
carefully positioned 8-nodes testbed. In addition, our proposed approach for
testbed slicing and requests mapping has shown an improved performance in terms
of total served requests, about five folds, compared to the simple allocation
policy with no slicing.Comment: IEEE Wireless Communications and Networking Conference (WCNC) 201
Sharing of Unlicensed Spectrum by Strategic Operators
Facing the challenge of meeting ever-increasing demand for wireless data, the
industry is striving to exploit large swaths of spectrum which anyone can use
for free without having to obtain a license. Major standards bodies are
currently considering a proposal to retool and deploy Long Term Evolution (LTE)
technologies in unlicensed bands below 6 GHz. This paper studies the
fundamental questions of whether and how the unlicensed spectrum can be shared
by intrinsically strategic operators without suffering from the tragedy of the
commons. A class of general utility functions is considered. The spectrum
sharing problem is formulated as a repeated game over a sequence of time slots.
It is first shown that a simple static sharing scheme allows a given set of
operators to reach a subgame perfect Nash equilibrium for mutually beneficial
sharing. The question of how many operators will choose to enter the market is
also addressed by studying an entry game. A sharing scheme which allows dynamic
spectrum borrowing and lending between operators is then proposed to address
time-varying traffic and proved to achieve perfect Bayesian equilibrium.
Numerical results show that the proposed dynamic sharing scheme outperforms
static sharing, which in turn achieves much higher revenue than uncoordinated
full-spectrum sharing. Implications of the results to the standardization and
deployment of LTE in unlicensed bands (LTE-U) are also discussed.Comment: To appear in the IEEE Journal on Selected Areas in Communications,
Special Issue on Game Theory for Network
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