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ABSTRACT: This paper studies the problem of self-organizing heterogeneous LTE systems.
We propose a model that jointly considers several important characteristics of
heterogeneous LTE system, including the usage of orthogonal frequency division
multiple access (OFDMA), the frequency-selective fading for each link, the
interference among different links, and the different transmission capabilities
of different types of base stations. We also consider the cost of energy by
taking into account the power consumption, including that for wireless
transmission and that for operation, of base stations and the price of energy.
Based on this model, we aim to propose a distributed protocol that improves the
spectrum efficiency of the system, which is measured in terms of the weighted
proportional fairness among the throughputs of clients, and reduces the cost of
energy. We identify that there are several important components involved in
this problem. We propose distributed strategies for each of these components.
Each of the proposed strategies requires small computational and
communicational overheads. Moreover, the interactions between components are
also considered in the proposed strategies. Hence, these strategies result in a
solution that jointly considers all factors of heterogeneous LTE systems.
Simulation results also show that our proposed strategies achieve much better
performance than existing ones.
02/2013;
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ABSTRACT: This paper studies the problem of content distribution in wireless
peer-to-peer networks where all nodes are selfish and non-cooperative. We
propose a model that considers both the broadcast nature of wireless channels
and the incentives of nodes, where each node aims to increase its own download
rate and reduces its upload rate through the course of content distribution. We
then propose a protocol for these selfish nodes to exchange contents. Our
protocol is distributed and does not require the exchange of money, reputation,
etc., and hence can be easily implemented without additional infrastructure.
Moreover, we show that our protocol can be easily modified to employ network
coding.
The performance of our protocol is studied. We derive a closed-form
expression of Nash Equilibriums when there are only two files in the system.
The prices of anarchy, both from each node's perspective and the whole system's
perspective, are also characterized. Moreover, we propose a distributed
mechanism where each node adjusts its strategies only based on local
information and show that the mechanism converges to a Nash Equilibrium. We
also introduce an approach for calculating Nash Equilibriums for systems that
incorporate network coding when there are more than two files.
12/2012;
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ABSTRACT: Stochastic Processing Networks (SPNs) can be used to model communication
networks, manufacturing systems, service systems, etc. We consider a real-time
SPN where tasks generate jobs with strict deadlines according to their traffic
patterns. Each job requires the concurrent usage of some resources to be
processed. The processing time of a job may be stochastic, and may not be known
until the job completes. Finally, each task may require that some portion of
its tasks to be completed on time.
In this paper, we study the problem of verifying whether it is feasible to
fulfill the requirements of tasks, and of designing scheduling policies that
actually fulfill the requirements. We first address these problems for systems
where there is only one resource. Such systems are analog to ones studied in a
previous work, and, similar to the previous work, we can develop sharp
conditions for feasibility and scheduling policy that is feasibility-optimal.
We then study systems with two resources where there are jobs that require both
resources to be processed. We show that there is a reduction method that turns
systems with two resources into equivalent single-resource systems. Based on
this method, we can also derive sharp feasibility conditions and
feasibility-optimal scheduling policies for systems with two resources.
04/2012;
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I-Hong Hou
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ABSTRACT: Wireless sensor networks have been increasingly used for real-time
surveillance over large areas. In such applications, it is important to support
end-to-end delay constraints for packet deliveries even when the corresponding
flows require multi-hop transmissions. In addition to delay constraints, each
flow of real-time surveillance may require some guarantees on throughput of
packets that meet the delay constraints. Further, as wireless sensor networks
are usually deployed in challenging environments, it is important to
specifically consider the effects of unreliable wireless transmissions.
In this paper, we study the problem of providing end-to-end delay guarantees
for multi-hop wireless networks. We propose a model that jointly considers the
end-to-end delay constraints and throughput requirements of flows, the need for
multi-hop transmissions, and the unreliable nature of wireless transmissions.
We develop a framework for designing feasibility-optimal policies. We then
demonstrate the utility of this framework by considering two types of systems:
one where sensors are equipped with full-duplex radios, and the other where
sensors are equipped with half-duplex radios. When sensors are equipped with
full-duplex radios, we propose an online distributed scheduling policy and
proves the policy is feasibility-optimal. We also provide a heuristic for
systems where sensors are equipped with half-duplex radios. We show that this
heuristic is still feasibility-optimal for some topologies.
04/2012;
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IEEE Wireless Commun. 01/2012; 19:48-59.
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ABSTRACT: A challenging problem in multi-band multi-cell self-organized wireless
systems, such as multi-channel Wi-Fi networks, femto/pico cells in 3G/4G
cellular networks, and more recent wireless networks over TV white spaces, is
of distributed resource allocation. This involves four components: channel
selection, client association, channel access, and client scheduling. In this
paper, we present a unified framework for jointly addressing the four
components with the global system objective of maximizing the clients
throughput in a proportionally fair manner. Our formulation allows a natural
dissociation of the problem into two sub-parts. We show that the first part,
involving channel access and client scheduling, is convex and derive a
distributed adaptation procedure for achieving Pareto-optimal solution. For the
second part, involving channel selection and client association, we develop a
Gibbs-sampler based approach for local adaptation to achieve the global
objective, as well as derive fast greedy algorithms from it that achieve good
solutions.
02/2011;
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Proceedings of the 12th ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2011, Paris, France, May 16-20, 2011; 01/2011
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ABSTRACT: We study the problem of scheduling periodic real-time tasks so as to meet their individual minimum reward requirements. A task generates jobs that can be given arbitrary service times before their deadlines. A task then obtains rewards based on the service times received by its jobs. We show that this model is compatible to the imprecise computation models and the increasing reward with increasing service models. In contrast to previous work on these models, which mainly focus on maximize the total reward in the system, we aim to fulfill different reward requirements by different tasks, which offers better fairness and allows fine-grained tradeoff between tasks. We first derive a necessary and sufficient condition for a system, along with reward requirements of tasks, to be feasible. We also obtain an off-line feasibility optimal scheduling policy. We then studies a sufficient condition for a policy to be feasibility optimal or achieves some approximation bound. This condition can serve as a guideline for designing on-line scheduling policy and we obtains a greedy policy based on it. We prove that the on-line policy is feasibility optimal when all tasks have the same periods and also obtain an approximation bound for the policy under general cases. Comment: 10 pages, 7 figures, under submission to RTSS 2010
06/2010;
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ABSTRACT: We develop a general approach for designing scheduling policies for real-time traffic over wireless channels. We extend prior work, which characterizes a real-time flow by its traffic pattern, delay bound, timely-throughput requirement, and channel reliability, to allow time-varying channels, allow clients to have different deadlines, and allow for the optional employment of rate adaptation. Thus, our model allow the treatment of more realistic fading channels as well as scenarios with mobile nodes, and the usage of more general transmission strategies. We derive a sufficient condition for a scheduling policy to be feasibility optimal, and thereby establish a class of feasibility optimal policies. We demonstrate the utility of the identified class by deriving a feasibility optimal policy for the scenario with rate adaptation, time-varying channels, and heterogeneous delay bounds. When rate adaptation is not available, we also derive a feasibility optimal policy for time-varying channels. For the scenario where rate adaptation is not available but clients have different delay bounds, we describe a heuristic. Simulation results are also presented which indicate the usefulness of the scheduling policies for more realistic and complex scenarios.
INFOCOM, 2010 Proceedings IEEE; 04/2010
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ABSTRACT: This paper studies the problem of utility maximization for clients with delay based QoS requirements in wireless networks. We adopt a model used in a previous work that characterizes the QoS requirements of clients by their delay constraints, channel reliabilities, and timely throughput requirements. In this work, we assume that the utility of a client is a function of the timely throughput it obtains. We treat the timely throughput for a client as a tunable parameter by the access point (AP), instead of a given value as in the previous work. We then study how the AP should assign timely throughputs to clients so that the total utility of all clients is maximized. We apply the techniques introduced in two previous papers to decompose the utility maximization problem into two simpler problems, a CLIENT problem and an ACCESS-POINT problem. We show that this decomposition actually describes a bidding game, where clients bid for the service time from the AP. We prove that although all clients behave selfishly in this game, the resulting equilibrium point of the game maximizes the total utility. In addition, we also establish an efficient scheduling policy for the AP to reach the optimal point of the ACCESS-POINT problem. We prove that the policy not only approaches the optimal point but also achieves some forms of fairness among clients. Finally, simulation results show that our proposed policy does achieve higher utility than all other compared policies.
INFOCOM, 2010 Proceedings IEEE; 04/2010
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Proceedings of the 11th ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2010, Chicago, IL, USA, September 20-24, 2010; 01/2010
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[show abstract]
[hide abstract]
ABSTRACT: We develop a general approach for designing scheduling policies for real-time traffic over wireless channels. We extend prior work, which characterizes a real-time flow by its traffic pattern, delay bound, timely-throughput requirement, and channel reliability, to allow time-varying channels, allow clients to have different deadlines, and allow for the optional employment of rate adaptation. Thus, our model allow the treatment of more realistic fading channels as well as scenarios with mobile nodes, and the usage of more general transmission strategies. We derive a sufficient condition for a scheduling policy to be feasibility optimal, and thereby establish a class of feasibility optimal policies. We demonstrate the utility of the identified class by deriving a feasibility optimal policy for the scenario with rate adaptation, time-varying channels, and heterogeneous delay bounds. When rate adaptation is not available, we also derive a feasibility optimal policy for time-varying channels. For the scenario where rate adaptation is not available but clients have different delay bounds, we describe a heuristic. Simulation results are also presented which indicate the usefulness of the scheduling policies for more realistic and complex scenarios.
08/2009;
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ABSTRACT: This paper studies the problem of utility maximization for clients with delay based QoS requirements in wireless networks. We adopt a model used in a previous work that characterizes the QoS requirements of clients by their delay constraints, channel reliabilities, and delivery ratio requirements. In this work, we assume that the utility of a client is a function of the delivery ratio it obtains. We treat the delivery ratio for a client as a tunable parameter by the access point (AP), instead of a given value as in the previous work. We then study how the AP should assign delivery ratios to clients so that the total utility of all clients is maximized. We apply the techniques introduced in two previous papers to decompose the utility maximization problem into two simpler problems, a CLIENT problem and an ACCESS-POINT problem. We show that this decomposition actually describes a bidding game, where clients bid for the service time from the AP. We prove that although all clients behave selfishly in this game, the resulting equilibrium point of the game maximizes the total utility. In addition, we also establish an efficient scheduling policy for the AP to reach the optimal point of the ACCESS-POINT problem. We prove that the policy not only approaches the optimal point but also achieves some forms of fairness among clients. Finally, simulation results show that our proposed policy does achieve higher utility than all other compared policies. Comment: submitted to INFOCOM 2010
08/2009;
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Proceedings of the 10th ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2009, New Orleans, LA, USA, May 18-21, 2009; 01/2009
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INFOCOM 2009. 28th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 19-25 April 2009, Rio de Janeiro, Brazil; 01/2009
