Zhen Kong

A Low-Complexity QoS-Aware Proportional Fair Multicarrier Scheduling Algorithm for OFDM Systems

Orthogonal frequency-division multiplexing (OFDM) systems are the major cellular platforms for supporting ubiquitous high-speed mobile applications. However, a number of research challenges remain to be tackled. One of the most important challenges is the design of a judicious packet scheduler that will make efficient use of the spectrum bandwidth. Due to the multicarrier nature of the OFDM systems, the applicability and performance of traditional wireless packet-scheduling algorithms, which are usually designed for single-carrier systems, are largely unknown. In th.is paper, we propose a new quality-of-service (QoS)-aware proportional fairness (QPF) packet-scheduling policy with low complexity for the downlink of multiuser OFDM systems to allocate radio resources among users. Our proposed algorithm is based on a cross-layer design in that the scheduler is aware of both the channel (i.e., physical layer) and the queue state (i.e., data link layer) information to achieve proportional fairness while maximizing each users packet-level QoS performance. The simulation results show that the proposed QPF algorithm is efficient in terms of average system throughput, packet-dropping probability, and packet delay, while maintaining adequate fairness among users with relatively low scheduling overhead.

Mechanism Design for Stochastic Virtual Resource Allocation in Non-cooperative Cloud Systems

Currently, virtualization technology has been widely adopted by cloud service providers to provide flexible and cost-effective resource sharing among users. On cloud platforms, computing resources are allocated on-demand dynamically and the application hosted on a virtual machine(VM) usually has the illusion of complete control of resources. Thus, a selfish VM may strategically compete for resource with other VMs to maximize its own benefit while at the cost of overall system performance. This problem poses new challenges to cloud providers, who must thwart non-cooperative behavior as well as allocating resource among selfish VMs efficiently. In this paper, we propose to utilize mechanism design to allocate resource among selfish VMs in a non-cooperative cloud environment. Because the accurate relationship between VMs valuation function and allocated resource may not be available in practice and the valuation function parameters may not noise free, we also propose to apply stochastic approximation methods to get stochastic solution for allocation and payment outcomes. We show through theoretical analysis and simulations that the proposed stochastic mechanism is efficient and incentive compatible. That is, the incorporation of mechanism design for virtualized resource allocation is able to enforce cooperation and achieve efficient resource utilization among selfish VMs in non-cooperative cloud systems.

eBase: A baseband unit cluster testbed to improve energy-efficiency for cloud radio access network

Recently, power consumption of radio access networks (RAN) has attracted a lot of attention since energy cost takes up a vast portion of operational expenditure (OPEX). Specifically, more than half of the energy is consumed by base stations (BS). Baseband Unit (BBU), which is responsible for baseband signal processing, is an important part of BS, and BBU consolidation in the form of a cluster is an promising solution to enhance energy efficiency. Although there are several existing work addressing similar ideas from theoretical perspective, there is still a gap between theoretical and practical solutions. Hence, by leveraging cloud computing and software-defined radio technologies, we develop a BBU cluster testbed, eBase, to consolidates multiple isolated BBUs into a virtualized BBU and then provide unified baseband resource pool for RAN. We present the architecture and implementation of eBase in detail. We also design a distributed resource management middleware to realize comprehensive resource management strategy for BBU cluster in order to improve energy efficiency. Through experiments, we find eBase can reduce total energy consumption by about 20% while satisfying about 95% QoS. These results not only demonstrate BBU clusters significant capability to reduce energy cost and improve resource utilization, but also show eBase is a capable prototyping testbed for cloud radio access network research.

A New Cross Layer Approach to QoS-Aware Proportional Fairness Packet Scheduling in the Downlink of OFDM Wireless Systems

OFDM systems are the major cellular platforms for supporting ubiquitous high performance mobile applications. However, there remain a number of research challenges to be tackled. One of the most important challenges is the design of a judicious packet scheduler so as to make efficient use of the spectrum bandwidth. In this paper, we propose a new QoS-aware proportional fairness (QPF) packet scheduling policy for the downlink of multiuser OFDM systems to allocate radio resource among users. Our proposed algorithm is based on a cross layer design in that the scheduler is aware of both channel and queue state information to achieve proportional fairness while improving each users QoS performance. Simulation results indicate that the proposed QPF algorithm is efficient in terms of average system throughput, packet dropping probability, and packet delay, while maintaining adequate fairness among users.

On the Impact of Selfish Behaviors in Wireless Packet Scheduling

In many practical scenarios, wireless devices are autonomous and thus, may exhibit non-cooperative behaviors due to self-interests. For instance, a wireless user may report bogus channel information to gain resource allocation advantages. Such non-cooperative behaviors are practicable as the devices software could be modified by the user. In this paper, we first analyze the impact of these rationally selfish behaviors on the performance of packet scheduling algorithms in time-slotted wireless networks. Using a mixed strategy game theoretic model, we show that the traditional Maximum Rate packet scheduling algorithm can lead non-cooperative users to undesirable Nash equilibriums, in which the wireless channels are used inefficiently. By using repeated game to enforce cooperation, we further propose a novel game theoretic approach that can lead to an efficient equilibrium.

Efficient wireless packet scheduling in a non-cooperative environment: Game theoretic analysis and algorithms

In many practical scenarios, wireless devices are autonomous and thus, may exhibit non-cooperative behaviors due to self-interests. For instance, a wireless cellular device may be programmed to report bogus channel information to gain resource allocation advantages. Such non-cooperative behaviors are highly probable as the devices software can be modified by the user. In this paper, we first analyze the impact of these rationally selfish behaviors on the performance of packet scheduling algorithms in time-slotted wireless networks. Using a mixed strategy game model, we show that the traditional maximum rate packet scheduling algorithm can cause non-cooperative devices to converge to highly inefficient Nash equilibria, in which the wireless channel resources are significantly wasted. By using a repeated game to enforce cooperation, we further propose a novel game theoretic algorithm that can lead to an efficient equilibrium.

Game Theoretic Packet Scheduling to Combat Non-Cooperativeness in Wireless Mesh Networks

In many practical scenarios, wireless mesh clients are autonomous and thus, may exhibit non-cooperative behaviors due to self-interests. For instance, a client may report bogus channel information to a mesh router in order to gain resource allocation advantages. Such non-cooperative behaviors are practicable as the client devices software could be modified by the user. In this paper, we analyze the impact of these rationally selfish and non-cooperative behaviors on the performance of packet scheduling algorithms in wireless mesh networks. Using a mixed strategy game theoretic model, we found that the traditional rate maximizing packet scheduling algorithms can lead non-cooperative clients to an undesirable Nash equilibrium, in which the wireless channel is used inefficiently. Motivated by this observation, we propose a novel repeated game theoretic approach to optimize packet scheduling and achieve efficient equilibria.

Auction-Based Scheduling in Non-Cooperative Multiuser OFDM Systems

We study the problem of achieving proportional fair resource allocation in a non-cooperative multiuser OFDM network. We propose an auction-based scheduling algorithm, which combines the merits of the VCG auction and the greedy MC PF algorithm, to ensure that wireless users truthfully declare their resource requirements even though the users are inherently selfish. Through simulations, we find that users lying about their resource requirements are severely penalized by very high payments so that they should rather declare true valuations of subcarriers to the scheduler. Thus, the proposed auction-based scheduling algorithm can be used efficiently in a non-cooperative situation to realize proportional fairness.

GreenBase: An energy-efficient middleware for baseband units in radio access networks

Recently, power consumption of radio access networks (RAN) has attracted a lot of attention since energy cost takes up a vast portion of operational expenditure (OPEX). Specifically, more than half of the energy is consumed by base stations (BS). Baseband Unit (BBU), which is responsible for baseband signal processing, is an important part of BS but still lacks effective power management solutions to improve energy efficiency. We present a power management middleware, GreenBase, to improve energy efficiency for BBUs. GreenBase consists of a software-based power metering tool, power and performance monitors as well as managers, an extensible power management policy library, and an energy efficiency analyzer. To evaluate this middleware, we construct a BBU testbed running video streaming applications based on software-defined radio platform GNU Radio/USRP. The experimental results validate GreenBase can achieve power and performance target with integrated power management policies. In particular, we find GreenBase can reduce total energy consumption by about 13% while satisfying target statistic QoS using a stochastic QoS controller.

VCG-Based Time-Slot Auctioning in IEEE 802.16 OFDM/TDMA Wireless Mesh Networks

In this paper, we study the problem of bandwidth resource allocation in a non-cooperative IEEE 802.16 OFDM/TDMA based wireless mesh network, and propose an auction based framework in which the gateway, equipped with the precious high speed Internet connection, serves as the auctioneer while the first-level mesh routers (MRs) (i.e., those with direct wireless connections to the gateway) act as bidders competing resources among each other. We then present Vickrey-Clarke-Groves (VCG) based auction approaches to allocate time-slots among MRs. Through simulations, we find that the proposed VCG algorithms can achieve much better throughput and connection blocking probability performance than traditional resource allocation approaches in a non-cooperative environment.