851 research outputs found

    Scheduling with Rate Adaptation under Incomplete Knowledge of Channel/Estimator Statistics

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    In time-varying wireless networks, the states of the communication channels are subject to random variations, and hence need to be estimated for efficient rate adaptation and scheduling. The estimation mechanism possesses inaccuracies that need to be tackled in a probabilistic framework. In this work, we study scheduling with rate adaptation in single-hop queueing networks under two levels of channel uncertainty: when the channel estimates are inaccurate but complete knowledge of the channel/estimator joint statistics is available at the scheduler; and when the knowledge of the joint statistics is incomplete. In the former case, we characterize the network stability region and show that a maximum-weight type scheduling policy is throughput-optimal. In the latter case, we propose a joint channel statistics learning - scheduling policy. With an associated trade-off in average packet delay and convergence time, the proposed policy has a stability region arbitrarily close to the stability region of the network under full knowledge of channel/estimator joint statistics.Comment: 48th Allerton Conference on Communication, Control, and Computing, Monticello, IL, Sept. 201

    pDCell: an End-to-End Transport Protocol for Mobile Edge Computing Architectures

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    Pendiente publicación 2019To deal with increasingly demanding services and the rapid growth in number of devices and traffic, 5G and beyond mobile networks need to provide extreme capacity and peak data rates at very low latencies. Consequently, applications and services need to move closer to the users into so-called edge data centers. At the same time, there is a trend to virtualize core and radio access network functionalities and bring them to edge data centers as well. However, as is known from conventional data centers, legacy transport protocols such as TCP are vastly suboptimal in such a setting. In this work, we present pDCell, a transport design for mobile edge computing architectures that extends data center transport approaches to the mobile network domain. Specifically, pDCell ensures that data traffic from application servers arrives at virtual radio functions (i.e., C-RAN Central Units) timely to (i) minimize queuing delays and (ii) to maximize cellular network utilization. We show that pDCell significantly improves flow completion times compared to conventional transport protocols like TCP and data center transport solutions, and is thus an essential component for future mobile networks.This work is partially supported by the European Research Council grant ERC CoG 617721, the Ramon y Cajal grant from the Spanish Ministry of Economy and Competitiveness RYC-2012-10788, by the European Union H2020-ICT grant 644399 (MONROE), by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant num. 761586) and the Madrid Regional Government through the TIGRE5-CM program (S2013/ICE-2919). Further, the work of Dr. Kogan is partially supported by a grant from the Cisco University Research Program Fund, an advised fund of Silicon Valley Community Foundation.No publicad

    Delay Optimal Server Assignment to Symmetric Parallel Queues with Random Connectivities

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    In this paper, we investigate the problem of assignment of KK identical servers to a set of NN parallel queues in a time slotted queueing system. The connectivity of each queue to each server is randomly changing with time; each server can serve at most one queue and each queue can be served by at most one server per time slot. Such queueing systems were widely applied in modeling the scheduling (or resource allocation) problem in wireless networks. It has been previously proven that Maximum Weighted Matching (MWM) is a throughput optimal server assignment policy for such queueing systems. In this paper, we prove that for a symmetric system with i.i.d. Bernoulli packet arrivals and connectivities, MWM minimizes, in stochastic ordering sense, a broad range of cost functions of the queue lengths including total queue occupancy (or equivalently average queueing delay).Comment: 6 pages, 4 figures, Proc. IEEE CDC-ECC 201

    Click on a Cluster: A Viable Approach to Scale Software-Based Routers

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    A Lightweight, Non-intrusive Approach for Orchestrating Autonomously-managed Network Elements

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    Software-Defined Networking enables the centralized orchestration of data traffic within a network. However, proposed solutions require a high degree of architectural penetration. The present study targets the orchestration of network elements that do not wish to yield much of their internal operations to an external controller. Backpressure routing principles are used for deriving flow routing rules that optimally stabilize a network, while maximizing its throughput. The elements can then accept in full, partially or reject the proposed routing rule-set. The proposed scheme requires minimal, relatively infrequent interaction with a controller, limiting its imposed workload, promoting scalability. The proposed scheme exhibits attracting network performance gains, as demonstrated by extensive simulations and proven via mathematical analysis.Comment: 6 pages 7, figures, IEEE ISCC'1

    Dynamic Server Allocation over Time Varying Channels with Switchover Delay

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    We consider a dynamic server allocation problem over parallel queues with randomly varying connectivity and server switchover delay between the queues. At each time slot the server decides either to stay with the current queue or switch to another queue based on the current connectivity and the queue length information. Switchover delay occurs in many telecommunications applications and is a new modeling component of this problem that has not been previously addressed. We show that the simultaneous presence of randomly varying connectivity and switchover delay changes the system stability region and the structure of optimal policies. In the first part of the paper, we consider a system of two parallel queues, and develop a novel approach to explicitly characterize the stability region of the system using state-action frequencies which are stationary solutions to a Markov Decision Process (MDP) formulation. We then develop a frame-based dynamic control (FBDC) policy, based on the state-action frequencies, and show that it is throughput-optimal asymptotically in the frame length. The FBDC policy is applicable to a broad class of network control systems and provides a new framework for developing throughput-optimal network control policies using state-action frequencies. Furthermore, we develop simple Myopic policies that provably achieve more than 90% of the stability region. In the second part of the paper, we extend our results to systems with an arbitrary but finite number of queues.Comment: 38 Pages, 18 figures. arXiv admin note: substantial text overlap with arXiv:1008.234

    Energy Efficient Reduced Complexity Multi-Service, Multi-Channel Scheduling Techniques

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    The need for energy efficient communications is essential in current and next-generation wireless communications systems. A large component of energy expenditure in mobile devices is in the mobile radio interface. Proper scheduling and resource allocation techniques that exploit instantaneous and long-term average knowledge of the channel, queue state and quality of service parameters can be used to improve the energy efficiency of communication. This thesis focuses on exploiting queue and channel state information as well as quality of service parameters in order to design energy efficient scheduling techniques. The proposed designs are for multi-stream, multi-channel systems and in general have high computational complexity. The large contributions of this thesis are in both the design of optimal/near-optimal scheduling/resource allocation schemes for these systems as well as proposing complexity reduction methods in their design. Methods are proposed for both a MIMO downlink system as well as an LTE uplink system. The effect of power efficiency on quality of service parameters is well studied as well as complexity/efficiency comparisons between optimal/near optimal allocation
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