487 research outputs found
Energy-Aware Base Stations: The Effect of Planning, Management, and Femto Layers
No full textWe compare the performance of three base station management schemes on three different network topologies. In addition, we explore the effect of offloading traffic to heterogeneous femtocell layer upon energy savings taking into account the increase of base station switch-off time intervals. Fairness between mobile operator and femtocell owners is maintained since current femtocell technologies present flat power consumption curves with respect to served traffic. We model two different user-to-femtocell association rules in order to capture realistic and maximum gains from the heterogeneous network. To provide accurate findings and a holistic overview of the techniques, we explore a real urban district where channel estimations and power control are modeled using deterministic algorithms. Finally, we explore energy efficiency metrics that capture savings in the mobile network operator, the required watts per user and watts per bitrate. It is found that the newly established pseudo distributed management scheme is the most preferable solution for practical implementations and together with the femotcell layer the network can handle dynamic load control that is regarded as the basic element of future demand response programs
Distributed dynamic scheduling for end-to-end rate guarantees in wireless ad hoc networks
No full textWe present a novel framework for the provision of deterministic end-to-end bandwidth guarantees in wireless ad hoc networks. Guided by a set of local feasibility conditions, multi-hop sessions are dynamically offered allocations, further translated to link demands. Using a distributed TDMA protocol, nodes adapt to the demand changes on their adjacent links by local, conflict-free slot reassignments. As soon as the changes stabilize, the nodes must incrementally converge to a TDMA schedule that realizes the global link (and session) demand allocation. We first identify an inherent trade-off between the degree of topology control and fraction of feasible allocations that can be captured by the local conditions. We show that tree topologies can be maximally utilized in this respect and that a converging distributed link scheduling algorithm exists in this case. Decoupling end-to-end bandwidth allocation from link scheduling allows support of various end-to-end QoS objectives. Focusing on Available Bit Rate (ABR) service, we design an asynchronous distributed algorithm for sharing bandwidth to the sessions in a maxmin fair (MMF) manner. Finally, we present the implementation of this framework over Bluetooth, an existing wireless technology that enables the formation of ad hoc networks. This implementation is free of the usual restrictive assumptions of previous TDMA approaches: it does not require any a-priori knowledge on the number of nodes in the network nor even network-wide slot synchronization
Approximation algorithms for data-intensive service chain embedding
No full textRecent advances in network virtualization and programmability enable innovative service models such as Service Chaining (SC), where flows can be steered through a pre-defined sequence of service functions deployed at different cloud locations. A key aspect dictating the performance and efficiency of a SC is its instantiation onto the physical infrastructure. While existing SC Embedding (SCE) algorithms can effectively address the instantiation of SCs consuming computation and communication resources, they lack efficient mechanisms to handle the increasing data-intensive nature of next-generation services. Differently from computation and communication resources, which are allocated in a dedicated per request manner, storage resources can be shared to satisfy multiple requests for the same data. To fill this gap, in this paper, we formulate the data-intensive SCE problem with the goal of minimizing storage, computation, and communication resource costs subject to resource capacity, service chaining, and data sharing constraints. Using a randomized rounding technique that exploits a novel data-aware linear programming decomposition procedure, we develop a multi-criteria approximation algorithm with provable performance guarantees. Evaluation results show that the proposed algorithm achieves near-optimal resource costs with up to 27.8% of the cost savings owed to the sharing of the data
Service placement and request routing in MEC networks with storage, computation, and communication constraints
No full textThe proliferation of innovative mobile services such as augmented reality, networked gaming, and autonomous driving has spurred a growing need for low-latency access to computing resources that cannot be met solely by existing centralized cloud systems. Mobile Edge Computing (MEC) is expected to be an effective solution to meet the demand for low-latency services by enabling the execution of computing tasks at the network edge, in proximity to the end-users. While a number of recent studies have addressed the problem of determining the execution of service tasks and the routing of user requests to corresponding edge servers, the focus has primarily been on the efficient utilization of computing resources, neglecting the fact that non-trivial amounts of data need to be pre-stored to enable service execution, and that many emerging services exhibit asymmetric bandwidth requirements. To fill this gap, we study the joint optimization of service placement and request routing in dense MEC networks with multidimensional constraints. We show that this problem generalizes several well-known placement and routing problems and propose an algorithm that achieves close-to-optimal performance using a randomized rounding technique. Evaluation results demonstrate that our approach can effectively utilize available storage, computation, and communication resources to maximize the number of requests served by low-latency edge cloud servers
Experimental evaluation of functional splits for 5G Cloud-RANs
No full textCentralized RAN processing has been identified as one of the major enablers for 5G mobile network access. By moving the baseband units (BBU) to the Cloud, multiple instances can be instantiated on the fly, serving several Remote Radio Head (RRH) units. The goal is to satisfy the existing demand of particular geographical areas, whereas drastically reducing the overall CAPEX and OPEX costs of the mobile operators. In this work, we present an experimental study of real Cloud-RAN deployments, with respect to different functional splits. We use as a reference architecture the 3GPP LTE stack, and argue about the functional split applicability in contemporary networks. We evaluate Layer 2 functional splits, that can be used for the convergence of multiple heterogeneous wireless technologies in an all-in-one unit. By deploying our approach in a real testbed setup, we extract the backhaul network transfer requirements for the different splits and present our experimental findings, compared with the respective simulation results. © 2017 IEEE
Energy-efficient planning and management of cellular networks
No full textWe study base stations energy-efficient management algorithms in a cellular access network taking into account different planning strategies. To provide energy savings, sleep modes are adopted at the Base Stations (BSs). We propose two switch-off strategies that are based either on the cell load or the BS coverage overlap. Our results show that energy savings between 10% and 30% can be achieved also for the deployment already planned to be energy-efficient, while even higher savings are achievable with the other deployments. Moreover, we find that both the proposed switch-off strategies obtain similar results, suggesting that the order at which the BSs are switched-off, and the set of BSs selected to be switched off, do not change significantly the average estimation of potential energy savings. Furthermore, on a realistic case study, comparisons are made between the results obtained by using deterministic channel estimation models and empirical formulations
Joint Service Placement and Request Routing in Multi-cell Mobile Edge Computing Networks
No full textAn overview of energy-efficient base station management techniques
No full textCellular networks have been traditionally dimensioned to fulfill the desired quality of service (QoS) requirements at all times, and consequently their deployment has been planned to meet the expected peak of the user demand. However, with the user demand recently increasing at exponential pace, concerns about the cellular networks energy consumption have been raised. In response, energy-efficient resource management schemes have been proposed, which take into account energy consumption, and control how much of the network infrastructure is actually needed at different times, and how much can be temporarily powered off to cut energy consumption. Since most of the energy consumed in cellular networks is used by base stations (BSs), algorithms for managing BSs seem to be the most urgent development to achieve energy-efficient operation. This paper provides a quick overview of the BS management techniques that were recently proposed for cellular networks. In addition, an outlook on real implementation aspects, including current commercial products, and trends in the development of energy-efficient hardware is also given
On emulating hardware/software co-designed control algorithms for packet switches
No full textHardware accelerators in networking systems for control algorithms offer a promising approach to scale performance. To that end, several research efforts have been devoted to verify a hardware version of complex control algorithms but only for small-scale hardware unit tests. In this paper we propose and evaluate an emulation framework, in which such control algorithm accelerators can be integrated to design a packet switch, able both to forward real traffic and to enable extensive experimental evaluation and demonstration scenarios. As a case study, we have integrated in the proposed framework a Belief-Propagation-driven algorithm accelerator for multicast packet scheduling. Copyright © 2014 ICST
Joint QoS Multicast Power / Admission Control and Base Station Assignment : A Geometric Programming Approach
No full textThe joint power control and base station (BS) assignment problem is considered under Quality-of-Service (QoS) constraints. If a feasible solution exists, the problem can be efficiently solved using existing distributed algorithms. Infeasibility is often encountered in practice, however, which brings up the issue of optimal admission control. The joint problem is NP-hard, yet important for QoS provisioning and bandwidth-efficient operation of existing and emerging cellular and overlay/underlay networks. Recognizing this, there have been several attempts to develop reasonable heuristics for joint admission and power control. This contribution takes a more disciplined approach. The joint problem is first concisely formulated as a constrained optimization problem, whose objective combines the BS assignment, admission, and power control components. The formulation also allows for multicasting. A geometric programming approximation is then developed, which forms the core of a heuristic, yet well-motivated centralized algorithm that generates approximate solutions to the original NP-hard problem. Numerical results against an enumeration baseline illustrate the merits of the approach.©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Eleftherios Karipidis, Nicholas Sidiropoulos and Leandros Tassiulas, Joint QoS Multicast Power / Admission Control and Base Station Assignment: A Geometric Programming Approach, 2008, Proceedings of the 5th IEEE Workshop on Sensor Array and Multi-Channel Signal Processing (SAM), 155-159.http://dx.doi.org/10.1109/SAM.2008.460684
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