37 research outputs found
Joint Congestion Control and Scheduling in Wireless Networks with Network Coding
published_or_final_versio
Resource Allocation in Relay Enhanced Broadband Wireless Access Networks
The use of relay nodes to improve the performance of broadband wireless access (BWA) networks has been the subject of intense research activities in recent years. Relay enhanced BWA networks are anticipated to support multimedia traffic (i.e., voice,
video, and data traffic). In order to guarantee service to network users, efficient resource distribution is imperative. Wireless multihop networks are characterized by two inherent dynamic characteristics: 1) the existence of wireless interference and 2) mobility of user nodes. Both mobility and interference greatly influence the ability of users to obtain the necessary resources for service. In this dissertation we conduct a comprehensive research study on the topic of resource allocation in the presence of interference and mobility. Specifically, this dissertation investigates the impact interference and mobility have on various aspects of resource allocation, ranging from fairness to spectrum utilization. We study four important resource allocation algorithms for relay enhanced BWA networks. The problems and our research achievements are briefly outlined as follows.
First, we propose an interference aware rate adaptive subcarrier and power allocation
algorithm using maximum multicommodity
flow optimization. We consider the impact of
the wireless interference constraints using Signal to Interference Noise Ratio (SINR). We
exploit spatial reuse to allocate subcarriers in the network and show that an intelligent
reuse of resources can improve throughput while mitigating the impact of interference.
We provide a sub-optimal heuristic to solve the rate adaptive resource allocation problem. We demonstrate that aggressive spatial reuse and fine tuned-interference modeling garner advantages in terms of throughput, end-to-end delay and power distribution.
Second, we investigate the benefits of decoupled optimization of interference aware
routing and scheduling using SINR and spatial reuse to improve the overall achievable
throughput. We model the routing optimization problem as a linear program using maximum concurrent flows. We develop an optimization formulation to schedule the link traffic such that interference is mitigated and time slots are reused appropriately based on spatial TDMA (STDMA). The scheduling problem is shown to be NP-hard and is solved using the column generation technique. We compare our formulations to conventional counterparts in the literature and show that our approach guarantees higher throughput by mitigating the effect of interference effectively.
Third, we investigate the problem of multipath flow routing and fair bandwidth allocation under interference constraints for multihop wireless networks. We first develop a novel isotonic routing metric, RI3M, considering the influence of interflow and intraflow interference. Second, in order to ensure QoS, an interference-aware max-min fair bandwidth allocation algorithm, LMX:M3F, is proposed where the lexicographically largest bandwidth allocation vector is found among all optimal allocation vectors while considering constraints of interference on the flows. We compare with various interference based routing metrics and interference aware bandwidth allocation algorithms established in the literature to show that RI3M and LMX:M3F succeed in improving network performance in terms of delay, packet loss ratio and bandwidth usage.
Lastly, we develop a user mobility prediction model using the Hidden Markov Model(HMM) in which prediction control is transferred to the various fixed relay nodes in the
network. Given the HMM prediction model, we develop a routing protocol which uses
the location information of the mobile user to determine the interference level on links
in its surrounding neighborhood. We use SINR as the routing metric to calculate the
interference on a specific link (link cost). We minimize the total cost of routing as a
cost function of SINR while guaranteeing that the load on each link does not exceed
its capacity. The routing protocol is formulated and solved as a minimum cost
flow optimization problem. We compare our SINR based routing algorithm with conventional counterparts in the literature and show that our algorithm reinforces routing paths with high link quality and low latency, therefore improving overall system throughput.
The research solutions obtained in this dissertation improve the service reliability and QoS assurance of emerging BWA networks
Optimal Joint Routing and Scheduling in Millimeter-Wave Cellular Networks
Millimeter-wave (mmWave) communication is a promising technology to cope with
the expected exponential increase in data traffic in 5G networks. mmWave
networks typically require a very dense deployment of mmWave base stations
(mmBS). To reduce cost and increase flexibility, wireless backhauling is needed
to connect the mmBSs. The characteristics of mmWave communication, and
specifically its high directional- ity, imply new requirements for efficient
routing and scheduling paradigms. We propose an efficient scheduling method,
so-called schedule-oriented optimization, based on matching theory that
optimizes QoS metrics jointly with routing. It is capable of solving any
scheduling problem that can be formulated as a linear program whose variables
are link times and QoS metrics. As an example of the schedule-oriented
optimization, we show the optimal solution of the maximum throughput fair
scheduling (MTFS). Practically, the optimal scheduling can be obtained even for
networks with over 200 mmBSs. To further increase the runtime performance, we
propose an efficient edge-coloring based approximation algorithm with provable
performance bound. It achieves over 80% of the optimal max-min throughput and
runs 5 to 100 times faster than the optimal algorithm in practice. Finally, we
extend the optimal and approximation algorithms for the cases of multi-RF-chain
mmBSs and integrated backhaul and access networks.Comment: To appear in Proceedings of INFOCOM '1
Dynamic Retransmission Limit Scheme in MAC Layer for Routing in Multihop Ad hoc Networks
We consider a wireless ad hoc network with random
access channel. We present a model that takes into account topology, routing, random access in MAC layer, and forwarding probability. In this paper, we focus on drawing benefit from the interaction of the MAC (governed by IEEE 802.11 or slotted Aloha) and routing by defining a new cross-layer scheme for routing based on the limit number of retransmission.
By adjusting dynamically and judiciously this parameter in a saturated network, we have
realized that both stability of forwarding queues and average throughput are significantly improved in linear networks with symmetric traffic: a gain of 100% can be reached. While in asymmetric topology network with asymmetric traffic, we achieve a better average delay (resp., throughput) for each connection without changing the average throughput (resp.,
delay). In addition, we show the efficiency of our new scheme in case of multimedia applications with delay constraint. A detailed performance study is presented using analytical and simulation evaluation
Centralized Rate Allocation and Control in 802.11-based Wireless Mesh Networks
Wireless Mesh Networks (WMNs) built with commodity 802.11 radios are a cost-effective means of providing last mile broadband Internet access. Their multihop architecture allows for rapid deployment and organic growth of these networks.
802.11 radios are an important building block in WMNs. These low cost radios are readily available, and can be used globally in license-exempt frequency bands. However, the 802.11 Distributed Coordination Function (DCF) medium access mechanism does not scale well in large multihop networks. This produces suboptimal behavior in many transport protocols, including TCP, the dominant transport protocol in the Internet. In particular, cross-layer interaction between DCF and TCP results in flow level unfairness, including starvation, with backlogged traffic sources. Solutions found in the literature propose distributed source rate control algorithms to alleviate this problem. However, this requires MAC-layer or transport-layer changes on all mesh routers. This is often infeasible in practical deployments.
In wireline networks, router-assisted rate control techniques have been proposed for use alongside end-to-end mechanisms. We evaluate the feasibility of establishing similar centralized control via gateway mesh routers in WMNs. We find that commonly used router-assisted flow control schemes designed for wired networks fail in WMNs. This is because they assume that: (1) links can be scheduled independently, and (2) router queue buildups are sufficient for detecting congestion. These abstractions do not hold in a wireless network, rendering wired scheduling algorithms such as Fair Queueing (and its variants) and Active Queue Management (AQM) techniques ineffective as a gateway-enforceable solution in a WMN. We show that only non-work-conserving rate-based scheduling can effectively enforce rate allocation via a single centralized traffic-aggregation point.
In this context we propose, design, and evaluate a framework of centralized, measurement-based, feedback-driven mechanisms that can enforce a rate allocation policy objective for adaptive traffic streams in a WMN. In this dissertation we focus on fair rate allocation requirements. Our approach does not require any changes to individual mesh routers. Further, it uses existing data traffic as capacity probes, thus incurring a zero control traffic overhead. We propose two mechanisms based on this approach: aggregate rate control (ARC) and per-flow rate control (PFRC). ARC limits the aggregate capacity of a network to the sum of fair rates for a given set of flows. We show that the resulting rate allocation achieved by DCF is approximately max-min fair. PFRC allows us to exercise finer-grained control over the rate allocation process. We show how it can be used to achieve weighted flow rate fairness. We evaluate the performance of these mechanisms using simulations as well as implementation on a multihop wireless testbed. Our comparative analysis show that our mechanisms improve fairness indices by a factor of 2 to 3 when compared with networks without any rate limiting, and are approximately equivalent to results achieved with distributed source rate limiting mechanisms that require software modifications on all mesh routers
Resource Management in Cloud-based Radio Access Networks: a Distributed Optimization Perspective
University of Minnesota Ph.D. dissertation. 2015. Major: Electrical Engineering. Advisor: Zhi-Quan Luo. 1 computer file (PDF); ix, 136 pages.In this dissertation, we consider the base station (BS) and the resource management problems for the cloud-based radio access network (C-RAN). The main difference of the envisioned future 5G network architecture is the adoption of multi-tier BSs to extend the coverage of the existing cellular BSs. Each of the BS is connected to the multi-hop backhaul network with limited bandwidth. For provisioning the network, the cloud centers have been proposed to serve as the control centers. These differences give rise to many practical challenges. The main focus of this dissertation is the distributed strategy across the cloud centers. First, we show that by jointly optimizing the transceivers and determining the active set of BSs, high system resource utilization can be achieved with only a small number of BSs. In particular, we provide efficient distributed algorithms for such joint optimization problem, under the following two common design criteria: i) minimization of the total power consumption at the BSs, and ii) maximization of the system spectrum efficiency. In both cases, we introduce a nonsmooth regularizer to facilitate the activation of the most appropriate BSs, and the algorithms are, respectively, developed with Alternating Direction Method of Multipliers (ADMM) and weighted minimum mean square error (WMMSE) algorithm. In the second part, we further explicitly consider the backhaul limitation issues. We propose an efficient algorithm for joint resource allocation across the wireless links and the flow control over the entire network. The algorithm, which maximizes the utility function of the rates among all the transmitted commodities, is based on a decomposition approach leverages both the ADMM and the WMMSE algorithms. This algorithm is shown to be easily parallelizable within cloud centers and converges globally to a stationary solution. Lastly, since ADMM has been popular for solving large-scale distributed convex optimization, we further consider the issues of the network synchronization across the cloud centers. We propose an ADMM-type implementation that can handle a specific form of asynchronism based on the so-called BSUM-M algorithm, a new variant of ADMM. We show that the proposed algorithm converges to the global optimal solution
QoS Routing in Wireless Mesh Networks
Wireless Mesh Networking is envisioned as an economically viable paradigm and a promising technology in providing wireless broadband services. The wireless mesh backbone consists of fixed mesh routers that interconnect different mesh clients to themselves and to the wireline backbone network. In order to approach the wireline servicing level and provide same or near QoS guarantees to different traffic flows, the wireless mesh backbone should be quality-of-service (QoS) aware. A key factor in designing protocols for a wireless mesh network (WMN) is to exploit its distinct characteristics, mainly immobility of mesh routers and less-constrained power consumption.
In this work, we study the effect of varying the transmission power to achieve the required signal-to-interference noise ratio for each link and, at the same time, to maximize the number of simultaneously active links. We propose a QoS-aware routing framework by using transmission power control. The framework addresses both the link scheduling and QoS routing problems with a cross-layer design taking into consideration the spatial reuse of the network bandwidth. We formulate an optimization problem to find the optimal link schedule and use it as a fitness function in a genetic algorithm to find candidate routes. Using computer simulations, we show that by optimal power allocation the QoS constraints for the different traffic flows are met with more efficient bandwidth utilization than the minimum power allocations