Mustafa Y. Arslan

FluidNet: a flexible cloud-based radio access network for small cells

Cloud-based radio access networks (C-RAN) have been proposed as a cost-efficient way of deploying small cells. Unlike conventional RANs, a C-RAN decouples the baseband processing unit (BBU) from the remote radio head (RRH), allowing for centralized operation of BBUs and scalable deployment of light-weight RRHs as small cells. In this work, we argue that the intelligent configuration of the front-haul network between the BBUs and RRHs, is essential in delivering the performance and energy benefits to the RAN and the BBU pool, respectively. We propose FluidNet-a scalable, light-weight framework for realizing the full potential of C-RAN. FluidNet deploys a logically re-configurable front-haul to apply appropriate transmission strategies in different parts of the network and hence cater effectively to both heterogeneous user profiles and dynamic traffic load patterns. FluidNets algorithms determine configurations that maximize the traffic demand satisfied on the RAN, while simultaneously optimizing the compute resource usage in the BBU pool. We prototype FluidNet on a 6 BBU, 6 RRH WiMAX C-RAN testbed. Prototype evaluations and large-scale simulations reveal that FluidNets ability to re-configure its front-haul and tailor transmission strategies provides a 50% improvement in satisfying traffic demands, while reducing the compute resource usage in the BBU pool by 50% compared to baseline schemes.

FERMI: a femtocell resource management system forinterference mitigation in OFDMA networks

The demand for increased spectral efficiencies is driving the next generation broadband access networks towards deploying smaller cells (femtocells) with sophisticated air interface technologies (Orthogonal Frequency Division Multiple Access or OFDMA). The projected dense deployment of femtocells however, makes interference and hence resource management both critical and extremely challenging. In this paper, we design and implement one of the first resource management systems, FERMI, for OFDMA-based femtocell networks. As part of its design, FERMI (i) provides resource isolation in the frequency domain (as opposed to time) to leverage power pooling across cells to improve capacity; (ii) uses measurement-driven triggers to intelligently distinguish clients that require just link adaptation from those that require resource isolation; (iii) incorporates mechanisms that enable the joint scheduling of both types of clients in the same frame; and (iv) employs efficient, scalable algorithms to determine a fair resource allocation across the entire network with high utilization and low overhead. We implement FERMI on a prototype four-cell WiMAX femtocell testbed and show that it yields significant gains over conventional approaches.

Software-defined networking in cellular radio access networks: potential and challenges

Software-defined networking has brought both performance and management benefits to wired networks. It is natural to wonder if SDN principles also apply and can deliver similar benefits to RANs. It is this question that we intend to address in this article. We first highlight that the core SDN principle of decoupling control and data planes already exists in RANs in the form of self-organizing networking solutions, which can optimize RAN performance at coarse timescales. In addition to control/data plane separation, we also elaborate how fine timescale optimizations such as coordinated multi-point transmission are made practical with the help of cloud RANs (C-RANS), which offer the notion of processing decoupled from transmission within the data plane. We finally discuss the potential and challenges related to a less explored application of SDN in the RAN, which is programming the fronthaul network in a C-RAN. We argue that this novel notion of software-defined fronthaul, SDF, has the power to orchestrate novel applications and thus should be a key area of focus in RAN optimization.

A practical traffic management system for integrated LTE-WiFi networks

Mobile operators are leveraging WiFi to relieve the pressure posed on their networks by the surging bandwidth demand of applications. However, operators often lack intelligent mechanisms to control the way users access their WiFi networks. This lack of sophisticated control creates poor network utilization, which in turn degrades the quality of experience (QoE). To meet user traffic demands, it is evident that operators need solutions that optimally balance user traffic across cellular and WiFi networks. Motivated by the lack of practical solutions in this space, we design and implement ATOM - an end-to-end system for adaptive traffic offloading for WiFi-LTE deployments. ATOM has two novel components: (i) A network interface selection algorithm that maps user traffic across WiFi and LTE to optimize user QoE and (ii) an interface switching service that seamlessly re-directs ongoing user sessions in a cost-effective and standards-compatible manner. Our evaluations on a real LTE-WiFi testbed using YouTube traffic reveals that ATOM reduces video stalls by 3-4 times compared to naive solutions.

Computing while charging: building a distributed computing infrastructure using smartphones

Every night, a large number of idle smartphones are plugged into a power source for recharging the battery. Given the increasing computing capabilities of smartphones, these idle phones constitute a sizeable computing infrastructure. Therefore, for an enterprise which supplies its employees with smartphones, we argue that a computing infrastructure that leverages idle smartphones being charged overnight is an energy-efficient and cost-effective alternative to running tasks on traditional server infrastructure. While parallel execution and scheduling models exist for servers (e.g., MapReduce), smartphones present a unique set of technical challenges due to the heterogeneity in CPU clock speed, variability in network bandwidth, and lower availability compared to servers. In this paper, we address many of these challenges to develop CWC---a distributed computing infrastructure using smartphones. Specifically, our contributions are: (i) we profile the charging behaviors of real phone owners to show the viability of our approach, (ii) we enable programmers to execute parallelizable tasks on smartphones with little effort, (iii) we develop a simple task migration model to resume interrupted task executions, and (iv) we implement and evaluate a prototype of CWC (with 18 Android smartphones) that employs an underlying novel scheduling algorithm to minimize the makespan of a set of tasks. Our extensive evaluations demonstrate that the performance of our approach makes our vision viable. Further, we explicitly evaluate the performance of CWCs scheduling component to demonstrate its efficacy compared to other possible approaches.

A resource management system for interference mitigation in enterprise OFDMA femtocells

To meet the capacity demands from ever-increasing mobile data usage, mobile network operators are moving toward smaller cell structures. These small cells, called femtocells, use sophisticated air interface technologies such as orthogonal frequency division multiple access (OFDMA). While femtocells are expected to provide numerous benefits such as energy efficiency and better throughput, the interference resulting from their dense deployments prevents such benefits from being harnessed in practice. Thus, there is an evident need for a resource management solution to mitigate the interference that occurs between collocated femtocells. In this paper, we design and implement one of the first resource management systems, FERMI, for OFDMA-based femtocell networks. As part of its design, FERMI: 1) provides resource isolation in the frequency domain (as opposed to time) to leverage power pooling across cells to improve capacity; 2) uses measurement-driven triggers to intelligently distinguish clients that require just link adaptation from those that require resource isolation; 3) incorporates mechanisms that enable the joint scheduling of both types of clients in the same frame; and 4) employs efficient, scalable algorithms to determine a fair resource allocation across the entire network with high utilization and low overhead. We implement FERMI on a prototype four-cell WiMAX femtocell testbed and show that it yields significant gains over conventional approaches.

Auto-configuration of 802.11n WLANs

Channel Bonding (CB) combines two adjacent frequency bands to form a new, wider band to facilitate high data rate transmissions in MIMO-based 802.11n networks. However, the use of a wider band with CB can exacerbate interference effects. Furthermore, CB does not always provide benefits in interference-free settings, and can even degrade performance in some cases. We conduct an in-depth, experimental study to understand the implications of CB. Based on this study we design an auto-configuration framework, ACORN, for enterprise 802.11n WLANs. ACORN integrates the functions of user association and channel allocation, since our study reveals that they are tightly coupled when CB is used. We show that the channel allocation problem with the constraints of CB is NP-complete. Thus, ACORN uses an algorithm that provides a worst case approximation ratio of [EQUATION] with Δ being the maximum node degree in the network. We implement ACORN on our 802.11n testbed. Our experiments show that ACORN (i) outperforms previous approaches that are agnostic to CB constraints; it provides per-AP throughput gains from 1.5x to 6x and (ii) in practice, its channel allocation module achieves an approximation ratio much better than [EQUATION].

A distributed resource management framework for interference mitigation in OFDMA femtocell networks

Next generation wireless networks (i.e., WiMAX, LTE) provide higher bandwidth and spectrum efficiency leveraging smaller (femto) cells with orthogonal frequency division multiple access (OFDMA). The uncoordinated, dense deployments of femtocells however, pose several unique challenges relating to interference and resource management in these networks. Towards addressing these challenges, we propose RADION, a distributed resource management framework that effectively manages interference across femtocells. RADIONs core building blocks enable femtocells to opportunistically find the available resources in a completely distributed and efficient manner. Further, RADIONs modular nature paves the way for different resource management solutions to be incorporated in the framework. We implement RADION on a real WiMAX femtocell testbed deployed in a typical indoor setting. We extensively evaluate two solutions integrated with RADION, both via prototype implementation and simulations and quantify their performance in terms of quick and efficient self-organization.

ACORN: an auto-configuration framework for 802.11n WLANs

The wide channels feature combines two adjacent channels to form a new, wider channel to facilitate high-data-rate transmissions in multiple-input-multiple-output (MIMO)-based IEEE 802.11n networks. Using a wider channel can exacerbate interference effects. Furthermore, contrary to what has been reported by prior studies, we find that wide channels do not always provide benefits in isolation (i.e., one link without interference) and can even degrade performance. We conduct an in-depth, experimental study to understand the implications of wide channels on throughput performance. Based on our measurements, we design an auto-configuration framework called ACORN for enterprise 802.11n WLANs. ACORN integrates the functions of user association and channel allocation since our study reveals that they are tightly coupled when wide channels are used. We show that the channel allocation problem with the constraints of wide channels is NP-complete. Thus, ACORN uses an algorithm that provides a worst-case approximation ratio of O(1/Δ + 1), with Δ being the maximum node degree in the network. We implement ACORN on our 802.11n testbed. Our evaluations show that ACORN: 1) outperforms previous approaches that are agnostic to wide channels constraints; it provides per-AP throughput gains ranging from 1.5 × 6×; and 2) in practice, its channel allocation module achieves an approximation ratio much better than the theoretically predicted O(1/Δ + 1).

Exploiting Cell Dormancy and Load Balancing in LTE HetNets: Optimizing the Proportional Fairness Utility

We consider the problem of maximizing the proportional fairness (PF) utility over heterogeneous wireless networks (HetNets) by jointly exploiting cell dormancy (cell ON-OFF) - wherein some transmission nodes from a set of interest are made inactive - and load balancing (user association) - wherein users are associated to the active transmission nodes in that set with each user being associated with only one node. We establish that this joint optimization problem which is a discrete optimization problem, is strongly NP-hard. Nevertheless, we prove that the load balancing sub-problem for any given set of active transmission nodes is not NP-hard but instead can be re-formulated as an asymmetric assignment problem and hence can be optimally solved in an efficient manner. In addition, we propose another lower complexity greedy algorithm for the load balancing sub-problem which offers a near-optimal average-case performance and a worst-case performance guarantee. We then propose a low-complexity algorithm for the joint optimization problem. Simulations over an example LTE HetNet topology reveal the superior performance of the proposed algorithms and underscore the significant benefits of jointly exploiting cell dormancy and load balancing.