Growing demand for data and increasing number of devices are drastically changing the scale of operation in mobile networks. Future services and business models require efficient provisioning with enhanced traffic management. It is hard to meet these requirements on today's mobile networks that are deployed over specialized hardware. While operators are keen to adopt NFV (Network Function Virtualization) to virtualize their networks, virtualized mobile network deployments face a few technical barriers. To address these challenges, we design SCOPE that effectively applies concepts from SDN and distributed systems to realize NFV-based LTE core networks. Using centralized allocation, SCOPE effectively manages the resources across multiple telecom data-centers in a way to meet the traffic requirements. To enforce the computed al- locations, SCOPE includes flexible and efficient mechanisms to configure the data-plane. With full compliance to 3GPP- based protocols, SCOPE ensures faster and cost-effective deployments. The efficacy of SCOPE is shown using a prototype implementation and large-scale simulations.

There is widespread agreement that future continuous interactive (CI) applications will require edge computing capabilities from mobile networks. There is also widespread expectation that the emerging 5G network architecture, with its constituent technology components, will be the context in which this will be realized. Indeed many of the components that will be part of such an environment have been studied in standalone manner. However, the question of whether an end-to-end combination of these components would satisfy application requirements, or indeed, how these components would be combined into service offerings by mobile network providers, have not been meaningfully addressed. Towards addressing these challenges, we propose ACACIA - a service abstraction framework that enables CI applications on edge clouds in mobile networks. Evaluation of our prototype implementation shows that our holistic approach provides a 70% end-to-end application level latency reduction when compared with existing cloud and mobile solutions.

We propose Acacia- a service abstraction framework that enables continuous interactive (CI) applications on edge clouds in mobile networks. We will demonstrate the Acacia architecture and illustrate its feasibility by using an augmented reality application as an example use case.

In addition to growth of data traffic, mobile networks are bracing for a significant rise in the control-plane signaling. While a complete re-design of the network to overcome inefficiencies may help alleviate the effects of signaling, our goal is to improve the design of the current platform to better manage the signaling. To meet our goal, we combine two key trends. Firstly, mobile operators are keen to transform their networks with the adoption of Network Function Virtualization (NFV) to ensure economies of scales. Secondly, growing popularity of cloud computing has led to advances in distributed systems. In bringing these trends together, we solve several challenges specific to the context of telecom networks. We present SCALE - A framework for effectively virtualizing the MME (Mobility Management Entity), a key control-plane element in LTE. SCALE is fully compatible with the 3GPP protocols, ensuring that it can be readily deployed in today's networks. SCALE enables (i) computational scaling with load and number of devices, and (ii) computational multiplexing across data centers, thereby reducing both, the latencies for control-plane processing, and the VM provisioning costs. Using an LTE prototype implementation and large-scale simulations, we show the efficacy of SCALE.

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.

With the growing demand for increased spectral efficiencies, there has been renewed interest in enabling full-duplex communications. However, existing approaches to enable full-duplex require a clean-slate approach to address the key challenge in full-duplex, namely self-interference suppression. This serves as a big deterrent to enabling full-duplex in existing cellular networks. Towards our vision of enabling full-duplex in legacy cellular, specifically LTE networks, with no modifications to existing hardware at BS and client as well as technology specific industry standards, we present the design of our experimental system FD-LTE, that incorporates a combination of passive SI cancellation schemes, with legacy LTE half-duplex BS and client devices. We build a prototype of FD-LTE, integrate it with LTE's evolved packet core and conduct over-the-air experiments to explore the feasibility and potential for full-duplex with legacy LTE networks. We report promising experimental results from FD-LTE, which currently applies to scenarios with limited ranges that is typical of small cells.

Mobile operators are witnessing a dramatic increase in traffic spurred by a combination of popularity of smartphones, innovative applications and diverse services. As mobile traffic transitions from being voice dominated to video and data dominated, the revenue per byte for the mobile operators is declining at an unhealthy rate. To counter the traffic growth and build cost-effective networks, many operators are now forging alliances for RAN (Radio Access Network) sharing to improve coverage and capacity at reasonable investments and operational costs. This paper presents the design and implementation of NetShare, a network-wide radio resource management framework that provides effective RAN Sharing. NetShare introduces a novel two-level scheduler split between the mobile gateway and the cellular basestations to effectively manage and allocate the wireless resources of the radio access network composed of multiple basestations among multiple different entities (such as operators, content providers, etc.) that share the network. Firstly, NetShare provides performance isolation across entities with a minimum guaranteed resource allocation to each entity across the network. Secondly, NetShare optimally distributes the resources to each entity across the network proportional to the resource demand at each basestation. Through extensive LTE-based system simulations and prototype evaluations on a WiMAX testbed, we show the efficacy of NetShare in (a) providing isolation across entities and (b) efficiently distributing resources for each entity across the network thus achieving high utilization of resources for an entity.

As the growth of mobile video traffic outpaces that of cellular network speed, industry is adopting HTTP-based adaptive video streaming technology which enables dynamic adaptation of video bit-rates to match changing network conditions. However, recent measurement studies have observed problems in fairness, stability, and efficiency of resource utilization when multiple adaptive video flows compete for bandwidth on a shared wired link. Through experiments and simulations, we confirm that such undesirable behavior manifests itself in cellular networks as well. To overcome these problems, we design an in-network resource management framework, AVIS, that schedules HTTP-based adaptive video flows on cellular networks. AVIS effectively manages the resources of a cellular base station across adaptive video flows. AVIS also provides a framework for mobile operators to achieve a desired balance between optimal resource allocation and user quality of experience. AVIS has three key differentiating features: (1) It optimally computes the bit-rate allocation for each user, (2) It includes a scheduler and per-flow shapers to enforce bit-rate stability of each flow and (3) It leverages the resource virtualization technique to separate resource management of adaptive video flows from regular video flows. We implement a prototype system of AVIS and evaluate it on both a WiMAX network testbed and a LTE system simulator to show its efficacy and scalability.

This paper describes the design and implementation of a network virtualization substrate (NVS) for effective virtualization of wireless resources in cellular networks. Virtualization fosters the realization of several interesting deployment scenarios such as customized virtual networks, virtual services, and wide-area corporate networks, with diverse performance objectives. In virtualizing a base station's uplink and downlink resources into slices, \ssrNVSmeets three key requirements-isolation, customization, and efficient resource utilization-using two novel features: 1)NVSintroduces a provably optimal slice scheduler that allows existence of slices with bandwidth-based and resource-based reservations simultaneously; and 2)NVSincludes a generic framework for efficiently enabling customized flow scheduling within the base station on a per-slice basis. Through a prototype implementation and detailed evaluation on a WiMAX testbed, we demonstrate the efficacy of \ssrNVS. For instance, we show for both downlink and uplink directions that \ssrNVScan run different flow schedulers in different slices, run different slices simultaneously with different types of reservations, and perform slice-specific application optimizations for providing customized services.

This paper is motivated by two observations: (1) cellular network operators are actively exploring advertisement delivery as a new means of revenue generation, and (2) cellular basestations perceive intermittent overloads at different times of day. Bringing the two observations together, we design and implement Opal, a novel system for opportunistically aligning advertisement delivery with basestation overload. Such alignment improves the overall perception of network availability for users. To achieve the alignment systematically, Opal builds on an analytical framework for tunable unavailability of network service to users during overload. At the same time, if the network is not overloaded enough during a certain period, Opal schedules enough advertisements to satisfy the advertisement delivery contracts. Opal minimizes the amount of state to be maintained to play advertisements to users uniformly and also maximizes the number of viewers for each advertisement. We implement a prototype of Opal on a Picochip based WiMAX testbed, and demonstrate its efficacy using simulations, analysis and prototype evaluation.

We demonstrate OPAL [2]- a system for opportunistically aligning advertisement delivery with basestation overload periods, which reduces the total number of times network service is unavailable to users. This system is motivated by two trends: Firstly, as networks get dominated by non-elastic traffic such as video, overload management using admission control will be imminent, thereby exposing network unavailability to users. Secondly, as mobile advertising is rapidly growing, mobile network operators are increasingly interested in leveraging its huge revenue potential, and are also better equipped than any other entity in reaching the users.

This paper describes the design and implementation of a network virtualization substrate NVS) for effective virtualization of wireless resources in WiMAX networks. Virtualization fosters the realization of several interesting deployment scenarios such as customized virtual networks, virtual services and wide-area corporate networks, with diverse performance objectives. In virtualizing a basestation's uplink and downlink resources into slices, NVS meets three key requirements - isolation, customization, and efficient resource utilization - using two novel features: (1) NVS introduces a provably-optimal slice scheduler that allows existence of slices with bandwidth-based and resource-based reservations simultaneously, and (2) NVS includes a generic framework for efficiently enabling customized flow scheduling within the basestation on a per-slice basis. Through a prototype implementation and detailed evaluation on a WiMAX testbed, we demonstrate the efficacy of NVS. For instance, we show for both downlink and uplink directions that NVS can run different flow schedulers in different slices, run different slices simultaneously with different types of reservations, and perform slice-specific application optimizations for providing customized services.

Wireless network emulator testbeds have become increasingly important for realistic, at-scale experimental evaluation of new network architectures and protocols. Typically, wireless network performance measurements are made at multiple layers of the wireless protocol stack, i.e. link layer, MAC layer and network layer. This study highlights the impact of layer 2 frame aggregation that is enabled by default in the software drivers for commodity wireless 802.11 devices while it is still not a part of the core 802.11 standard. Using experimental measurements, it is shown that this feature has an impact across a diverse set of wireless experiments and should be considered while comparing results. Measurements on the ORBIT testbed show that throughput measurements can vary up to a startling 25% for certain packet sizes and the variance in receiver side interframe delays can almost double if MAC aggregation and preset transmission opportunities are not taken into consideration. Further results for VoIP traffic show a deterioration in jitter of up to 8 times when coupled with MAC layer aggregation in 802.11.