Rahul Amin

Balancing Spectral Efficiency, Energy Consumption, and Fairness in Future Heterogeneous Wireless Systems with Reconfigurable Devices

In this paper, we present an approach to managing resources in a large-scale heterogeneous wireless network that supports reconfigurable devices. The system under study embodies internetworking concepts requiring independent wireless networks to cooperate in order to provide a unified network to users. We propose a multi-attribute scheduling algorithm implemented by a central Global Resource Controller (GRC) that manages the resources of several different autonomous wireless systems. The attributes considered by the multi-attribute optimization function consist of system spectral efficiency, battery lifetime of each user (or overall energy consumption), and instantaneous and long-term fairness for each user in the system. To compute the relative importance of each attribute, we use the Analytical Hierarchy Process (AHP) that takes interview responses from wireless network providers as input and generates weight assignments for each attribute in our optimization problem. Through Matlab/CPLEX based simulations, we show an increase in a multi-attribute system utility measure of up to 57% for our algorithm compared to other widely studied resource allocation algorithms including Max-Sum Rate, Proportional Fair, Max-Min Fair and Min Power.

Smart Grid communication using next generation heterogeneous wireless networks

In this paper, we present a Smart Grid Home Area Network communication infrastructure solution that is based on future next generation heterogeneous wireless systems. The heterogeneous wireless system is composed of several Radio Access Technologies (RATs) available at consumer premises. The smart devices that use Smart Grid applications are assumed to have reconfigurable radios. A centralized Global Resource Controller (GRC) instructs the smart devices to use a particular RAT at any given time. The device-to-RAT association is made by the GRC using a two-step scheduling algorithm that accounts for the requirements of both best-effort and real-time Smart Grid traffic. To make the solution scalable, the approach utilizes Dynamic Spectrum Access methods to obtain additional open spectrum. We show up to 80% increase in real-time traffic support and 726% increase in best-effort traffic support in our proposed heterogeneous wireless system that uses reconfigurable radios, compared to the homogeneous wireless networks used today by smart devices with static radios.

A Fast Cloud-Based Network Selection Scheme Using Coalition Formation Games in Vehicular Networks

Leveraging multiple wireless technologies and radio access networks (RANs), vehicles on the move have the potential to get robust connectivity and continuous service. To support the demands of as many vehicles as possible, an efficient and fast network selection scheme is critically important to achieve high performance and efficiency. So far, prior works have primarily focused on design of optimization algorithms and utility functions for either user or network performance. Most such studies do not address the complexities involved in the acquisition of needed information and the execution of algorithms, making them unsuitable for practical implementations in vehicles. This paper proposes a fast cloud-based network selection scheme for vehicular networks. By leveraging a compute clouds abundant computing and data storage resources, vehicles can leverage wider scope network information for decision-making. Vehicles select best access networks through a coalition formation game approach. A one-iteration fast convergence algorithm is proposed to achieve the final state of coalition structure in the game. Through extensive simulation, the proposed network selection scheme was shown to balance system throughput and fairness with a built-in utility division rule of the framework. The algorithm efficiency showed eightfold enhancement over a conventional coalition formation algorithm. Such features validate the potential of implementation in practice.

Energy aware task mapping algorithm for heterogeneous MPSoC based architectures

Energy Management for multi-mode Software Defined Radio (SDR) systems remains a daunting challenge. In this paper, we focus on the issue of task allocation for multi-processor based systems with hybrid processing resources that can be reconfigured. With the objective of minimizing energy, we propose a fast, energy aware static task mapping heuristic to minimize the average overall energy consumption. Simulation results show that the proposed heuristic is capable of achieving results that are within 20% of the optimal solution while providing orders of magnitude speedup in processing time.

Design considerations in applying disruption tolerant networking to tactical edge networks

In recent years there has been a strong desire in the U.S. Department of Defense to augment traditional ground and satellite communications with a high capacity aerial tier. High capacity airborne links are often directional in nature and highly affected by aircraft body blockage, exhibiting unique outage characteristics compared to ground or satellite networks. To mitigate the effects of periodic link outages that last seconds to minutes, disruption tolerant networking (DTN) technology has been proposed. In this article we examine applying the DTN Bundle Protocol (RFC 5050) to ship-to-shore networks for traffic flowing over the aerial nodes. Specifically, we examine applying DTN proxies, tunnels, and interfaces to both the plaintext and ciphertext side of military networks to understand architecture and design considerations and limitations.

Assessing Performance Gains Through Global Resource Control of Heterogeneous Wireless Networks

We study the resource allocation and management issues related to heterogeneous wireless systems made up of several radio access technologies (RATs) that collectively provide a unified wireless network to a diverse set of users through co-ordination managed by a centralized global resource controller (GRC). We assume that the user devices are multimodal, which makes it possible for each device to use any available access point (AP)/base station (BS) of a RAT at any given time. Through detailed protocol level simulations performed in ns-2, we show an increase in spectral efficiency of up to 99 percent and an increase in short-term fairness of up to 28.5 percent for two greedy sort-based user device-to-AP/BS association algorithms implemented at the GRC compared to a distributed solution used in practice today where each user makes his/her own association decision. While the increase in overhead due to re-associations for a centralized solution grows only slightly (by up to 4.1 percent) compared to a distributed solution, we find the performance increase in spectral efficiency and short-term fairness attributes come at the cost of an order of magnitude increase (of up to 794 percent) in energy consumption.

An interference and QOS aware distributed scheduling approach for hybrid IEEE 802.16E mesh networks

A distributed scheduling approach for fast deployable tactical IEEE 802.16e networks is presented where distributed base stations with dual radios form a mesh backhaul and mobile battle units communicate through these base-stations. The mesh backhaul is formed via an IEEE 802.16e mesh mode radio on each base station, while mobile units communicate with base stations via PMP mode radios. The scheduling approach consists of two phases. In the first phase where base stations are deployed, a centralized mesh scheduling algorithm is applied with collected information on network topology, radio parameters, and initial QoS provision requirements. At the same time, each base station utilizes the initial mesh schedule to derive a PMP schedule for actual demands from associated mobile units. In the second phase, each base station monitors its carried PMP traffic load statistics; to accommodate traffic load changes in a distributed fashion, each base station lends or borrows time slots from nearby base stations to adjust its mesh and PMP radio schedules. The distributed schedule adaptation method not only allows individual base stations to accommodate short-term increases in bandwidth demands, it also provides the means for optimizing the mesh and PMP schedules with respect to actual bandwidth demands. Integrated with a previously proposed routing scheme, the method is evaluated with simulations in network simulator ns-2. In various mobile scenarios, increased overall network throughput and per-mobile throughput across handoffs are achieved with the proposed scheduling methods.

Energy Aware Mapping for Reconfigurable Wireless MPSoCs

Energy management for multimode software defined radio systems remains a daunting challenge. This brief develops a high level framework that generates a multiprocessor systems on chip architecture from a library of heterogeneous processing resources that can be reconfigured to support various modes of operation. The framework proposes joint task and core mapping with system level floorplanning. With the objective of minimizing energy, we develop an analytical probabilistic model that considers static, dynamic, configuration, and communication energy components for multiple applications characterized by probabilities of execution. Finally, a fast energy aware joint task and core mapping heuristic is proposed and performance is demonstrated on realistic benchmarks.

A User Study of Netflix Streaming

Netflix and Hulu are examples of HTTP-based Adaptive Streaming (HAS). HAS is unique because it attempts to manage the user’s perceived quality by adapting video quality. Current HAS research fails to address whether adaptations actually make a difference? The main challenge in answering this is the lack of consideration for the end user’s perceived quality. The research community is converging on an accepted set of ‘component metrics’ for HAS. However, determining an objective Quality of Experience (QoE) estimate is an open issue. A between-subject user study of Netflix was conducted to shed light on the user’s perception of quality. We found that users prefer to receive lower video quality levels first with marginal improvements made over time. Currently, content providers switch between the highest and lowest level of quality. This paper seeks to explain a better method that led to higher user satisfaction based on Mean opinion score values (MOS).

MPMAP : A high level synthesis and mapping tool for MPSoCs

The design of efficient multiprocessor systems on chip (MPSoC) is a daunting challenge. This challenge is driven by the increasing demand in achieving high performance, low power, and reconfigurable applications onto the same platform. As a consequence, there is an emerging need for fast, and efficient design space exploration, while providing abstract models for a wide range of applications, and types of processing units (PUs). Therefore, this paper proposes a framework for a fast MPSoC generation with joint task and core mapping with the objective of minimizing the average power consumption. The proposed framework considers the static, dynamic, reconfiguration and communication power components. A tool for high level MPSoC task and core mapping (MPMAP) is built based on the proposed framework. MPMAP provides a flexible XML interface that provides a high level description of the different PU architectures, and different applications scenarios. Additionally, the paper presents a case study of real-life applications that can be adopted in future heterogeneous wireless systems.