Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

Towards Viable Large Scale Heterogeneous Wireless Networks

We explore radio resource allocation and management issues related to a large-scale heterogeneous (hetnet) wireless system 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 incorporate 3G cellular technologies HSPA and EVDO, 4G cellular technologies WiMAX and LTE, and WLAN technology Wi-Fi as the RATs in our hetnet wireless system. We assume that the user devices are either multi-modal or have one or more reconfigurable radios which makes it possible for each device to use any available RAT at any given time subject to resource-sharing agreements. For such a hetnet system where resource allocation is coordinated at a global level, characterizing the network performance in terms of various conflicting network efficiency objectives that takes costs associated with a network re-association operation into account largely remains an open problem. Also, all the studies to-date that try to characterize the network performance of a hetnet system do not account for RAT-specific implementation details and the management overhead associated with setting up a centralized control. We study the radio resource allocation problem and the implementation/management overhead issues associated with a hetnet system in two research phases. In the first phase, we develop cost models associated with network re-association in terms of increased power consumption and communication downtime taking into account various user device assumptions. Using these cost models in our problem formulations, the first phase focuses on resource allocation strategies where we use a high-level system modeling approach to study the achievable performance in terms of conflicting network efficiency measures of spectral efficiency, overall power consumption, and instantaneous and long-term fairness for each user in the hetnet system. Our main result from this phase of study suggests that the gain in spectral efficiency due to multi-access network diversity results in a tremendous increase in overall power consumption due to frequent re-associations required by user devices. We then develop a utility function-based optimization algorithm to characterize and achieve a desired tradeoff in terms of all four network efficiency measures of spectral efficiency, overall power consumption and instantaneous and long-term fairness. We show an increase in a multi-attribute system utility measure of up to 56.7% for our algorithm compared to other widely studied resource allocation algorithms including max-sum rate, proportional fairness, max-min fairness and min power. The second phase of our research study focuses on practical implementation issues including the overhead required to implement a centralized GRC solution in a hetnet system. Through detailed protocol level simulations performed in ns-2, we show an increase in spectral efficiency of up to 99% and an increase in instantaneous fairness of up to 28.5% for two sort-based user device-to-Access Point (AP)/Base Station (BS) association algorithms implemented at the GRC that aim to maximize system spectral efficiency and instantaneous fairness performance metrics respectively compared to a distributed solution where each user makes his/her own association decision. The efficiency increase for each respective attribute again results in a tremendous increase in power consumption of up to 650% and 794% for each respective algorithm implemented at the GRC compared to a distributed solution because of frequent re-associations

Cooperative smartphone relay selection based on fair power utilization for network coverage extension

This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either by providing access to out-of-range devices or by facilitating multi-path network access to connected devices. In this work, we assume that all mobile devices can benefit from using other mobile devices as relays and investigate the fairness of relay selection algorithms. We point out that signal strength based relay selection inevitably leads to unfair relay selection and devise a new algorithm that is based on fair utilization of power resources on mobile devices. We call this algorithm Credit based Fair Relay Selection (CF-RS) and in this paper show through simulation that the algorithm results in fair battery power utilization, while providing similar data rates compared with traditional approaches. We then extend the solution to demonstrate that adding incentives for relay operation adds clear value for mobile devices in the case they require relay service. Typically, mobile devices represent self-interested users who are reluctant to cooperate with other network users, mainly due to the cost in terms of power and network capacity. In this paper, we present an incentive based solution which provides clear mutual benefit for mobile devices and demonstrate this benefit in the simulation of symmetric and asymmetric network topologies. The CF-RS algorithm achieves the same performance in terms of achievable data rate, Jain's fairness index and utility of end devices in both symmetric and asymmetric network configurations

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Efficient design of WIMAX/802.16 mesh networks

Broadband wireless networks are becoming increasingly popular due to their fast and inexpensive deployment and their capabilities of providing flexible and ubiquitous Internet access. While the majority of existing broadband wireless networks are still exclusively limited to single hop access, it is the ability of these networks to forward data frames over multi-hop wireless routes which enabled them to easily extend the network coverage area. Unfortunately, achieving good multi- hop throughput has been challenging due to several factors, such as lossy wireless links caused by interference from concurrent transmissions, and intra-path interference caused by transmissions on successive hops along a single path. A wireless mesh network WMN consists of a number of stationary wireless mesh routers, forming a wireless backbone. The wireless mesh routers serve as access points (APs) for wireless mobile devices, and some of them also act as gateways to the Internet via high speed wireless links. Several technologies are currently being considered for mesh (multi-hop) networks, including, IEEE 802.11 (both single channel and multi-channel), IEEE 802.16/WiMAX, and next generation cellular networks (LTE). In this work, we focus on the IEEE 802.16. To maximize the network performance of mesh networks (e.g., throughput), it is essential to consider a cross-layer design, exploiting the dependency between protocol layers such as the routing network layer and the scheduling resource allocation MAC layer. Therefore this PhD thesis considers a cross-layer design approach for designing efficient wireless mesh networks; we first develop mathematical models (link-based and path-based) for the problem of joint routing tree construction and link scheduling in WiMAX-based mesh networks with the objective of minimizing the schedule length to satisfy a set of uplink and downlink demands. This is achieved by maximizing the number of concurrent active transmissions in the network by efficiently reusing the spectrum spatially. Second, we exploit the broadcasts nature of the wireless medium and enhance our design models by incorporating opportunistic network coding into the joint routing tree construction and link scheduling problem. Identifying coding-aware routing structures and utilizing the broadcasting feature of the wireless medium play an important role in realizing the achievable gain of network coding. Last, the uprising mobile WiMAX (802.16e amendment) has introduced more difficulties and challenges into the network design problem; thus, ensuring larger connection lifetime and better routing stability become of greater interest for the joint routing and scheduling problem. This is addressed by augmenting the previously designed models. Throughout this thesis, we assume centralized scheduling at the base station (BS) and we develop, for the joint problems, integer linear programming (ILP) models which require the enumeration of all feasible solutions to reach the optimal solution. Given their complexities, we rely on optimization decomposition methods using column generation for solving each model in an efficient way

Electric vehicle as a service (EVaaS):applications, challenges and enablers

Under the vehicle-to-grid (V2G) concept, electric vehicles (EVs) can be deployed as loads to absorb excess production or as distributed energy resources to supply part of their stored energy back to the grid. This paper overviews the technologies, technical components and system requirements needed for EV deployment. Electric vehicle as a service (EVaaS) exploits V2G technology to develop a system where suitable EVs within the distribution network are chosen individually or in aggregate to exchange energy with the grid, individual customers or both. The EVaaS framework is introduced, and interactions among EVaaS subsystems such as EV batteries, charging stations, loads and advanced metering infrastructure are studied. The communication infrastructure and processing facilities that enable data and information exchange between EVs and the grid are reviewed. Different strategies for EV charging/discharging and their impact on the distribution grid are reviewed. Several market designs that incentivize energy trading in V2G environments are discussed. The benefits of V2G are studied from the perspectives of ancillary services, supporting of renewables and the environment. The challenges to V2G are studied with respect to battery degradation, energy conversion losses and effects on distribution system

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Optimized traffic scheduling and routing in smart home networks

Home networks are evolving rapidly to include heterogeneous physical access and a large number of smart devices that generate different types of traffic with different distributions and different Quality of Service (QoS) requirements. Due to their particular architectures, which are very dense and very dynamic, the traditional one-pair-node shortest path solution is no longer efficient to handle inter-smart home networks (inter-SHNs) routing constraints such as delay, packet loss, and bandwidth in all-pair node heterogenous links. In addition, Current QoS-aware scheduling methods consider only the conventional priority metrics based on the IP Type of Service (ToS) field to make decisions for bandwidth allocation. Such priority based scheduling methods are not optimal to provide both QoS and Quality of Experience (QoE), especially for smart home applications, since higher priority traffic does not necessarily require higher stringent delay than lower-priority traffic. Moreover, current QoS-aware scheduling methods in the intra-smart home network (intra-SHN) do not consider concurrent traffic caused by the fluctuation of intra-SH network traffic distributions. Thus, the goal of this dissertation is to build an efficient heterogenous multi-constrained routing mechanism and an optimized traffic scheduling tool in order to maintain a cost-effective communication between all wired-wireless connected devices in inter-SHNs and to effectively process concurrent and non-concurrent traffic in intra-SHN. This will help Internet service providers (ISPs) and home user to enhance the overall QoS and QoE of their applications while maintaining a relevant communication in both inter-SHNs and intra-SHN. In order to meet this goal, three key issues are required to be addressed in our framework and are summarized as follows: i) how to build a cost-effective routing mechanism in heterogonous inter-SHNs ? ii) how to efficiently schedule the multi-sourced intra-SHN traffic based on both QoS and QoE ? and iii) how to design an optimized queuing model for intra-SHN concurrent traffics while considering their QoS requirements? As part of our contributions to solve the first problem highlighted above, we present an analytical framework for dynamically optimizing data flows in inter-SHNs using Software-defined networking (SDN). We formulate a QoS-based routing optimization problem as a constrained shortest path problem and then propose an optimized solution (QASDN) to determine minimal cost between all pairs of nodes in the network taking into account the different types of physical accesses and the network utilization patterns. To address the second issue and to solve the gaps between QoS and QoE, we propose a new queuing model for QoS-level Pair traffic with mixed arrival distributions in Smart Home network (QP-SH) to make a dynamic QoS-aware scheduling decision meeting delay requirements of all traffic while preserving their degrees of criticality. A new metric combining the ToS field and the maximum number of packets that can be processed by the system's service during the maximum required delay, is defined. Finally, as part of our contribution to address the third issue, we present an analytic model for a QoS-aware scheduling optimization of concurrent intra-SHN traffics with mixed arrival distributions and using probabilistic queuing disciplines. We formulate a hybrid QoS-aware scheduling problem for concurrent traffics in intra-SHN, propose an innovative queuing model (QC-SH) based on the auction economic model of game theory to provide a fair multiple access over different communication channels/ports, and design an applicable model to implement auction game on both sides; traffic sources and the home gateway, without changing the structure of the IEEE 802.11 standard. The results of our work offer SHNs more effective data transfer between all heterogenous connected devices with optimal resource utilization, a dynamic QoS/QoE-aware traffic processing in SHN as well as an innovative model for optimizing concurrent SHN traffic scheduling with enhanced fairness strategy. Numerical results show an improvement up to 90% for network resource utilization, 77% for bandwidth, 40% for scheduling with QoS and QoE and 57% for concurrent traffic scheduling delay using our proposed solutions compared with Traditional methods