Hiram Galeana-Zapién

Design and Evaluation of a Backhaul-Aware Base Station Assignment Algorithm for OFDMA-Based Cellular Networks

Existing base station (BS) assignment methods in cellular networks are mainly driven by radio criteria since it is assumed that the only limiting resource factor is on the air interface. However, as enhanced air interfaces have been deployed, and mobile data and multimedia traffic increases, a growing concern is that the backhaul of the cellular network can become the bottleneck in certain deployment scenarios. In this paper, we extend the BS assignment problem to cope with possible backhaul congestion situations. A backhaul-aware BS assignment problem is modeled as an optimization problem using a utility-based framework, imposing constraints on both radio and backhaul resources, and mapped into a Multiple-Choice Multidimensional Knapsack Problem (MMKP). A novel heuristic BS assignment algorithm with polynomial time is formulated, evaluated and compared to classical schemes based exclusively on radio conditions. Simulation results demonstrate that the proposed algorithm can provide the same system capacity with less backhaul resources so that, under backhaul bottleneck situations, a better overall network performance is effectively achieved.

Analytical Modeling and Performance Evaluation of Cell Selection Algorithms for Mobile Networks with Backhaul Capacity Constraints

Mobile backhaul has moved to the forefront of wireless industry hot topics. The progressive deployment of spectrally efficient radio access technologies (e.g. HSPA, LTE, WiMAX) in mobile broadband is turning into stringent capacity requirements on the backhaul network. This makes backhaul capacity to become a potential network bottleneck in some deployment scenarios. While more cost-efficient transmission technologies are needed to increase the capacity of mobile backhaul, optimization solutions to get the most out of the backhaul capacity are also necessary. This paper analyses the possibility to exploit load balancing among base stations to improve backhaul capacity utilization. Load balancing is realized through cell selection algorithms accounting for both radio interface and backhaul conditions. An analytical model aimed at evaluating the performance of cell selection strategies for mobile networks with backhaul capacity constraints is developed. The analytical model is used to evaluate the performance of a novel backhaul-aware cell selection algorithm and compare it with classical schemes based exclusively on radio information. Obtained results show that the proposed algorithm can achieve a utilization of backhaul resources higher than the traditional cell selection schemes while providing the same radio interface performance. Analytical results have been verified by means of simulation.

Mobile phone middleware architecture for energy and context awareness in location-based services.

The disruptive innovation of smartphone technology has enabled the development of mobile sensing applications leveraged on specialized sensors embedded in the device. These novel mobile phone applications rely on advanced sensor information processes, which mainly involve raw data acquisition, feature extraction, data interpretation and transmission. However, the continuous accessing of sensing resources to acquire sensor data in smartphones is still very expensive in terms of energy, particularly due to the periodic use of power-intensive sensors, such as the Global Positioning System (GPS) receiver. The key underlying idea to design energy-efficient schemes is to control the duty cycle of the GPS receiver. However, adapting the sensing rate based on dynamic context changes through a flexible middleware has received little attention in the literature. In this paper, we propose a novel modular middleware architecture and runtime environment to directly interface with application programming interfaces (APIs) and embedded sensors in order to manage the duty cycle process based on energy and context aspects. The proposed solution has been implemented in the Android software stack. It allows continuous location tracking in a timely manner and in a transparent way to the user. It also enables the deployment of sensing policies to appropriately control the sampling rate based on both energy and perceived context. We validate the proposed solution taking into account a reference location-based service (LBS) architecture. A cloud-based storage service along with online mobility analysis tools have been used to store and access sensed data. Experimental measurements demonstrate the feasibility and efficiency of our middleware, in terms of energy and location resolution.

Power management techniques in smartphone-based mobility sensing systems: A survey

Abstract The rapidly enhancing sensing capabilities of smartphones are enabling the development of a wide range of innovative mobile sensing applications that are impacting on everyday life of mobile users. However, supporting long-term sensing applications is challenging because of their key requirements for continuous access to embedded sensors for gathering raw data, which can deplete the device’s battery in a few hours. This problem is expected to remain in the near future because the improvements on the capacity of batteries are coming at a slower pace than those advances in computing and sensing capabilities. The research community has highlighted the need for power-aware and context-aware sensing techniques deployed at different levels of mobile platforms for making a more efficient use of energy resources. Previous studies have analyzed the optimization of power consumption in mobile devices over different critical axes, like data transmission, computing, and hardware design. However, a comprehensive study focused in the challenges of power-aware smartphone-based sensing and strategies for addressing them has not been produced yet. This survey aims to fill this void with a particular focus on mobility sensing systems (e.g., human activity recognition, location-based services), presenting a comprehensive review of relevant strategies aimed at solving this issue. Also, this survey defines a taxonomy for such solutions, highlighting their strengths and limitations. Finally, most relevant open challenges and trends are discussed for providing insights for future research in the field.

Genetic tuning of fuzzy rule-based systems for multi-hop broadcast protocols for VANETs

Vehicular ad-hoc networks (VANETs) have been identified as a key technology to enable intelligent transport systems (ITS), which in turn have the potential to radically enhance the safety and comfort of vehicles on the road as well as the potential to reduce their environmental impact. Nevertheless, several issues still must be addressed in order to fully exploit the potential of VANETs in favor of ITSs. Particularly, one key open issue in VANETs is the multi-hop broadcast message dissemination (MBMD) for safety and infotainment applications. In this context, fuzzy rule-based systems (FRBSs) have been proved to be useful when designing MBMD protocols for VANETs. However, a methodological tuning of the FRBS for such MBMD protocols to improve their performance in terms of metrics like packet delivery ratio still remains open. This paper deals with the problem of determining the best position and overlap between fuzzy states (FSs) of the MFs for FRBS-based MBMD protocols in order to enhance its performance. Specifically, a component-based methodology using genetic algorithm (GA) for the MFs tuning problem is proposed. The proposed methodology is validated by tuning two relevant FRBS-based MBMD protocols found in the literature. The tuned MBMD protocols have been evaluated over a range of realistic scenarios. Obtained results from the evaluations show that the tuned MBMD protocols provide better performance than the heuristically defined FRBSs in terms of important metrics like packet delivery ratio.

Reliable Multihop Broadcast Protocol with a Low-Overhead Link Quality Assessment for ITS Based on VANETs in Highway Scenarios

Vehicular ad hoc networks (VANETs) have been identified as a key technology to enable intelligent transport systems (ITS), which are aimed to radically improve the safety, comfort, and greenness of the vehicles in the road. However, in order to fully exploit VANETs potential, several issues must be addressed. Because of the high dynamic of VANETs and the impairments in the wireless channel, one key issue arising when working with VANETs is the multihop dissemination of broadcast packets for safety and infotainment applications. In this paper a reliable low-overhead multihop broadcast (RLMB) protocol is proposed to address the well-known broadcast storm problem. The proposed RLMB takes advantage of the hello messages exchanged between the vehicles and it processes such information to intelligently select a relay set and reduce the redundant broadcast. Additionally, to reduce the hello messages rate dependency, RLMB uses a point-to-zone link evaluation approach. RLMB performance is compared with one of the leading multihop broadcast protocols existing to date. Performance metrics show that our RLMB solution outperforms the leading protocol in terms of important metrics such as packet dissemination ratio, overhead, and delay.

A Business-Oriented Management Framework for Mobile Communication Systems

The incremental efforts needed to manage low-level radio access network decisions from a business-perspective have received little attention so far. This paper considers the influence of business-level indicators on network management decisions related to low-level network control mechanisms. It provides a formal understanding of all involved aspects, the representation of the adjustable parameters, and the network control mechanisms that enable the reconfiguration of access network entities from a business perspective (i.e., users’ information, operator’s goals). The effectiveness of our approach is validated through a simulation environment that we developed on OPNET.

Towards Intelligent Tuning of Frequency and Transmission Power Adjustment in Beacon-based Ad-Hoc Networks.

This paper presents a genetic-based approach to determine optimal values of frequency and transmission power in beacon-based ad-hoc networks. The approach has been evaluated through simulations, and it has demonstrated to be more efficient than a dynamic control of frequency and transmission power, with reduction of up to 73% in packet collisions and with reduction of packet losses of up to 63% in an urban scenario. The approach and the results presented in this paper represent our initial efforts towards a more efficient control of beacon frequency and transmission power, which can exploit the benefits of a geneticbased approach but that can be applied in runtime in practical scenarios.

Multi-hop broadcast message dissemination in vehicular ad hoc networks: A security perspective review:

Vehicular ad hoc networks have been identified as a key technology for enabling safety and infotainment applications in the context of smart and connected vehicles. In this sense, diverse approaches of multi-hop broadcast protocols have been proposed to collect and disseminate context information through the network. However, before vehicular ad hoc networks applications fulfill their expected potential to connect smart vehicles, several issues must be addressed. Among these issues, those related to security are of particular importance. In this article, the main security issues of broadcast message dissemination in vehicular ad hoc networks are discussed. Moreover, a review of the most relevant threats and proposed solutions to secure broadcast message dissemination in vehicular ad hoc networks is presented and discussed. As mentioned, security is an important topic which has not been fully addressed in vehicular ad hoc networks; therefore, the aim of this article is to introduce security issues and proposed solutions related to three main security concerns associated with the message dissemination process in vehicular ad hoc networks: network access, data consistency, and broadcast protocols.

Full On-Device Stay Points Detection in Smartphones for Location-Based Mobile Applications

The tracking of frequently visited places, also known as stay points, is a critical feature in location-aware mobile applications as a way to adapt the information and services provided to smartphones users according to their moving patterns. Location based applications usually employ the GPS receiver along with Wi-Fi hot-spots and cellular cell tower mechanisms for estimating user location. Typically, fine-grained GPS location data are collected by the smartphone and transferred to dedicated servers for trajectory analysis and stay points detection. Such Mobile Cloud Computing approach has been successfully employed for extending smartphone’s battery lifetime by exchanging computation costs, assuming that on-device stay points detection is prohibitive. In this article, we propose and validate the feasibility of having an alternative event-driven mechanism for stay points detection that is executed fully on-device, and that provides higher energy savings by avoiding communication costs. Our solution is encapsulated in a sensing middleware for Android smartphones, where a stream of GPS location updates is collected in the background, supporting duty cycling schemes, and incrementally analyzed following an event-driven paradigm for stay points detection. To evaluate the performance of the proposed middleware, real world experiments were conducted under different stress levels, validating its power efficiency when compared against a Mobile Cloud Computing oriented solution.