A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Flow-oriented anomaly-based detection of denial of service attacks with flow-control-assisted mitigation

Flooding-based distributed denial-of-service (DDoS) attacks present a serious and major threat to the targeted enterprises and hosts. Current protection technologies are still largely inadequate in mitigating such attacks, especially if they are large-scale. In this doctoral dissertation, the Computer Network Management and Control System (CNMCS) is proposed and investigated; it consists of the Flow-based Network Intrusion Detection System (FNIDS), the Flow-based Congestion Control (FCC) System, and the Server Bandwidth Management System (SBMS). These components form a composite defense system intended to protect against DDoS flooding attacks. The system as a whole adopts a flow-oriented and anomaly-based approach to the detection of these attacks, as well as a control-theoretic approach to adjust the flow rate of every link to sustain the high priority flow-rates at their desired level. The results showed that the misclassification rates of FNIDS are low, less than 0.1%, for the investigated DDOS attacks, while the fine-grained service differentiation and resource isolation provided within the FCC comprise a novel and powerful built-in protection mechanism that helps mitigate DDoS attacks

Diseños de capa cruzada para redes inalámbricas de área corporal energéticamente eficientes: una revisión

RESUMEN: El diseño de capa cruzada se considera una poderosa alternativa para dar solución a las complejidades introducidas por las comunicaciones inalámbricas en redes de área corporal (WBAN), donde el modelo clásico de comunicaciones no ha exhibido un desempeño adecuado. Respecto al problema puntual de consumo de energía, hemos preparado la presente revisión de las publicaciones más relevantes que tratan la eficiencia energética para WBAN usando diseño de capa cruzada. En este artículo se proporciona una revisión exhaustiva de los avances en aproximaciones, protocolos y optimizaciones de capa cruzada cuyo objetivo es incrementar el tiempo de vida de las redes WBAN mediante el ahorro de energía. Luego, se discute los aspectos relevantes y deficiencias de las técnicas de capa cruzada energéticamente eficientes. Además, se introducen aspectos de investigación abiertos y retos en el diseño de capa cruzada para WBAN. En esta revisión proponemos una taxonomía de las aproximaciones de capa cruzada, de modo que las técnicas revisadas se ajustan en categorías de acuerdo a los protocolos involucrados en el diseño. Una clasificación novedosa se incluye para hacer claridad en los conceptos teóricos involucrados en cada esquema de capa cruzada y para luego agrupar aproximaciones similares evidenciando las diferencias con otras técnicas entre sí. Nuestras conclusiones consideran los aspectos de movilidad y modelamiento del canal en escenarios de WBAN como las direcciones para futura investigación en WBAN y en aplicaciones de telemedicina.ABSTRACT: Cross-layer design is considered a powerful alternative to solve the complexities of wireless communication in wireless body area networks (WBAN), where the classical communication model has been shown to be inaccurate. Regarding the energy consumption problem, we have prepared a current survey of the most relevant scientific publications on energy-efficient cross-layer design for WBAN. In this paper, we provide a comprehensive review of the advances in cross-layer approaches, protocols and optimizations aimed at increasing the network lifetime by saving energy in WBANs. Subsequently, we discuss the relevant aspects and shortcomings of these energy-efficient cross-layer techniques and point out the open research issues and challenges in WBAN cross-layer design. In this survey, we propose a taxonomy for cross-layer approaches to fit them into categories based on the protocols involved in the cross-layer scheme. A novel classification is included to clarify the theoretical concepts behind each cross-layer scheme; and to group similar approaches by establishing their differences from the other strategies reviewed. Our conclusion considers the aspects of mobility and channel modeling in WBAN scenarios as the directions of future cross-layer research for WBAN and telemedicine applications