2,046 research outputs found
Enabling Disaster Resilient 4G Mobile Communication Networks
The 4G Long Term Evolution (LTE) is the cellular technology expected to
outperform the previous generations and to some extent revolutionize the
experience of the users by taking advantage of the most advanced radio access
techniques (i.e. OFDMA, SC-FDMA, MIMO). However, the strong dependencies
between user equipments (UEs), base stations (eNBs) and the Evolved Packet Core
(EPC) limit the flexibility, manageability and resiliency in such networks. In
case the communication links between UEs-eNB or eNB-EPC are disrupted, UEs are
in fact unable to communicate. In this article, we reshape the 4G mobile
network to move towards more virtual and distributed architectures for
improving disaster resilience, drastically reducing the dependency between UEs,
eNBs and EPC. The contribution of this work is twofold. We firstly present the
Flexible Management Entity (FME), a distributed entity which leverages on
virtualized EPC functionalities in 4G cellular systems. Second, we introduce a
simple and novel device-todevice (D2D) communication scheme allowing the UEs in
physical proximity to communicate directly without resorting to the
coordination with an eNB.Comment: Submitted to IEEE Communications Magazin
A survey of self organisation in future cellular networks
This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks
Cloud-assisted body area networks: state-of-the-art and future challenges
Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed
Self-Adaptive Communication for Collaborative Mobile Entities in ERCMS
International audienceAdaptation of communication is required for maintaining the connectivity and the quality of communication in group-wide collaborative activities. This becomes challenging to handle when considering mobile entities in a wireless environment, requiring responsiveness and availability of the communication system. We address these challenges in the context of the ROSACE project where mobile ground and flying robots have to collaborate with each other and with remote human and artificial actors to save and rescue in case of disasters such as forest fires. This paper aims to expose a communication component architecture allowing to manage a cooperative adaptation which is aware of the activity and resource context into pervasive environment. This allows to provide the appropriate adaptation of the activity in response to evolutions of the activity requirements and the changes in relation with the communication resource constraints. In this paper, we present a simulation of a ROSACE use case. The results show how ROSACE entities collaborate to maintain the connectivity and to enhance the quality of communications
Meeting the challenges of decentralized embedded applications using multi-agent systems
International audienceToday embedded applications become large scale andstrongly constrained. They require a decentralized embedded intelligencegenerating challenges for embedded systems. A multi-agent approach iswell suited to model and design decentralized embedded applications.It is naturally able to take up some of these challenges. But somespecific points have to be introduced, enforced or improved in multiagentapproaches to reach all features and all requirements. In thisarticle, we present a study of specific activities that can complementmulti-agent paradigm in the ”embedded” context.We use our experiencewith the DIAMOND method to introduce and illustrate these featuresand activities
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
Mobility management in 5G heterogeneous networks
In recent years, mobile data traffic has increased exponentially as a result of widespread popularity and uptake of portable devices, such as smartphones, tablets and laptops. This growth has placed enormous stress on network service providers who are committed to offering the best quality of service to consumer groups. Consequently, telecommunication engineers are investigating innovative solutions to accommodate the additional load offered by growing numbers of mobile users.
The fifth generation (5G) of wireless communication standard is expected to provide numerous innovative solutions to meet the growing demand of consumer groups. Accordingly the ultimate goal is to achieve several key technological milestones including up to 1000 times higher wireless area capacity and a significant cut in power consumption.
Massive deployment of small cells is likely to be a key innovation in 5G, which enables frequent frequency reuse and higher data rates. Small cells, however, present a major challenge for nodes moving at vehicular speeds. This is because the smaller coverage areas of small cells result in frequent handover, which leads to lower throughput and longer delay.
In this thesis, a new mobility management technique is introduced that reduces the number of handovers in a 5G heterogeneous network. This research also investigates techniques to accommodate low latency applications in nodes moving at vehicular speeds
A cyber-enabled mission-critical system for post-flood response:Exploiting TV white space as network backhaul links
A crucial problem in post-flood recovery actions is the ability to rapidly establish communication and collaboration among rescuers to conduct timely and effective search and rescue (SAR) mission given disrupted telecommunication infrastructure to support the service. Aimed at providing such proximity service (ProSe) for mission-critical data exchange in the post-flood environment, the majority of existing solutions rely heavily upon ad-hoc networking approaches, which suffer from restricted communication range and the limited scope of interaction. As an effort to broaden the ProSe coverage and expand integrated global-local information exchange in the post-flood SAR activities, this paper proposes a novel network architecture in the form of a cyber-enabled mission-critical system (CEMCS) for acquiring and communicating post-flood emergency data by exploiting TV white space spectrum as network backhaul links. The primary method of developing the proposed system builds upon a layered architecture of wireless local, regional and wide-area communications, and incorporates collaborative network components among these layers. The desirable functionalities of CEMCS are showcased through formulation and the development of an efficient global search strategy exploiting a wide range of collaboration among network agents. The simulation results demonstrate the capability of CEMCS to provide ProSe in the post-flood scenarios as reflected by reliable network performance (e.g., packet delivery ratio nearing 80%-90%) and the optimality of efficient search algorithm
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