“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

This paper presents and evaluates two principles for wireless routing protocols. The first is datapath validation: data traffic quickly discovers and fixes routing inconsistencies. The second is adaptive beaconing: extending the Trickle algorithm to routing control traffic reduces route repair latency and sends fewer beacons.We evaluate datapath validation and adaptive beaconing in CTP Noe, a sensor network tree collection protocol. We use 12 different testbeds ranging in size from 20--310 nodes, comprising seven platforms, and six different link layers, on both interference-free and interference-prone channels. In all cases, CTP Noe delivers > 90% of packets. Many experiments achieve 99.9%. Compared to standard beaconing, CTP Noe sends 73% fewer beacons while reducing topology repair latency by 99.8%. Finally, when using low-power link layers, CTP Noe has duty cycles of 3% while supporting aggregate loads of 30 packets/minute.

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Collection tree protocol

In this article we discuss the state of the art of (mobile) multihop ad hoc networking. This paradigm has often been identified with the solutions developed inside the IETF MANET working group, and for this reason it is called the MANET paradigm. However, they do not coincide, and in the last decade they clearly diverged. In this article, we start from the reasons why the MANET paradigm did not have a major impact on computer communications, and we discuss the evolution of the multihop ad hoc networking paradigm by building on the lessons learned from the MANET research. Specifically, we analyze four successful networking paradigms, mesh, sensor, opportunistic, and vehicular networks, that emerged from the MANET world as a more pragmatic application of the multihop ad hoc networking paradigm. We also present the new research directions in the multihop ad hoc networking field: peoplecentric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications.

Mobile ad hoc networking: milestones, challenges, and new research directions

The emergence of two new technologies, namely, software defined networking (SDN) and network function virtualization (NFV), have radically changed the development of network functions and the evolution of network architectures. These two technologies bring to mobile operators the promises of reducing costs, enhancing network flexibility and scalability, and shortening the time-to-market of new applications and services. With the advent of SDN and NFV and their offered benefits, the mobile operators are gradually changing the way how they architect their mobile networks to cope with ever-increasing growth of data traffic, massive number of new devices and network accesses, and to pave the way toward the upcoming fifth generation networking. This survey aims at providing a comprehensive survey of state-of-the-art research work, which leverages SDN and NFV into the most recent mobile packet core network architecture, evolved packet core. The research work is categorized into smaller groups according to a proposed four-dimensional taxonomy reflecting the: 1) architectural approach, 2) technology adoption, 3) functional implementation, and 4) deployment strategy. Thereafter, the research work is exhaustively compared based on the proposed taxonomy and some added attributes and criteria. Finally, this survey identifies and discusses some major challenges and open issues, such as scalability and reliability, optimal resource scheduling and allocation, management and orchestration, and network sharing and slicing that raise from the taxonomy and comparison tables that need to be further investigated and explored.

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SDN/NFV-Based Mobile Packet Core Network Architectures: A Survey

Current challenges demand a profound restructuration of the global healthcare system. A more efficient system is required to cope with the growing world population and increased life expectancy, which is associated with a marked prevalence of chronic neurological disorders such as Parkinson's disease (PD). One possible approach to meet this demand is a laterally distributed platform such as the Internet of Things (IoT). Real-time motion metrics in PD could be obtained virtually in any scenario by placing lightweight wearable sensors in the patient's clothes and connecting them to a medical database through mobile devices such as cell phones or tablets. Technologies exist to collect huge amounts of patient data not only during regular medical visits but also at home during activities of daily life. These data could be fed into intelligent algorithms to first discriminate relevant threatening conditions, adjust medications based on online obtained physical deficits, and facilitate strategies to modify disease progression. A major impact of this approach lies in its efficiency, by maximizing resources and drastically improving the patient experience. The patient participates actively in disease management via combined objective device- and self-assessment and by sharing information within both medical and peer groups. Here, we review and discuss the existing wearable technologies and the Internet-of-Things concept applied to PD, with an emphasis on how this technological platform may lead to a shift in paradigm in terms of diagnostics and treatment.

An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things

Routing in communication networks involves the indirection from a persistent name (or ID) to a locator and delivering packets based upon the locator. In a large-scale, highly dynamic network, the ID-to-locator mappings are both large in number, and change often. Traditional routing protocols require high overhead to keep these in directions up-to-date. In this paper, we propose Weak State Routing (WSR), a routing mechanism for large-scale highly dynamic networks. WSR's novelty is that it uses random directional walks biased occasionally by weak indirection state information in intermediate nodes. The indirection state information is weak, i.e. interpreted not as absolute truth, but as probabilistic hints. Nodes only have partial information about the region a destination node is likely to be. This method allows us to aggregate information about a number of remote locations in a geographic region. In other words, the state information maps a set-of-IDs to a it geographical region. The intermediate nodes receiving the random walk use a method similar to longest-prefix-match in order to prioritize their mappings to decide how to bias and forward the random walk. WSR can also be viewed as an unstructured distributed hashing technique. WSR displays good rare-object recall with scalability properties similar to structured DHTs, albeit with more tolerance to dynamism and without constraining the degree distribution of the underlying network.Through simulations, we show that WSR offers a high packet delivery ratio, more than 98%. The control packet overhead incurred in the network scales as O(N) for N-node networks. The number of mappings stored in the network appears to scale as Θ(N(3/2)). We compare WSR with Dynamic Source Routing (DSR) and geographic forwarding (GPSR) combined with Grid Location Service (GLS). Our results indicate that WSR delivers more packets with less overhead at the cost of increased path length.

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Weak state routing for large scale dynamic networks

WiFi-enabled buses and stops may form the backbone of a metropolitan delay-tolerant network, which exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real-time information. This paper studies the routing problem in such a network. Assuming that the bus schedule is known, we maximize the delivery probability by a given deadline for each packet. Our approach takes the randomness into account, which stems from road traffic conditions, passengers boarding and alighting, and other factors that affect bus mobility. In this sense, this paper is one of the first to tackle quasi-deterministic mobility scenarios. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: 1) minimizing the expected traversal time over our graph; 2) maximizing the delivery probability over an infinite time-horizon; and 3) a recently proposed heuristic based on bus frequencies. We show that our optimal algorithm shows the best performance, but it essentially reduces to minimizing the expected traversal time. When transmissions frequently fail (more than half of the times), the algorithm behaves similarly to a heuristic that maximizes the delivery probability over an infinite time horizon. For reliable transmissions and values of deadlines close to the expected delivery time, the multicopy extension requires only ten copies to almost reach the performance of the costly flooding approach.

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Timely Data Delivery in a Realistic Bus Network

DMME is a distributed architecture that implements mobility management for next-generation cellular systems. It has been designed to serve as a scalable and cost-effective drop-in replacement for the Long Term Evolution (LTE) mobility management entity (MME). DMME is an example of a flexible control plane architecture that can be deployed incrementally across operator networks: processing locality is obtained by assigning control plane events to a local DMME replica and by allowing the transparent migration of control plane state across the different replicas as the users move. We evaluate the DMME scheme via analysis and simulation under several deployment scenarios, using mobility patterns drawn from both synthetic models and traces collected in a production network. Our analysis shows that DMME can achieve performances that are comparable with a centralized, server-based infrastructure in terms of system availability and signaling delay. Furthermore, we propose and evaluate a set of heuristics based on user behavior that specify the allocation policy of DMME instances over the available replicas. We also report preliminary performance figures from our DMME prototype implementation. Our results confirm that distributed architectures are a viable choice to reliably support high-throughput, latency-sensitive control plane functions such as cellular mobility management. © 2012 Alcatel-Lucent.

DMME: A distributed LTE mobility management entity

As Internet of Things (IoT) becomes a growing reality, more ubiquitous devices are embedded in our daily lives, serving us in a broad range of purposes in everyday life from: personal healthcare to home automation to tailored smart city services. These devices primarily collect data that is about or produced by people, be it street noise level of a neighbourhood, or the energy footprint of an individual's home or her location and other situational context. As this unprecedented amount of data is collected, we are challenged with one fundamental research question: who owns this data and who should have access to it? Specifically, the emergent of the Human Data Interaction (HDI) topic which aims to put the human at the centre of the data driven industry, calls attention to the IoT community to address the data ownership aspect more carefully. In this note, we offer a reflection on the challenges that IoT faces in regards to the data ownership in HDI and advocate the roles that both ordinary people and industries must play to best answer those challenges in shaping the IoT landscape.

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Human Data Interaction in IoT: The ownership aspect

We present eSense - an open and multi-sensory in-ear wearable platform for personal-scale behaviour analytics. eSense is a true wireless stereo (TWS) earbud and supports dual-mode Bluetooth and Bluetooth Low Energy. It is also augmented with a 6-axis in-ertial measurement unit and a microphone. We demonstrate the eSense platform, the data exploration tool with the open APIs for the real-time visualisation of multi-modal sensory data, and its manifestation in a 360° workplace well-being application.

Utku Günay Acer

Papers

Weak state routing for large scale dynamic networks

Timely Data Delivery in a Realistic Bus Network

DMME: A distributed LTE mobility management entity

Human Data Interaction in IoT: The ownership aspect

eSense: Open Earable Platform for Human Sensing