Message Relay Research Articles

Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integration in Precision Medicine.

Machine learning (ML) is being ubiquitously incorporated into everyday products such as Internet search, email spam filters, product recommendations, image classification, and speech recognition. New approaches for highly integrated manufacturing and automation such as the Industry 4.0 and the Internet of things are also converging with ML methodologies. Many approaches incorporate complex artificial neural network architectures and are collectively referred to as deep learning (DL) applications. These methods have been shown capable of representing and learning predictable relationships in many diverse forms of data and hold promise for transforming the future of omics research and applications in precision medicine. Omics and electronic health record data pose considerable challenges for DL. This is due to many factors such as low signal to noise, analytical variance, and complex data integration requirements. However, DL models have already been shown capable of both improving the ease of data encoding and predictive model performance over alternative approaches. It may not be surprising that concepts encountered in DL share similarities with those observed in biological message relay systems such as gene, protein, and metabolite networks. This expert review examines the challenges and opportunities for DL at a systems and biological scale for a precision medicine readership.

Amateur radio communications in a disaster preparedness simulation When all else fails . . . amateur radio.

During natural disasters, communications can be disrupted, which negatively impacts response time of first responders thus diminishing the level of care provided to disaster victims. In the fall of 2014, as part of a larger community-based participatory research study, the Tarleton Area Amateur Radio Club (TAARC) joined the Department of Nursing, Tarleton State University, and provided amateur radio communications during a disaster preparedness simulation. The simulation was conducted to determine the ability of the university to provide rapid response and render quality, acute healthcare to its neighbors during a natural disaster. The primary goals of the TAARC were to assess the ability to quickly establish radio communications, accurately relay messages, and establish rapport and affiliation between each facility commander and the amateur radio operators. It was determined that communication was key to provide quality care, and the inclusion of amateur radio operators in the simulation helped ensure rapid response times and rapid transport of critical victims.

Control of Message Transmission in Delay/Disruption Tolerant Network

Message in delay/disruption tolerant network (DTN) is often transmitted in the store/carry/forward mode. In this mode, the transmission process includes two important steps (beaconing and forwarding). Both processes consume much energy which is very precious for the wireless application. At present, most of the works considers just one step in the controlling process (some ignore the beaconing control and some ignore the forwarding control). In addition, state-of-the-art works often assume that there is only one destination for a specific message. In this paper, we consider the optimal forwarding and beaconing control problem at the same time in DTN, where multiple destinations exist. In particular, based on whether those destinations are willing to relay message for others, we consider the selfish and altruistic cases, respectively. Based on these settings, we mathematically characterize this problem as an optimal control problem. The controlling parameters are the forwarding rate and beaconing rate, respectively. Then, we solve the problem by Pontryagin’s Maximum Principle, and mathematically prove that both the optimal forwarding and beaconing policies conform to the threshold form. Next, we check the accuracy of the theoretical models by simulations based on both synthetic and real motion traces. Finally, we check the result in a real scenario with 100 students, and show that the optimal policy can really improve the performance.

BIRDS-1 CubeSat Constellation Using Compact UHF Patch Antenna

BIRDS-1 satellites, a constellation of five identical 1U CubeSats, were designed, manufactured, assembled, integrated, and tested at LASINE Laboratory, Kyutech, Japan. Students from five nations (Japan, Ghana, Mongolia, Nigeria, and Bangladesh) collaborated to develop a number of CubeSats with coordinated ground coverage, named “Joint Global Multi-Nation BIRDS,” or abbreviated as “BIRDS.” To establish the downlink communication between satellite and Earth, an UHF patch antenna was utilized. Patch antennas offer an ideal solution to Cube satellite communication requirements due to their compact dimension and lightweight. However, the limited surface area available in CubeSats, conventional UHF and VHF patch antennas cannot be used. In this paper, a compact coaxial fed UHF (437.375 MHz) patch antenna system for 1U BIRDS-1 CubeSat (small satellite) is presented. The proposed antenna consists of a spiral meander line patch at the top side and partial ground plane another side of the substrate. A shorting pin has also been utilized to change the resonance to the required UHF band. For the intended 1U BIRDS-1 application, the goal is to mount on satellite body within a limited area of 1U BIRDS-1 satellite. The proposed antenna dimension ( $0.105\lambda \times 0.047\lambda \times 0.002 \lambda $ at 437.375 MHz) and characteristics are compatible with any CubeSat standard structure. A prototype of the antenna was developed with a 1.57-mm-thick single layer Roger’s substrate having a relative permittivity of 2.2, and measured results are consistent with simulation. The proposed UHF antenna has integrated and tested with 1U BIRDS-1 satellite. Finally, the satellite was successfully launched on June 3, 2017, from the John F. Kennedy Space Center, the USA at Low Earth Orbit for earth observations, message relay, space environment, and technology demonstration through the International Space Station.

Cancer drug start-up Navire sets sail

BridgeBio Pharma and the University of Texas MD Anderson Cancer Center have launched a new company called Navire Pharma. Backed by $30 million in financing from BridgeBio, Navire will develop small-molecule inhibitors of an enzyme called SHP2, implicated in many cancers. “I’ve been working on this protein for longer than I want to admit, so this is exciting,” says Benjamin G. Neel, director of New York University’s Perlmutter Cancer Center. Neel, who has studied the proteins since 1992, is a scientific cofounder of Navire and chair of its scientific advisory board. SHP2 belongs to the tyrosine phosphatase family of proteins, which help relay chemical messages controlling cell growth and division. MD Anderson is contributing its SHP2 inhibitors to the collaboration and will continue to spearhead studies until a compound is ready for human trials. Researchers think that blocking SHP2 could halt the growth of tumors spurred by malfunctions in the

Suppressive Fair Buffer Management Policy for Intermittently Connected Mobile Ad Hoc Networks

We propose a suppressive fair buffer management policy for intermittently connected mobile ad-hoc networks. So far, several buffer management policies have been considered. These existing buffer management policies assume that all stored messages can be replaced when nodes encounter each other. Buffer management policies, however, can prioritize messages stored at the receiving side over those at the sending side. By doing this, message transmissions are suppressive, and thus energy consumption in terms of sending messages is reduced. Moreover, our proposed policy gives relay messages with a small number of message copies to high priority. Specifically, our proposed policy maintains a sharing of buffer spaces that is as fair as possible. In this paper, we reveal how the suppression of receiving messages affects the system performance compared with existing buffer management policies. Through simulation experiments, we show that the suppressive fair buffer management policy improves energy consumption without largely degrading the delivery failure probability and the mean delivery delay.

Motes enhance data recovery from satellite-relayed biologgers and can facilitate collaborative research into marine habitat utilization

BackgroundThe fields of biologging and telemetry have triggered significant advances in the understanding of animal behavior, physiological ecology and habitat utilization. Biologging devices (“tags”) can also measure aspects of the physical and biological characteristics of the animals’ environment. As marine ecosystems are less accessible than terrestrial ones and marine animals more elusive and difficult to study, data collected by tags attached to marine animals often have to be relayed via satellite. However, satellite availability is not continuous and decreases with decreasing latitude. Consequently, collection of sufficient data is even more challenging in the tropics and mid-latitudes than at the poles. To overcome this limitation and increase data throughput from biologgers, new land-based receiving stations (called Motes) that can receive, log and relay messages from devices transmitting on the Argos satellite frequency have been developed.MethodsWe investigated the performance of Motes as enhancers of recovery of signals transmitted by tags normally destined for satellite relay. We quantified Mote reception range, coverage area, data throughput and data corruption rates and examined factors that might impact these parameters. To do so, we used all signals detected by two arrays of Motes installed in the Hawaiian Islands and in Southern California between latitudes 22 and 33°N. Second, using data from 12 sharks and 12 whales tagged near the two Mote arrays, we assessed how increased data recovery translated into improved ability to interpret the behavior of the tagged animals.ResultsMotes were capable of receiving up to 100% of messages transmitted within their reception range and overall presented a ~three- to fivefold increase in data message recovery compared to satellites alone. Message reception performance of Motes depended on their coverage area which in turn was affected by station elevation, the presence or not of obstacles within their line of sight, and the directionality of antennas.ConclusionsThe increased quantity of data enabled improved biological interpretation of the animals studied. As such, Motes can improve our knowledge of marine animals’ ecology in relation to their physical and biological environments. Large-scale Mote arrays could potentially facilitate collaborative multi-disciplinary research projects, resulting in better ecosystem conservation and management.

A new cooperative communication algorithm for improving connectivity in the event of network failure in VANETs

Communication in Vehicular Ad-Hoc Networks (VANETs) is frequently disrupted by high mobility of nodes, obstacles, and interference-prone links. The communication link between nodes can be maintained using cooperative communication techniques where nodes collaborate with one another to increase the network performance. Implementation of cooperative communication, which requires helpful nodes to collaborate with others, is a difficult task in VANETs due to their inherent characteristics. Selection of a cooperative node which will help during the retransmission process is the most crucial work in the cooperative communication process considering the dynamic nature of nodes. In this study, we formulate a game-theoretic relay selection protocol for MAC-level retransmission, where every node plans to maximize their received incentives, which is determined by an incentive function. Therefore, cooperative neighboring nodes form tree structures to the destination node from transmitter node by using the proposed algorithm, NGOMA. The distributed incentive function stores promiscuous packets in nodes and forms a tree architecture with cooperative nodes to relay messages to the recipient node from the source node in times of packet-loss events. The network formed by the NGOMA protocol by the source and destination node with relay nodes, converges into a Nash network. Numerical results show that NGOMA, which allows nodes to cooperatively store and transmit lost packets to the recipients, reduces the MAC-level retransmission delay by 63% compared to a non-cooperative function, which does not cooperatively relay messages.

Data Collection Strategy in Low Duty Cycle Wireless Sensor Networks with Mobile Sink

The lifetime of wireless sensor networks can be improved by imposing low duty cycle, but doing so could not solve unbalanced energy consumption and will increase transmission latency. To avoid this, this paper gives a new method to collect data by mobile sink. The proper data collection route is selected according to the sink speed and buffer size of the sensors. The sensors only wake up when the sink approaches them. When certain sensors detect an emergency, the sink catches the message quickly and moves to the hotspot to decrease message relay in the network. The result of simulation by OPNET shows that this protocol can reduce transmission data in the network and prolong the network lifetime.

Determinants of Preferences for Advertisement and Communication in the Promotion of Anti-Malaria Products in Ibadan, Southwestern Nigeria

One of the strategies for promoting malaria prevention and control globally is advertisement of anti-malaria products. This study was designed to determine users’ preferences for style of advertisement and communication of anti-malaria products in Ibadan. Data collection involved twelve Key Informant Interviews and 500 copies of a questionnaire. Radio was the most preferred and most accessible medium of advert in both rural and urban areas. A large majority (86.4%) of rural dwellers preferred advertisements in form of speeches, house-to-house campaigns, face-to-face counselling and rallies. Whereas, advertisement in forms of drama (44.0%) and music (16.0%) were preferred by the urban dwellers. Results show that advertisements and communication programs on anti-malaria products do not relay messages on drug reaction and its treatment, and cost of anti-malaria products. Hence, advertisements and communicative programmes for controlling malaria would be more effective if the social and environmental factors influencing preferences for advertisement are put into consideration.

VDNet: an infrastructure-less UAV-assisted sparse VANET system with vehicle location prediction

Vehicular Ad Hoc Network (VANET) has been a hot topic in the past few years. Compared with vehicular networks where vehicles are densely distributed, sparse VANET have more realistic significance. The first challenge of a sparse VANET system is that the network suffers from frequent disconnections. The second challenge is to adapt the transmission route to the dynamic mobility pattern of the vehicles. Also, some infrastructural requirements are hard to meet when deploying a VANET widely. Facing these challenges, we devise an infrastructure-less unmanned aerial vehicle (UAV) assisted VANET system called Vehicle-Drone hybrid vehicular ad hoc Network (VDNet), which utilizes UAVs, particularly quadrotor drones, to boost vehicle-to-vehicle data message transmission under instructions conducted by our distributed vehicle location prediction algorithm. VDNet takes the geographic information into consideration. Vehicles in VDNet observe the location information of other vehicles to construct a transmission route and predict the location of a destination vehicle. Some vehicles in VDNet equips an on-board UAV, which can deliver data message directly to destination, relay messages in a multi-hop route, and collect location information while flying above the traffic. The performance evaluation shows that VDNet achieves high efficiency and low end-to-end delay with controlled communication overhead. Copyright © 2016 John Wiley & Sons, Ltd.

A Study of LoRa: Long Range & Low Power Networks for the Internet of Things

LoRa is a long-range, low-power, low-bitrate, wireless telecommunications system, promoted as an infrastructure solution for the Internet of Things: end-devices use LoRa across a single wireless hop to communicate to gateway(s), connected to the Internet and which act as transparent bridges and relay messages between these end-devices and a central network server. This paper provides an overview of LoRa and an in-depth analysis of its functional components. The physical and data link layer performance is evaluated by field tests and simulations. Based on the analysis and evaluations, some possible solutions for performance enhancements are proposed.

A Disaster Management Specific Mobility Model for Flying Ad-hoc Network

The extended Mobile Ad-hoc Network architecture is a paramount research domain due to a wide enhancement of smart phone and open source Unmanned Aerial Vehicle (UAV) technology. The novelty of the current work is to design a disaster aware mobility modeling for a Flying Ad-hoc network infrastructure, where the UAV group is considered as nodes of such ecosystem. This can perform a collaborative task of a message relay, where the mobility modeling under a “Post Disaster” is the main subject of interest, which is proposed with a multi-UAV prototype test bed. The impact of various parameters like UAV node attitude, geometric dilution precision of satellite, Global Positioning System visibility, and real life atmospheric upon the mobility model is analyzed. The results are mapped with the realistic disaster situation. A cluster based mobility model using the map oriented navigation of nodes is emulated with the prototype test bed.

Using network coding to achieve the capacity of deterministic relay networks with relay messages

AbstractIn this paper, we derive the capacity of the deterministic relay networks with relay messages. We consider a network that consists of five nodes, four of which can only communicate via the fifth one. However, the fifth node is not merely a relay as it may exchange private messages with the other network nodes. First, we develop an upper bound on the capacity region based on the notion of a single‐sided genie. In the course of the achievability proof, we also derive the deterministic capacity of a four‐user relay network (without private messages at the relay). The capacity achieving schemes use a combination of two network coding techniques: the simple ordering scheme and detour scheme. In the simple ordering scheme, we order the transmitted bits at each user such that the bi‐directional messages will be received at the same channel level at the relay, while the basic idea behind the detour scheme is that some parts of the message follow an indirect paths to their respective destinations. This paper, therefore, serves to show that user cooperation and network coding can enhance throughput, even when the users are not directly connected to each other. Finally, we make a conjecture about the capacity region of the general K‐node relay network with relay messages. Copyright © 2016 John Wiley & Sons, Ltd.

Cooperative Diamond Channel With Energy Harvesting Nodes

We consider the energy harvesting diamond channel, where the source and two relays harvest energy from nature and the physical layer is modeled as a concatenation of a broadcast and a multiple access channel. Since the broadcast channel is degraded, one of the relays has the message of the other relay and the multiple access channel can be modeled as a cooperative multiple access channel with common data. We find the optimal offline transmit power and rate allocations that maximize the end-to-end throughput. For the broadcast side, we show that there exists an optimal source power allocation, which is equal to the single-user optimal power allocation for the source energy arrivals. We then show that the fraction of the power spent on each broadcast link depends on the energy arrivals for the relays. For the multiple access side with no co-operation, with fixed source rates, we show that the problem can be cast as a multiple access channel with both data and energy arrivals and can be formulated in terms of data transmission rates only. We use a dual decomposition method to solve the overall problem efficiently. Finally, we focus on the diamond channel with co-operative multiple access capacity region and find the optimal rates and powers using a decomposition into inner and outer maximization problems.

A TOPIC MODELING BASED REPRESENTATION TO DETECT TWEET LOCATIONS. EXAMPLE OF THE EVENT ”JE SUIS CHARLIE”

Abstract. Social Networks became a major actor in information propagation. Using the Twitter popular platform, mobile users post or relay messages from different locations. The tweet content, meaning and location, show how an event-such as the bursty one ”JeSuisCharlie”, happened in France in January 2015, is comprehended in different countries. This research aims at clustering the tweets according to the co-occurrence of their terms, including the country, and forecasting the probable country of a non-located tweet, knowing its content. First, we present the process of collecting a large quantity of data from the Twitter website. We finally have a set of 2,189 located tweets about “Charlie”, from the 7th to the 14th of January. We describe an original method adapted from the Author-Topic (AT) model based on the Latent Dirichlet Allocation (LDA) method. We define an homogeneous space containing both lexical content (words) and spatial information (country). During a training process on a part of the sample, we provide a set of clusters (topics) based on statistical relations between lexical and spatial terms. During a clustering task, we evaluate the method effectiveness on the rest of the sample that reaches up to 95% of good assignment. It shows that our model is pertinent to foresee tweet location after a learning process.

CONCOR: context-aware community-oriented routing for intermittently connected network

Delay-Tolerant Networks (DTNs) are characterized by time-varying and partially connected network topology. In such networks, mobility of node may be by virtue of its carrier. Social beings such as humans may act as a carrier of mobile nodes, and therefore mobility pattern of node follows a social-based movement model. Due to intermittent connectivity, end-to-end path between source and destination is rare and therefore message delivery is a challenge in such networks. In this paper, we present a new routing approach, context-aware community-oriented routing (CONCOR) that exploits the community and the context awareness of nodes, for efficient message delivery. Nodes with a common point of interest form a dynamic community. We have identified a set of node’s attribute (context) and formulated a utility function to determine its capability to deliver a message. CONCOR is a multihop routing approach exploiting the nodes as message relays (store-carry-forward). Through simulation, we validated the effectiveness of node’s attributes in estimation of message delivery probability. The simulations were done for our approach using the social movement-based data set on Opportunistic Network Environment (ONE) simulator. We compared our approach with dynamic social grouping (DSG)-based routing and context-aware routing(CAR) on three metrics viz. message delivery ratio, message traffic ratio and average message delay. We found that the results of our approach outperforms the DSG and CAR on all the three metrics.

Solving Scalability Problems on Secure RFID Grouping-Proof Protocol

Scalable grouping-proof protocol has broad and various RFID applications. It generates a proof to confirm scalable multiple co-existing tags within timeout period. The scalability problems focus on performance of generating the scalable grouping-proof, such as messages relay, collision, exhaustive search and computation load of lightweight tag. No integrated solution is presented to scalability problems on RFID grouping-proof. In this paper, a novel protocol is proposed to solve scalability problems and offer secure properties including the mutual authentication, replay attack prevention, forward security, anonymity, and forge proof resistance. In addition, the pseudo identity with direct search is used to provide the privacy and unlinkability. The proposed mechanism adopts broadcast and pre-ordering responses scheme to improve system performance. The achievement is based on reducing the number of message relay, avoiding collision of responses and computing simultaneously of multiple lightweight tags. The experimental results of simulation show that the scalability requirements on grouping-proof protocol are satisfied with our protocol. Within timeout period of 400 ms, the proposed protocol could provide a proof with a scale up to about 130 and 600 tags under data rate of 105 and 640 kbps. The scalability performance of the proposed protocol is more than 3 times better than the other grouping-proof protocols.

ML-SOR: Message routing using multi-layer social networks in opportunistic communications

Opportunistic networks are a generalization of DTNs in which disconnections are frequent and encounter patterns between mobile devices are unpredictable. In such scenarios, message routing is a fundamental issue. Social-based routing protocols usually exploit the social information extracted from the history of encounters between mobile devices to find an appropriate message relay. Protocols based on encounter history, however, take time to build up a knowledge database from which to take routing decisions. While contact information changes constantly and it takes time to identify strong social ties, other types of ties remain rather stable and could be exploited to augment available partial contact information. In this paper, we start defining a multi-layer social network model combining the social network detected through encounters with other social networks and investigate the relationship between these social network layers in terms of node centrality, community structure, tie strength and link prediction. The purpose of this analysis is to better understand user behavior in a multi-layered complex network combining online and offline social relationships. Then, we propose a novel opportunistic routing approach ML-SOR (Multi-layer Social Network based Routing) which extracts social network information from such a model to perform routing decisions. To select an effective forwarding node, ML-SOR measures the forwarding capability of a node when compared to an encountered node in terms of node centrality, tie strength and link prediction. Trace driven simulations show that a routing metric combining social information extracted from multiple social network layers allows users to achieve good routing performance with low overhead cost.

An Author-Topic based Approach to Cluster Tweets and Mine their Location

Social Networks became a major actor in information propagation. Using the Twitter popular platform, mobile users post or relay messages from different locations. The tweet content, meaning and location show how an event-such as the bursty one “JeSuisCharlie”’ happened in France in January 2015 is comprehended in different countries. This research aims at clustering the tweets according to the co-occurrence of their terms, including the country, and forecasting the probable country of a non located tweet, knowing its content. First, we present the process of collecting a large quantity of data from the Twitter website. We finally have a set of 2.189 located tweets about “Charlie”, from the 7th to the 14th of January. We describe an original method adapted from the Author-Topic (AT) model based on the Latent Dirichlet Allocation method (LDA). We define a homogeneous space containing both lexical content (words) and spatial information (country). During a training process on a part of the sample, we provide a set of clusters (topics) based on statistical relations between lexical and spatial terms. During a clustering task, we evaluate the method effectiveness on the rest of the sample that reaches up to 95% of good assignment.