657 research outputs found
Message and time efficient multi-broadcast schemes
We consider message and time efficient broadcasting and multi-broadcasting in
wireless ad-hoc networks, where a subset of nodes, each with a unique rumor,
wish to broadcast their rumors to all destinations while minimizing the total
number of transmissions and total time until all rumors arrive to their
destination. Under centralized settings, we introduce a novel approximation
algorithm that provides almost optimal results with respect to the number of
transmissions and total time, separately. Later on, we show how to efficiently
implement this algorithm under distributed settings, where the nodes have only
local information about their surroundings. In addition, we show multiple
approximation techniques based on the network collision detection capabilities
and explain how to calibrate the algorithms' parameters to produce optimal
results for time and messages.Comment: In Proceedings FOMC 2013, arXiv:1310.459
A Context-aware Trust Framework for Resilient Distributed Cooperative Spectrum Sensing in Dynamic Settings
Cognitive radios enable dynamic spectrum access where secondary users (SUs) are allowed to operate on the licensed spectrum bands on an opportunistic noninterference basis. Cooperation among the SUs for spectrum sensing is essential for environments with deep shadows. In this paper, we study the adverse effect of insistent spectrum sensing data falsification (ISSDF) attack on iterative distributed cooperative spectrum sensing. We show that the existing trust management schemes are not adequate in mitigating ISSDF attacks in dynamic settings where the primary user (PU) of the band frequently transitions between active and inactive states. We propose a novel context-aware distributed trust framework for cooperative spectrum sensing in mobile cognitive radio ad hoc networks (CRAHN) that effectively alleviates different types of ISSDF attacks (Always-Yes, Always-No, and fabricating) in dynamic scenarios. In the proposed framework, the SU nodes evaluate the trustworthiness of one another based on the two possible contexts in which they make observations from each other: PU absent context and PU present context. We evaluate the proposed context-aware scheme and compare it against the existing context-oblivious trust schemes using theoretical analysis and extensive simulations of realistic scenarios of mobile CRAHNs operating in TV white space. We show that in the presence of a large set of attackers (as high as 60% of the network), the proposed context-aware trust scheme successfully mitigates the attacks and satisfy the false alarm and missed-detection rates of and lower. Moreover, we show that the proposed scheme is scalable in terms of attack severity, SU network density, and the distance of the SU network to the PU transmitter
On Mobile Bluetooth Tags
This paper presents a new approach for hyper-local data sharing and delivery
on the base of discoverable Bluetooth nodes. Our approach allows customers to
associate user-defined data with network nodes and use a special mobile
application (context-aware browser) for presenting this information to mobile
users in proximity. Alternatively, mobile services can request and share local
data in M2M applications rely on network proximity. Bluetooth nodes in cars are
among the best candidates for the role of the bearing nodes.Comment: submitted to FRUCT-17 conference (http://fruct.org
How to Stop Disagreeing and Start Cooperatingin the Presence of Asymmetric Packet Loss
We consider the design of a disagreement correction protocol in multi-vehicle systems. Vehicles broadcast in real-time vital information such as position, direction, speed, acceleration, intention, etc. This information is then used to identify the risks and adapt their trajectory to maintain the highest performance without compromising the safety. To minimize the risk due to the use of inconsistent information, all cooperating vehicles must agree whether to use the exchanged information to operate in a cooperative mode or use the only local information to operate in an autonomous mode. However, since wireless communications are prone to failures, it is impossible to deterministically reach an agreement. Therefore, any protocol will exhibit necessary disagreement periods. In this paper, we investigate whether vehicles can still cooperate despite communication failures even in the scenario where communication is suddenly not available. We present a deterministic protocol that allows all participants to either operate a cooperative mode when vehicles can exchange all the information in a timely manner or operate in autonomous mode when messages are lost. We show formally that the disagreement time is bounded by the time that the communication channel requires to deliver messages and validate our protocol using NS-3 simulations. We explain how the proposed solution can be used in vehicular platooning to attain high performance and still guarantee high safety standards despite communication failures
Content distribution in vanets using network coding: The effect of disk i/o and processing o/h
Abstract—Besides safe navigation (e.g., warning of approaching vehicles), car to car communications will enable a host of new applications, ranging from office-on-the-wheel support to entertainment. One of the most promising applications is content distribution among drivers such as multi-media files and software updates. Content distribution in vehicular networks is a challenge due to network dynamics and high mobility, yet network coding was shown to efficiently handle such dynamics and to considerably enhance performance. This paper provides an in-depth analysis of implementation issues of network coding in vehicular networks. To this end, we consider general resource constraints (e.g., CPU, disk, memory) besides bandwidth, that are likely to impact the encoding and storage management operations required by network coding. We develop an abstract model of the network coding procedures and implement it in the wireless network simulator to evaluate the impact of limited resources. We then propose schemes that considerably improve the use of such resources. Our model and extensive simulation results show that network coding parameters must be carefully configured by taking resource constraints into account. I
Pheromone-based In-Network Processing for wireless sensor network monitoring systems
Monitoring spatio-temporal continuous fields using wireless sensor networks (WSNs) has emerged as a novel solution. An efficient data-driven routing mechanism for sensor querying and information gathering in large-scale WSNs is a challenging problem. In particular, we consider the case of how to query the sensor network information with the minimum energy cost in scenarios where a small subset of sensor nodes has relevant readings. In order to deal with this problem, we propose a Pheromone-based In-Network Processing (PhINP) mechanism. The proposal takes advantages of both a pheromone-based iterative strategy to direct queries towards nodes with relevant information and query- and response-based in-network filtering to reduce the number of active nodes. Additionally, we apply reinforcement learning to improve the performance. The main contribution of this work is the proposal of a simple and efficient mechanism for information discovery and gathering. It can reduce the messages exchanged in the network, by allowing some error, in order to maximize the network lifetime. We demonstrate by extensive simulations that using PhINP mechanism the query dissemination cost can be reduced by approximately 60% over flooding, with an error below 1%, applying the same in-network filtering strategy.Fil: Riva, Guillermo Gaston. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Universidad Tecnológica Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Finochietto, Jorge Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Estudios Avanzados en Ingeniería y Tecnología. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Estudios Avanzados en Ingeniería y Tecnología; Argentin
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
Infrastructure-less D2D Communications through Opportunistic Networks
Mención Internacional en el título de doctorIn recent years, we have experienced several social media blackouts, which have
shown how much our daily experiences depend on high-quality communication services.
Blackouts have occurred because of technical problems, natural disasters, hacker attacks
or even due to deliberate censorship actions undertaken by governments. In all cases,
the spontaneous reaction of people consisted in finding alternative channels and media so
as to reach out to their contacts and partake their experiences. Thus, it has clearly
emerged that infrastructured networks—and cellular networks in particular—are well
engineered and have been extremely successful so far, although other paradigms should
be explored to connect people. The most promising of today’s alternative paradigms
is Device-to-Device (D2D) because it allows for building networks almost freely, and
because 5G standards are (for the first time) seriously addressing the possibility of using
D2D communications.
In this dissertation I look at opportunistic D2D networking, possibly operating in an
infrastructure-less environment, and I investigate several schemes through modeling and
simulation, deriving metrics that characterize their performance. In particular, I consider
variations of the Floating Content (FC) paradigm, that was previously proposed in the
technical literature.
Using FC, it is possible to probabilistically store information over a given restricted
local area of interest, by opportunistically spreading it to mobile users while in the area.
In more detail, a piece of information which is injected in the area by delivering it to one
or more of the mobile users, is opportunistically exchanged among mobile users whenever
they come in proximity of one another, progressively reaching most (ideally all) users in
the area and thus making the information dwell in the area of interest, like in a sort of
distributed storage.
While previous works on FC almost exclusively concentrated on the communication
component, in this dissertation I look at the storage and computing components of FC,
as well as its capability of transferring information from one area of interest to another.
I first present background work, including a brief review of my Master Thesis activity,
devoted to the design, implementation and validation of a smartphone opportunistic
information sharing application. The goal of the app was to collect experimental data that permitted a detailed analysis of the occurring events, and a careful assessment of
the performance of opportunistic information sharing services. Through experiments, I
showed that many key assumptions commonly adopted in analytical and simulation works
do not hold with current technologies. I also showed that the high density of devices and
the enforcement of long transmission ranges for links at the edge might counter-intuitively
impair performance.
The insight obtained during my Master Thesis work was extremely useful to devise
smart operating procedures for the opportunistic D2D communications considered in this
dissertation. In the core of this dissertation, initially I propose and study a set of schemes
to explore and combine different information dissemination paradigms along with real
users mobility and predictions focused on the smart diffusion of content over disjoint
areas of interest. To analyze the viability of such schemes, I have implemented a Python
simulator to evaluate the average availability and lifetime of a piece of information, as
well as storage usage and network utilization metrics. Comparing the performance of
these predictive schemes with state-of-the-art approaches, results demonstrate the need
for smart usage of communication opportunities and storage. The proposed algorithms
allow for an important reduction in network activity by decreasing the number of data
exchanges by up to 92%, requiring the use of up to 50% less of on-device storage,
while guaranteeing the dissemination of information with performance similar to legacy
epidemic dissemination protocols.
In a second step, I have worked on the analysis of the storage capacity of probabilistic
distributed storage systems, developing a simple yet powerful information theoretical
analysis based on a mean field model of opportunistic information exchange. I have
also extended the previous simulator to compare the numerical results generated by the
analytical model to the predictions of realistic simulations under different setups, showing
in this way the accuracy of the analytical approach, and characterizing the properties of
the system storage capacity.
I conclude from analysis and simulated results that when the density of contents seeded
in a floating system is larger than the maximum amount which can be sustained by the
system in steady state, the mean content availability decreases, and the stored information
saturates due to the effects of resource contention. With the presence of static nodes, in
a system with infinite host memory and at the mean field limit, there is no upper bound
to the amount of injected contents which a floating system can sustain. However, as with
no static nodes, by increasing the injected information, the amount of stored information
eventually reaches a saturation value which corresponds to the injected information at
which the mean amount of time spent exchanging content during a contact is equal to
the mean duration of a contact.
As a final step of my dissertation, I have also explored by simulation the computing
and learning capabilities of an infrastructure-less opportunistic communication, storage and computing system, considering an environment that hosts a distributed Machine
Learning (ML) paradigm that uses observations collected in the area over which the FC
system operates to infer properties of the area. Results show that the ML system can
operate in two regimes, depending on the load of the FC scheme. At low FC load, the ML
system in each node operates on observations collected by all users and opportunistically
shared among nodes. At high FC load, especially when the data to be opportunistically
exchanged becomes too large to be transmitted during the average contact time between
nodes, the ML system can only exploit the observations endogenous to each user, which
are much less numerous. As a result, I conclude that such setups are adequate to support
general instances of distributed ML algorithms with continuous learning, only under the
condition of low to medium loads of the FC system. While the load of the FC system
induces a sort of phase transition on the ML system performance, the effect of computing
load is more progressive. When the computing capacity is not sufficient to train all
observations, some will be skipped, and performance progressively declines.
In summary, with respect to traditional studies of the FC opportunistic information
diffusion paradigm, which only look at the communication component over one area of
interest, I have considered three types of extensions by looking at the performance of FC:
over several disjoint areas of interest;
in terms of information storage capacity;
in terms of computing capacity that supports distributed learning.
The three topics are treated respectively in Chapters 3 to 5.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Claudio Ettori Casetti.- Secretario: Antonio de la Oliva Delgado.- Vocal: Christoph Somme
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