8,973 research outputs found
The Bus Goes Wireless: Routing-Free Data Collection with QoS Guarantees in Sensor Networks
Abstract—We present the low-power wireless bus (LWB), a new communication paradigm for QoS-aware data collection in lowpower sensor networks. The LWB maps all communication onto network floods by using Glossy, an efficient flooding architecture for wireless sensor networks. Therefore, unlike current solutions, the LWB requires no information of the network topology, and inherently supports networks with mobile nodes and multiple data sinks. A LWB prototype implemented in Contiki guarantees bounded end-to-end communication delay and duplicate-free, inorder packet delivery—key QoS requirements in many control and mission-critical applications. Experiments on two testbeds demonstrate that the LWB prototype outperforms state-of-theart data collection and link layer protocols, in terms of reliability and energy efficiency. For instance, we measure an average radio duty cycle of 1.69 % and an overall data yield of 99.97 % in a typical data collection scenario with 85 sensor nodes on Twist. I
PluralisMAC: a generic multi-MAC framework for heterogeneous, multiservice wireless networks, applied to smart containers
Developing energy-efficient MAC protocols for lightweight wireless systems has been a challenging task for decades because of the specific requirements of various applications and the varying environments in which wireless systems are deployed. Many MAC protocols for wireless networks have been proposed, often custom-made for a specific application. It is clear that one MAC does not fit all the requirements. So, how should a MAC layer deal with an application that has several modes (each with different requirements) or with the deployment of another application during the lifetime of the system? Especially in a mobile wireless system, like Smart Monitoring of Containers, we cannot know in advance the application state (empty container versus stuffed container). Dynamic switching between different energy-efficient MAC strategies is needed. Our architecture, called PluralisMAC, contains a generic multi-MAC framework and a generic neighbour monitoring and filtering framework. To validate the real-world feasibility of our architecture, we have implemented it in TinyOS and have done experiments on the TMote Sky nodes in the w-iLab.t testbed. Experimental results show that dynamic switching between MAC strategies is possible with minimal receive chain overhead, while meeting the various application requirements (reliability and low-energy consumption)
Powertrace: Network-level Power Profiling for Low-power Wireless Networks
Low-power wireless networks are quickly becoming a critical part of our everyday infrastructure. Power consumption is a critical concern, but power measurement and estimation is a challenge. We present Powertrace,
which to the best of our knowledge is the first system for network-level power profiling of low-power wireless systems. Powertrace uses power state tracking to estimate system power consumption and a structure called energy capsules to attribute energy consumption to activities such as packet transmissions and receptions. With Powertrace, the power consumption of a system can be broken down into individual activities which allows us to answer questions such as “How much energy is spent forwarding packets for node X?”, “How much energy
is spent on control traffic and how much on critical data?”, and “How much energy does application X account for?”. Experiments show that Powertrace is accurate to 94% of the energy consumption of a device. To
demonstrate the usefulness of Powertrace, we use it to experimentally analyze the power behavior of the proposed IETF standard IPv6 RPL routing protocol and a sensor network data collection protocol. Through using Powertrace, we find the highest power consumers and are
able to reduce the power consumption of data collection with 24%. It is our hope that Powertrace will help the community to make empirical energy evaluation a widely used tool in the low-power wireless research community toolbox
RTXP : A Localized Real-Time Mac-Routing Protocol for Wireless Sensor Networks
Protocols developed during the last years for Wireless Sensor Networks (WSNs)
are mainly focused on energy efficiency and autonomous mechanisms (e.g.
self-organization, self-configuration, etc). Nevertheless, with new WSN
applications, appear new QoS requirements such as time constraints. Real-time
applications require the packets to be delivered before a known time bound
which depends on the application requirements. We particularly focus on
applications which consist in alarms sent to the sink node. We propose
Real-Time X-layer Protocol (RTXP), a real-time communication protocol. To the
best of our knowledge, RTXP is the first MAC and routing real-time
communication protocol that is not centralized, but instead relies only on
local information. The solution is cross-layer (X-layer) because it allows to
control the delays due to MAC and Routing layers interactions. RTXP uses a
suited hop-count-based Virtual Coordinate System which allows deterministic
medium access and forwarder selection. In this paper we describe the protocol
mechanisms. We give theoretical bound on the end-to-end delay and the capacity
of the protocol. Intensive simulation results confirm the theoretical
predictions and allow to compare with a real-time centralized solution. RTXP is
also simulated under harsh radio channel, in this case the radio link
introduces probabilistic behavior. Nevertheless, we show that RTXP it performs
better than a non-deterministic solution. It thus advocates for the usefulness
of designing real-time (deterministic) protocols even for highly unreliable
networks such as WSNs
An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks
Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful
energy awareness is essential when working with these devices.
Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features.
This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols.
The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and
has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference
publications in IEEE Explore and one workshop paper
Performance Comparison of Contention- and Schedule-based MAC Protocols in Urban Parking Sensor Networks
Network traffic model is a critical problem for urban applications, mainly
because of its diversity and node density. As wireless sensor network is highly
concerned with the development of smart cities, careful consideration to
traffic model helps choose appropriate protocols and adapt network parameters
to reach best performances on energy-latency tradeoffs. In this paper, we
compare the performance of two off-the-shelf medium access control protocols on
two different kinds of traffic models, and then evaluate their application-end
information delay and energy consumption while varying traffic parameters and
network density. From the simulation results, we highlight some limits induced
by network density and occurrence frequency of event-driven applications. When
it comes to realtime urban services, a protocol selection shall be taken into
account - even dynamically - with a special attention to energy-delay tradeoff.
To this end, we provide several insights on parking sensor networks.Comment: ACM International Workshop on Wireless and Mobile Technologies for
Smart Cities (WiMobCity) (2014
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
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
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