8,055 research outputs found
Comparison of CSMA based MAC protocols of wireless sensor networks
Energy conservation has been an important area of interest in Wireless Sensor
networks (WSNs). Medium Access Control (MAC) protocols play an important role
in energy conservation. In this paper, we describe CSMA based MAC protocols for
WSN and analyze the simulation results of these protocols. We implemented
S-MAC, T-MAC, B-MAC, B-MAC+, X-MAC, DMAC and Wise-MAC in TOSSIM, a simulator
which unlike other simulators simulates the same code running on real hardware.
Previous surveys mainly focused on the classification of MAC protocols
according to the techniques being used or problem dealt with and presented a
theoretical evaluation of protocols. This paper presents the comparative study
of CSMA based protocols for WSNs, showing which MAC protocol is suitable in a
particular environment and supports the arguments with the simulation results.
The comparative study can be used to find the best suited MAC protocol for
wireless sensor networks in different environments.Comment: International Journal of AdHoc Network Systems, Volume 2, Number 2,
April 201
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
Sensor networks potentially feature large numbers of nodes that can sense
their environment over time, communicate with each other over a wireless
network, and process information. They differ from data networks in that the
network as a whole may be designed for a specific application. We study the
theoretical foundations of such large scale sensor networks, addressing four
fundamental issues- connectivity, capacity, clocks and function computation.
To begin with, a sensor network must be connected so that information can
indeed be exchanged between nodes. The connectivity graph of an ad-hoc network
is modeled as a random graph and the critical range for asymptotic connectivity
is determined, as well as the critical number of neighbors that a node needs to
connect to. Next, given connectivity, we address the issue of how much data can
be transported over the sensor network. We present fundamental bounds on
capacity under several models, as well as architectural implications for how
wireless communication should be organized.
Temporal information is important both for the applications of sensor
networks as well as their operation.We present fundamental bounds on the
synchronizability of clocks in networks, and also present and analyze
algorithms for clock synchronization. Finally we turn to the issue of gathering
relevant information, that sensor networks are designed to do. One needs to
study optimal strategies for in-network aggregation of data, in order to
reliably compute a composite function of sensor measurements, as well as the
complexity of doing so. We address the issue of how such computation can be
performed efficiently in a sensor network and the algorithms for doing so, for
some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE
Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications
In recent years, the networks of low-power devices have gained popularity.
Typically these devices are wireless and interact to form large networks such
as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable
Computing, and Wireless Sensor Networks. The collaboration among these devices
is a key to achieving the full potential of these networks. A major problem in
this field is to guarantee robust communication between elements while keeping
the whole network energy efficient. In this paper, we introduce an extended and
improved emergent broadcast slot (EBS) scheme, which facilitates collaboration
for robust communication and is energy efficient. In the EBS, nodes
communication unit remains in sleeping mode and are awake just to communicate.
The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up
window in partially overlapped manner within each duty-cycle to avoid message
collisions. We show the theoretical convergence behavior of the scheme, which
is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa
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
A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks
In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs
Design Aspects of An Energy-Efficient, Lightweight Medium Access Control Protocol for Wireless Sensor Networks
This document gives an overview of the most relevant design aspects of the lightweight medium access control (LMAC) protocol [16] for wireless sensor networks (WSNs). These aspects include selfconfiguring and localized operation of the protocol, time synchronization in multi-hop networks, network setup and strategies to reduce latency.\ud
The main goal in designing a MAC protocol for WSNs is to minimize energy waste - due to collisions of messages and idle listening - , while limiting latency and loss of data throughput. It is shown that the LMAC protocol performs well on energy-efficiency and delivery ratio [19] and can\ud
ensure a long-lived, self-configuring network of battery-powered wireless sensors.\ud
The protocol is based upon scheduled access, in which each node periodically gets a time slot, during which it is allowed to transmit. The protocol does not depend on central managers to assign time slots to nodes.\ud
WSNs are assumed to be multi-hop networks, which allows for spatial reuse of time slots, just like frequency reuse in GSM cells. In this document, we present a distributed algorithm that allows nodes to find unoccupied time slots, which can be used without causing collision or interference to other nodes. Each node takes one time slot in control to\ud
carry out its data transmissions. Latency is affected by the actual choice of controlled time slot. We present time slot choosing strategies, which ensure a low latency for the most common data traffic in WSNs: reporting of sensor readings to central sinks
Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks
Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the networkâs energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of âvirtual clusters,â forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The âdistributed formationâ algorithm automatically forms and classifies the virtual clusters. The âround robin sample schemeâ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption
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