436 research outputs found
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
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
Coverage Protocols for Wireless Sensor Networks: Review and Future Directions
The coverage problem in wireless sensor networks (WSNs) can be generally
defined as a measure of how effectively a network field is monitored by its
sensor nodes. This problem has attracted a lot of interest over the years and
as a result, many coverage protocols were proposed. In this survey, we first
propose a taxonomy for classifying coverage protocols in WSNs. Then, we
classify the coverage protocols into three categories (i.e. coverage aware
deployment protocols, sleep scheduling protocols for flat networks, and
cluster-based sleep scheduling protocols) based on the network stage where the
coverage is optimized. For each category, relevant protocols are thoroughly
reviewed and classified based on the adopted coverage techniques. Finally, we
discuss open issues (and recommend future directions to resolve them)
associated with the design of realistic coverage protocols. Issues such as
realistic sensing models, realistic energy consumption models, realistic
connectivity models and sensor localization are covered
QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK
A Wireless Sensor Networks (WSN) is composed of a large number of low-powered
sensor nodes that are randomly deployed to collect environmental data. In a WSN,
because of energy scarceness, energy efficient gathering of sensed information is one
of the most critical issues. Thus, most of the WSN routing protocols found in the
literature have considered energy awareness as a key design issue. Factors like
throughput, latency and delay are not considered as critical issues in these protocols.
However, emerging WSN applications that involve multimedia and imagining sensors
require end-to-end delay within acceptable limits. Hence, in addition to energy
efficiency, the parameters (delay, packet loss ratio, throughput and coverage) have
now become issues of primary concern. Such performance metrics are usually
referred to as the Quality of Service (QoS) in communication systems. Therefore, to
have efficient use of a sensor node’s energy, and the ability to transmit the imaging
and multimedia data in a timely manner, requires both a QoS based and energy
efficient routing protocol. In this research work, a QoS based energy efficient routing
protocol for WSN is proposed. To achieve QoS based energy efficient routing, three
protocols are proposed, namely the QoS based Energy Efficient Clustering (QoSEC)
for a WSN, the QoS based Energy Efficient Sleep/Wake Scheduling (QoSES) for a
WSN, and the QoS based Energy Efficient Mobile Sink (QoSEM) based Routing for a
Clustered WSN.
Firstly, in the QoSEC, to achieve energy efficiency and to prolong
network/coverage lifetime, some nodes with additional energy resources, termed as
super-nodes, in addition to normal capability nodes, are deployed. Multi-hierarchy
clustering is done by having super-nodes (acting as a local sink) at the top tier, cluster
head (normal node) at the middle tier, and cluster member (normal node) at the lowest
tier in the hierarchy. Clustering within normal sensor nodes is done by optimizing the
network/coverage lifetime through a cluster-head-selection algorithm and a
sleep/wake scheduling algorithm. QoSEC resolves the hot spot problem and prolongs
network/coverage lifetime.
Secondly, the QoSES addressed the delay-minimization problem in sleep/wake
scheduling for event-driven sensor networks for delay-sensitive applications. For this
purpose, QoSES assigns different sleep/wake intervals (longer wake interval) to
potential overloaded nodes, according to their varied traffic load requirement defined
a) by node position in the network, b) by node topological importance, and c) by
handling burst traffic in the proximity of the event occurrence node. Using these
heuristics, QoSES minimizes the congestion at nodes having heavy traffic loads and
ultimately reduces end-to-end delay while maximizing the throughput.
Lastly, the QoSEM addresses hot spot problem, delay minimization, and QoS
assurance. To address hot-spot problem, mobile sink is used, that move in the network
to gather data by virtue of which nodes near to the mobile sink changes with each
movement, consequently hot spot problem is minimized. To achieve delay
minimization, static sink is used in addition to the mobile sink. Delay sensitive data is
forwarded to the static sink, while the delay tolerant data is sent through the mobile
sink. For QoS assurance, incoming traffic is divided into different traffic classes and
each traffic class is assigned different priority based on their QoS requirement
(bandwidth, delay) determine by its message type and content. Furthermore, to
minimize delay in mobile sink data gathering, the mobile sink is moved throughout
the network based on the priority messages at the nodes. Using these heuristics,
QoSEM incur less end-to-end delay, is energy efficient, as well as being able to
ensure QoS.
Simulations are carried out to evaluate the performance of the proposed protocols
of QoSEC, QoSES and QoSEM, by comparing their performance with the established
contemporary protocols. Simulation results have demonstrated that when compared
with contemporary protocols, each of the proposed protocol significantly prolong the
network and coverage lifetime, as well as improve the other QoS routing parameters,
such as delay, packet loss ratio, and throughput
Clustered wireless sensor networks
The study of topology in randomly deployed wireless sensor networks (WSNs) is important in addressing the fundamental issue of stochastic coverage resulting from randomness in the deployment procedure and power management algorithms. This dissertation defines and studies clustered WSNs, WSNs whose topology due to the deployment procedure and the application requirements results in the phenomenon of clustering or clumping of nodes. The first part of this dissertation analyzes a range of topologies of clustered WSNs and their impact on the primary sensing objectives of coverage and connectivity. By exploiting the inherent advantages of clustered topologies of nodes, this dissertation presents techniques for optimizing the primary performance metrics of power consumption and network capacity. It analyzes clustering in the presence of obstacles, and studies varying levels of redundancy to determine the probability of coverage in the network. The proposed models for clustered WSNs embrace the domain of a wide range of topologies that are prevalent in actual real-world deployment scenarios, and call for clustering-specific protocols to enhance network performance. It has been shown that power management algorithms tailored to various clustering scenarios optimize the level of active coverage and maximize the network lifetime. The second part of this dissertation addresses the problem of edge effects and heavy traffic on queuing in clustered WSNs. In particular, an admission control model called directed ignoring model has been developed that aims to minimize the impact of edge effects in queuing by improving queuing metrics such as packet loss and wait time
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