348 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
Low Duty-Cycled Wireless Sensor Networks: Connectivity and Opportunistic Routing
This thesis addresses a number of performance and design issues that
arise in a low duty-cycled wireless sensor network.
The advances in sensing technology, miniaturization and wireless
communication have led to a large number of emerging applications
using networked wireless sensors. One of the most critical design
goals is the longevity of the system. A widely accepted and
commonly used method of energy conservation is duty cycling --
sensor nodes are periodically put to sleep mode to conserve energy.
While effective in prolonging the system lifetime, duty-cycling
disrupts communication and sensing capabilities as sensors alternate
between sleep and wake modes. This not only affects network
coverage and connectivity, but also causes delay in message
delivery. A central theme of this thesis is to understand the
energy-performance trade-off and design good networking algorithms
that work well with low duty-cycled sensors. Our work thus centers
on how the performance degradation caused by duty-cycling may be
mitigated.
The first method is to add redundancy to the deployment: the more
sensors we deploy, the more we can reduce the duty cycle of
individual sensors while maintaining the system level performance.
In this context we investigate the fundamental relationship between
the amount of redundancy required vs. the achievable reduction in
duty cycle for a fixed performance criterion. We examine this
relationship in the case of asymptotic network connectivity.
A second method is to design good algorithms that effectively deal
with temporal loss of connectivity. Within this context, we first
develop a routing scheme using an optimal stochastic (also referred
to as opportunistic) routing framework, designed to work in the
presence of duty-cycling as well as unreliable wireless channels.
We then examine how the routing delay of this type of algorithms
scales compared to conventional (non-opportunistic) routing
algorithms in a limiting regime where the network becomes dense.
Lastly, for any routing algorithm to work properly there needs to be
an efficient broadcast mechanism that discovers and disseminates
topology information. In this context we develop an
analysis-emulation hybrid model that combines analytical models with
elements of numerical simulation to obtain the desired modeling
accuracy and computational efficiency.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61569/1/kimds_1.pd
A framework for energy based performability models for wireless sensor networks
A novel idea of alternating node operations between Active and Sleep modes in Wireless Sensor Network (WSN) has successfully been used to save node power consumption. The idea which started off as a simple implementation of a timer in most protocols has been improved over the years to dynamically change with traffic conditions and the nature of application area. Recently, use of a second low power radio transceiver to triggered Active/Sleep modes has also been made. Active/Sleep operation modes have also been used to separately model and evaluate performance and availability of WSNs. The advancement in technology and continuous improvements of the existing protocols and application implementation demands continue to pose great challenges to the existing performance and availability models. In this study the need for integrating performance and availability studies of WSNs in the presence of both channel and node failures and repairs is investigated. A framework that outlines and characterizes key models required for integration of performance and availability of WSN is in turn outlined. Possible solution techniques for such models are also highlighted. Finally it is shown that the resulting models may be used to comparatively evaluate energy consumption of the existing motes and WSNs as well as deriving required performance measures
The Beauty of the Commons: Optimal Load Sharing by Base Station Hopping in Wireless Sensor Networks
In wireless sensor networks (WSNs), the base station (BS) is a critical
sensor node whose failure causes severe data losses. Deploying multiple fixed
BSs improves the robustness, yet requires all BSs to be installed with large
batteries and large energy-harvesting devices due to the high energy
consumption of BSs. In this paper, we propose a scheme to coordinate the
multiple deployed BSs such that the energy supplies required by individual BSs
can be substantially reduced. In this scheme, only one BS is selected to be
active at a time and the other BSs act as regular sensor nodes. We first
present the basic architecture of our system, including how we keep the network
running with only one active BS and how we manage the handover of the role of
the active BS. Then, we propose an algorithm for adaptively selecting the
active BS under the spatial and temporal variations of energy resources. This
algorithm is simple to implement but is also asymptotically optimal under mild
conditions. Finally, by running simulations and real experiments on an outdoor
testbed, we verify that the proposed scheme is energy-efficient, has low
communication overhead and reacts rapidly to network changes
Stochastic Performance Trade-offs in the Design of Real-Time Wireless Sensor Networks
Future sensing applications call for a thorough evaluation of network performance trade-offs so that desired guarantees can be provided for the realization of real-time wireless sensor networks (WSNs). Recent studies provide insight into the performance metrics in terms of first-order statistics, e.g., the expected delay. However, WSNs are characterized by the stochastic nature of the wireless channel and the queuing processes, which result in non-deterministic delay, throughput, and network lifetime. For the design of WSNs with predictable performance, probabilistic analysis of these performance metrics and their intrinsic trade-offs is essential. Moreover, providing stochastic guarantees is crucial since each deployment may result in a different realization.
In this paper, the trade-offs between delay, throughput, and lifetime are quantified through a stochastic network design approach. To this end, two novel probabilistic network design measures, quantile and quantile interval, are defined to capture the dependability and predictability of the performance metrics, respectively. Extensive evaluations are conducted to explore the performance trade-offs in real-time WSNs
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