11,083 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
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
Multi-mode Tracking of a Group of Mobile Agents
We consider the problem of tracking a group of mobile nodes with limited
available computational and energy resources given noisy RSSI measurements and
position estimates from group members. The multilateration solutions are known
for energy efficiency. However, these solutions are not directly applicable to
dynamic grouping scenarios where neighbourhoods and resource availability may
frequently change. Existing algorithms such as cluster-based GPS duty-cycling,
individual-based tracking, and multilateration-based tracking can only
partially deal with the challenges of dynamic grouping scenarios. To cope with
these challenges in an effective manner, we propose a new group-based
multi-mode tracking algorithm. The proposed algorithm takes the topological
structure of the group as well as the availability of the resources into
consideration and decides the best solution at any particular time instance. We
consider a clustering approach where a cluster head coordinates the usage of
resources among the cluster members. We evaluate the energy-accuracy trade-off
of the proposed algorithm for various fixed sampling intervals. The evaluation
is based on the 2D position tracks of 40 nodes generated using Reynolds'
flocking model. For a given energy budget, the proposed algorithm reduces the
mean tracking error by up to in comparison to the existing
energy-efficient cooperative algorithms. Moreover, the proposed algorithm is as
accurate as the individual-based tracking while using almost half the energy.Comment: Accepted for publication in the 20th international symposium on
wireless personal multimedia communications (WPMC-2017
Design of an autonomous software platform for future symbiotic service management
Nowadays, public as well as private communication infrastructures are all contending for the same limited amount of bandwidth. To optimally share network resources, symbiotic networks have been proposed, which cross logical and physical boundaries to improve the reliability, scalability, and energy efficiency of the network as a whole as well as its constituents. This paper focuses on software services in such symbiotic networks. We propose a platform for the intelligent composition of services provided by symbiotically connected parties, resulting in novel cooperation opportunities. The platform harvests Semantic Web technology to describe services in a highly expressive manner, and constructs service compositions using SeCoA, our tunable best-first search algorithm. The resulting compositions are then enacted via CaPI, a reconfigurable middleware infrastructure. By means of an illustrative scenario, we provide further insight into the platform's functioning
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