879 research outputs found
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
TOPOLOGY CONTROL ALGORITHMS FOR RULE-BASED ROUTING
In this dissertation, we introduce a new topology control problem for rule- based link-state routing in autonomous networks. In this context, topology control is a mechanism to reduce the broadcast storm problem associated with link-state broadcasts. We focus on a class of topology control mechanisms called local-pruning mechanisms. Topology control by local pruning is an interesting multi-agent graph optimization problem, where every agent/router/station has access to only its local neighborhood information. Every agent selects a subset of its incident link-state in- formation for broadcast. This constitutes the pruned link-state information (pruned graph) for routing. The objective for every agent is to select a minimal subset of the local link-state information while guaranteeing that the pruned graph preserves desired paths for routing.
In topology control for rule-based link-state routing, the pruned link-state information must preserve desired paths that satisfy the rules of routing. The non- triviality in these problems arises from the fact that the pruning agents have access to only their local link-state information. Consequently, rules of routing must have some property, which allows specifying the global properties of the routes from the local properties of the graph. In this dissertation, we illustrate that rules described as algebraic path problem in idempotent semirings have these necessary properties.
The primary contribution of this dissertation is identifying a policy for pruning, which depends only on the local neighborhood, but guarantees that required global routing paths are preserved in the pruned graph. We show that for this local policy to ensure loop-free pruning, it is sufficient to have what is called an inflatory arc composition property. To prove the sufficiency, we prove a version of Bellman's optimality principle that extends to path-sets and minimal elements of partially ordered sets.
As a motivating example, we present a stable path topology control mecha- nism, which ensures that the stable paths for routing are preserved after pruning. We show, using other examples, that the generic pruning works for many other rules of routing that are suitably described using idempotent semirings
Coalition Formation Games for Collaborative Spectrum Sensing
Collaborative Spectrum Sensing (CSS) between secondary users (SUs) in
cognitive networks exhibits an inherent tradeoff between minimizing the
probability of missing the detection of the primary user (PU) and maintaining a
reasonable false alarm probability (e.g., for maintaining a good spectrum
utilization). In this paper, we study the impact of this tradeoff on the
network structure and the cooperative incentives of the SUs that seek to
cooperate for improving their detection performance. We model the CSS problem
as a non-transferable coalitional game, and we propose distributed algorithms
for coalition formation. First, we construct a distributed coalition formation
(CF) algorithm that allows the SUs to self-organize into disjoint coalitions
while accounting for the CSS tradeoff. Then, the CF algorithm is complemented
with a coalitional voting game for enabling distributed coalition formation
with detection probability guarantees (CF-PD) when required by the PU. The
CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e.,
coalitions that achieve the target detection probability with minimal costs.
For both algorithms, we study and prove various properties pertaining to
network structure, adaptation to mobility and stability. Simulation results
show that CF reduces the average probability of miss per SU up to 88.45%
relative to the non-cooperative case, while maintaining a desired false alarm.
For CF-PD, the results show that up to 87.25% of the SUs achieve the required
detection probability through MWCComment: IEEE Transactions on Vehicular Technology, to appea
Efficient Information Access in Data-Intensive Sensor Networks
Recent advances in wireless communications and microelectronics have enabled wide deployment of smart sensor networks. Such networks naturally apply to a broad range of applications that involve system monitoring and information tracking (e.g., fine-grained weather/environmental monitoring, structural health monitoring, urban-scale traffic or parking monitoring, gunshot detection, monitoring volcanic eruptions, measuring rate of melting glaciers, forest fire detection, emergency medical care, disaster response, airport security infrastructure, monitoring of children in metropolitan areas, product transition in warehouse networks etc.).Meanwhile, existing wireless sensor networks (WSNs) perform poorly when the applications have high bandwidth needs for data transmission and stringent delay constraints against the network communication. Such requirements are common for Data Intensive Sensor Networks (DISNs) implementing Mission-Critical Monitoring applications (MCM applications).We propose to enhance existing wireless network standards with flexible query optimization strategies that take into account network constraints and application-specific data delivery patterns in order to meet high performance requirements of MCM applications.In this respect, this dissertation has two major contributions: First, we have developed an algebraic framework called Data Transmission Algebra (DTA) for collision-aware concurrent data transmissions. Here, we have merged the serialization concept from the databases with the knowledge of wireless network characteristics. We have developed an optimizer that uses the DTA framework, and generates an optimal data transmission schedule with respect to latency, throughput, and energy usage. We have extended the DTA framework to handle location-based trust and sensor mobility. We improved DTA scalability with Whirlpool data delivery mechanism, which takes advantage of partitioning of the network. Second, we propose relaxed optimization strategy and develop an adaptive approach to deliver data in data-intensive wireless sensor networks. In particular, we have shown that local actions at nodes help network to adapt in worse network conditions and perform better. We show that local decisions at the nodes can converge towards desirable global network properties e.g.,high packet success ratio for the network. We have also developed a network monitoring tool to assess the state and dynamic convergence of the WSN, and force it towards better performance
Traffic Management System for the combined optimal routing, scheduling and motion planning of self-driving vehicles inside reserved smart road networks
The topic discussed in this thesis belongs to the field of automation of transport
systems, which has grown in importance in the last decade, both in the innovation
field (where different automation technologies have been gradually introduced in
different sectors of road transport, in the promising view of making it more efficient,
safer, and greener) and in the research field (where different research activities and
publications have addressed the problem under different points of view).
More in detail, this work addresses the problem of autonomous vehicles coordina tion inside reserved road networks by proposing a novel Traffic Management System
(TMS) for the combined routing, scheduling and motion planning of the vehicles.
To this aim, the network is assumed to have a modular structure, which results from
a certain number of roads and intersections assembled together. The way in which
roads and intersections are put together defines the network layout. Within such a
system architecture, the main tasks addressed by the TMS are: (1) at the higher
level, the optimal routing of the vehicles in the network, exploiting the available
information coming from the vehicles and the various elements of the network; (2)
at a lower level, the modeling and optimization of the vehicle trajectories and speeds
for each road and for each intersection in the network; (3) the coordination between
the vehicles and the elements of the network, to ensure a combined approach that
considers, in a recursive way, the scheduling and motion planning of the vehicles in
the various elements when solving the routing problem.
In particular, the routing and the scheduling and motion planning problems are
formulated as MILP optimization problems, aiming to maximize the performance
of the entire network (routing model) and the performance of its single elements -
roads and intersections (scheduling and motion planning model) while guaranteeing
the requested level of safety and comfort for the passengers.
Besides, one of the main features of the proposed approach consists of the integration of the scheduling decisions and the motion planning computation by means of constraints regarding the speed limit, the acceleration, and the so-called safety
dynamic constraints on incompatible positions of conflicting vehicles. In particular,
thanks to these last constraints, it is possible to consider the real space occupancy
of the vehicles avoiding collisions.
After the theoretical discussion of the proposed TMS and of its components
and models, the thesis presents and discusses the results of different numerical experiments, aimed at testing the TMS in some specific scenarios. In particular, the
routing model and the scheduling and motion planning model are tested on different scenarios, which demonstrate the effectiveness and the validity of such approach
in performing the addressed tasks, also compared with more traditional methods.
Finally, the computational effort needed for the problem solution, which is a key element to take into account, is discussed both for the road element and the intersection element
- …