1,288 research outputs found
Cross-layer design of multi-hop wireless networks
MULTI -hop wireless networks are usually defined as a collection of nodes
equipped with radio transmitters, which not only have the capability to
communicate each other in a multi-hop fashion, but also to route each others’ data
packets. The distributed nature of such networks makes them suitable for a variety of
applications where there are no assumed reliable central entities, or controllers, and
may significantly improve the scalability issues of conventional single-hop wireless
networks.
This Ph.D. dissertation mainly investigates two aspects of the research issues
related to the efficient multi-hop wireless networks design, namely: (a) network
protocols and (b) network management, both in cross-layer design paradigms to
ensure the notion of service quality, such as quality of service (QoS) in wireless mesh
networks (WMNs) for backhaul applications and quality of information (QoI) in
wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of
this Ph.D. dissertation, different network settings are used as illustrative examples,
however the proposed algorithms, methodologies, protocols, and models are not
restricted in the considered networks, but rather have wide applicability.
First, this dissertation proposes a cross-layer design framework integrating
a distributed proportional-fair scheduler and a QoS routing algorithm, while using
WMNs as an illustrative example. The proposed approach has significant performance
gain compared with other network protocols. Second, this dissertation proposes
a generic admission control methodology for any packet network, wired and
wireless, by modeling the network as a black box, and using a generic mathematical
0. Abstract 3
function and Taylor expansion to capture the admission impact. Third, this dissertation
further enhances the previous designs by proposing a negotiation process,
to bridge the applications’ service quality demands and the resource management,
while using WSNs as an illustrative example. This approach allows the negotiation
among different service classes and WSN resource allocations to reach the optimal
operational status. Finally, the guarantees of the service quality are extended to
the environment of multiple, disconnected, mobile subnetworks, where the question
of how to maintain communications using dynamically controlled, unmanned data
ferries is investigated
A Greedy Link Scheduler for Wireless Networks with Fading Channels
We consider the problem of link scheduling for wireless networks with fading
channels, where the link rates are varying with time. Due to the high
computational complexity of the throughput optimal scheduler, we provide a low
complexity greedy link scheduler GFS, with provable performance guarantees. We
show that the performance of our greedy scheduler can be analyzed using the
Local Pooling Factor (LPF) of a network graph, which has been previously used
to characterize the stability of the Greedy Maximal Scheduling (GMS) policy for
networks with static channels. We conjecture that the performance of GFS is a
lower bound on the performance of GMS for wireless networks with fading
channel
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
Optimal Energy Management Policies for Energy Harvesting Sensor Nodes
We study a sensor node with an energy harvesting source. The generated energy
can be stored in a buffer. The sensor node periodically senses a random field
and generates a packet. These packets are stored in a queue and transmitted
using the energy available at that time. We obtain energy management policies
that are throughput optimal, i.e., the data queue stays stable for the largest
possible data rate. Next we obtain energy management policies which minimize
the mean delay in the queue.We also compare performance of several easily
implementable sub-optimal energy management policies. A greedy policy is
identified which, in low SNR regime, is throughput optimal and also minimizes
mean delay.Comment: Submitted to the IEEE Transactions on Wireless Communications; 22
pages with 10 figure
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