650 research outputs found
Joint Routing and STDMA-based Scheduling to Minimize Delays in Grid Wireless Sensor Networks
In this report, we study the issue of delay optimization and energy
efficiency in grid wireless sensor networks (WSNs). We focus on STDMA (Spatial
Reuse TDMA)) scheduling, where a predefined cycle is repeated, and where each
node has fixed transmission opportunities during specific slots (defined by
colors). We assume a STDMA algorithm that takes advantage of the regularity of
grid topology to also provide a spatially periodic coloring ("tiling" of the
same color pattern). In this setting, the key challenges are: 1) minimizing the
average routing delay by ordering the slots in the cycle 2) being energy
efficient. Our work follows two directions: first, the baseline performance is
evaluated when nothing specific is done and the colors are randomly ordered in
the STDMA cycle. Then, we propose a solution, ORCHID that deliberately
constructs an efficient STDMA schedule. It proceeds in two steps. In the first
step, ORCHID starts form a colored grid and builds a hierarchical routing based
on these colors. In the second step, ORCHID builds a color ordering, by
considering jointly both routing and scheduling so as to ensure that any node
will reach a sink in a single STDMA cycle. We study the performance of these
solutions by means of simulations and modeling. Results show the excellent
performance of ORCHID in terms of delays and energy compared to a shortest path
routing that uses the delay as a heuristic. We also present the adaptation of
ORCHID to general networks under the SINR interference model
Wireless Scheduling with Power Control
We consider the scheduling of arbitrary wireless links in the physical model
of interference to minimize the time for satisfying all requests. We study here
the combined problem of scheduling and power control, where we seek both an
assignment of power settings and a partition of the links so that each set
satisfies the signal-to-interference-plus-noise (SINR) constraints.
We give an algorithm that attains an approximation ratio of , where is the number of links and is the ratio
between the longest and the shortest link length. Under the natural assumption
that lengths are represented in binary, this gives the first approximation
ratio that is polylogarithmic in the size of the input. The algorithm has the
desirable property of using an oblivious power assignment, where the power
assigned to a sender depends only on the length of the link. We give evidence
that this dependence on is unavoidable, showing that any
reasonably-behaving oblivious power assignment results in a -approximation.
These results hold also for the (weighted) capacity problem of finding a
maximum (weighted) subset of links that can be scheduled in a single time slot.
In addition, we obtain improved approximation for a bidirectional variant of
the scheduling problem, give partial answers to questions about the utility of
graphs for modeling physical interference, and generalize the setting from the
standard 2-dimensional Euclidean plane to doubling metrics. Finally, we explore
the utility of graph models in capturing wireless interference.Comment: Revised full versio
Interference-Aware Scheduling for Connectivity in MIMO Ad Hoc Multicast Networks
We consider a multicast scenario involving an ad hoc network of co-channel
MIMO nodes in which a source node attempts to share a streaming message with
all nodes in the network via some pre-defined multi-hop routing tree. The
message is assumed to be broken down into packets, and the transmission is
conducted over multiple frames. Each frame is divided into time slots, and each
link in the routing tree is assigned one time slot in which to transmit its
current packet. We present an algorithm for determining the number of time
slots and the scheduling of the links in these time slots in order to optimize
the connectivity of the network, which we define to be the probability that all
links can achieve the required throughput. In addition to time multiplexing,
the MIMO nodes also employ beamforming to manage interference when links are
simultaneously active, and the beamformers are designed with the maximum
connectivity metric in mind. The effects of outdated channel state information
(CSI) are taken into account in both the scheduling and the beamforming
designs. We also derive bounds on the network connectivity and sum transmit
power in order to illustrate the impact of interference on network performance.
Our simulation results demonstrate that the choice of the number of time slots
is critical in optimizing network performance, and illustrate the significant
advantage provided by multiple antennas in improving network connectivity.Comment: 34 pages, 12 figures, accepted by IEEE Transactions on Vehicular
Technology, Dec. 201
Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting
In a multihop wireless network, it is crucial but challenging to schedule
transmissions in an efficient and fair manner. In this paper, a novel
distributed node scheduling algorithm, called Local Voting, is proposed. This
algorithm tries to semi-equalize the load (defined as the ratio of the queue
length over the number of allocated slots) through slot reallocation based on
local information exchange. The algorithm stems from the finding that the
shortest delivery time or delay is obtained when the load is semi-equalized
throughout the network. In addition, we prove that, with Local Voting, the
network system converges asymptotically towards the optimal scheduling.
Moreover, through extensive simulations, the performance of Local Voting is
further investigated in comparison with several representative scheduling
algorithms from the literature. Simulation results show that the proposed
algorithm achieves better performance than the other distributed algorithms in
terms of average delay, maximum delay, and fairness. Despite being distributed,
the performance of Local Voting is also found to be very close to a centralized
algorithm that is deemed to have the optimal performance
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
Link Scheduling in UAV-Aided Networks
Unmanned Aerial Vehicles (UAVs) or drones are a type of low altitude aerial mobile vehicles. They can be integrated into existing networks; e.g., cellular, Internet of Things (IoT) and satellite networks. Moreover, they can leverage existing cellular or Wi-Fi infrastructures to communicate with one another. A popular application of UAVs is to deploy them as mobile base stations and/or relays to assist terrestrial wireless communications. Another application is data collection, whereby they act as mobile sinks for wireless sensor networks or sensor devices operating in IoT networks. Advantageously, UAVs are cost-effective and they are able to establish line-of-sight links, which help improve data rate. A key concern, however, is that the uplink communications to a UAV may be limited, where it is only able to receive from one device at a time. Further, ground devices, such as those in IoT networks, may have limited energy, which limit their transmit power. To this end, there are three promising approaches to address these concerns, including (i) trajectory optimization, (ii) link scheduling, and (iii) equipping UAVs with a Successive Interference Cancellation (SIC) radio.
Henceforth, this thesis considers data collection in UAV-aided, TDMA and SICequipped wireless networks. Its main aim is to develop novel link schedulers to schedule uplink communications to a SIC-capable UAV. In particular, it considers two types of networks: (i) one-tier UAV communications networks, where a SIC-enabled rotary-wing UAV collects data from multiple ground devices, and (ii) Space-Air-Ground Integrated Networks (SAGINs), where a SIC-enabled rotary-wing UAV offloads collected data from ground devices to a swarm of CubeSats. A CubeSat then downloads its data to a terrestrial gateway. Compared to one-tier UAV communications networks, SAGINs are able to provide wide coverage and seamless connectivity to ground devices in remote and/or sparsely populated areas
Data Collection in Two-Tier IoT Networks with Radio Frequency (RF) Energy Harvesting Devices and Tags
The Internet of things (IoT) is expected to connect physical objects and end-users using technologies such as wireless sensor networks and radio frequency identification (RFID). In addition, it will employ a wireless multi-hop backhaul to transfer data collected by a myriad of devices to users or applications such as digital twins operating in a Metaverse. A critical issue is that the number of packets collected and transferred to the Internet is bounded by limited network resources such as bandwidth and energy. In this respect, IoT networks have adopted technologies such as time division multiple access (TDMA), signal interference cancellation (SIC) and multiple-input multiple-output (MIMO) in order to increase network capacity. Another fundamental issue is energy. To this end, researchers have exploited radio frequency (RF) energy-harvesting technologies to prolong the lifetime of energy constrained sensors and smart devices. Specifically, devices with RF energy harvesting capabilities can rely on ambient RF sources such as access points, television towers, and base stations. Further, an operator may deploy dedicated power beacons that serve as RF-energy sources. Apart from that, in order to reduce energy consumption, devices can adopt ambient backscattering communication technologies. Advantageously, backscattering allows devices to communicate using negligible amount of energy by modulating ambient RF signals.
To address the aforementioned issues, this thesis first considers data collection in a two-tier MIMO ambient RF energy-harvesting network. The first tier consists of routers with MIMO capability and a set of source-destination pairs/flows. The second tier consists of energy harvesting devices that rely on RF transmissions from routers for energy supply. The problem is to determine a minimum-length TDMA link schedule that satisfies the traffic demand of source-destination pairs and energy demand of energy harvesting devices. It formulates the problem as a linear program (LP), and outlines a heuristic to construct transmission sets that are then used by the said LP. In addition, it outlines a new routing metric that considers the energy demand of energy harvesting devices to cope with routing requirements of IoT networks. The simulation results show that the proposed algorithm on average achieves 31.25% shorter schedules as compared to competing schemes. In addition, the said routing metric results in link schedules that are at most 24.75% longer than those computed by the LP
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