On end-to-end delay minimization in wireless networks under the physical interference model

Li, Yuan; Capone, Antonio; Yuan, Di

doi:10.1109/infocom.2015.7218586

Cited by 7 publications

(6 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This refers to interference stemming from multiple nodes transmitting simultaneously, even where any one of these nodes' transmissions would not be sufficient on its own to prevent successful decoding of packets at a given receiver node. Compatible sets (c-sets) [4] are capable of accounting for physical interference -that is, based on received signal strength -in a computationally efficient way, and have been successfully applied to modelling and optimisation of wireless mesh networks [5]- [9].…”

mentioning

confidence: 99%

Energy-Optimal Data Aggregation and Dissemination for the Internet of Things

Fitzgerald

Pióro

Tomaszewski

2018

IEEE Internet Things J.

View full text Add to dashboard Cite

Abstract-Established approaches to data aggregation in wireless sensor networks (WSNs) do not cover the variety of new use cases developing with the advent of the Internet of Things. In particular, the current push towards fog computing, in which control, computation, and storage are moved to nodes close to the network edge, induces a need to collect data at multiple sinks, rather than the single sink typically considered in WSN aggregation algorithms. Moreover, for machine-to-machine communication scenarios, actuators subscribing to sensor measurements may also be present, in which case data should be not only aggregated and processed in-network, but also disseminated to actuator nodes. In this paper, we present mixed-integer programming formulations and algorithms for the problem of energy-optimal routing and multiple-sink aggregation, as well as joint aggregation and dissemination, of sensor measurement data in IoT edge networks. We consider optimisation of the network for both minimal total energy usage, and min-max per-node energy usage. We also provide a formulation and algorithm for throughput-optimal scheduling of transmissions under the physical interference model in the pure aggregation case. We have conducted a numerical study to compare the energy required for the two use cases, as well as the time to solve them, in generated network scenarios with varying topologies and between 10 and 40 nodes. Although aggregation only accounts for less than 15% of total energy usage in all cases tested, it provides substantial energy savings. Our results show more than 13 times greater energy usage for 40-node networks using direct, shortest-path flows from sensors to actuators, compared with our aggregation and dissemination solutions.

show abstract

mentioning

confidence: 99%

Energy-Optimal Data Aggregation and Dissemination for the Internet of Things

Fitzgerald

Pióro

Tomaszewski

2018

IEEE Internet Things J.

View full text Add to dashboard Cite

show abstract

“…This provides the smallest number of time slots for performing different sets of compatible transmissions. Basically, given a total set of packet transmissions to be performed, these are allocated to a minimum number of time slots so as to maximize parallelization and resource reuse [33].…”

Section: ) Proposed Throughput Maximization Modelmentioning

confidence: 99%

Enhanced QoS-Aware Routing Protocol for Delay Sensitive Data in Wireless Body Area Networks

Kaur,

Verma,

Kavita

et al. 2023

IEEE Access

View full text Add to dashboard Cite

The Wireless Body Area Network (WBAN) shows potential as a technology that can provide high-quality healthcare services to its users. However, the limited battery life of low-power devices attached to the body is a challenge. The data must be sent through a reliable connection with minimum delay to the healthcare centre since it directly influences user satisfaction. In case of potentially fatal situation, transmitting data at the right time is important. Therefore, more policies and methods for better end-toend performance of a network are required. In this paper, the end-to-end delay of network over a wireless channel from sensor to healthcare centre has been analyzed. The proposed work presents an Enhanced Quality of Service Aware Routing Protocol for Delay Sensitive Data (EQRD). EQRD reduces the delay by proposing a Bandwidth Utilization Constant to maximize the utilization of channel capacity. It finds the best minimum number of slots that can be used for data transmission for the minimization of delay and maximization of throughput. By analyzing various parameters, the EQRD protocol's effectiveness was evaluated in relation to other delay-aware routing protocols. The findings indicate that the proposed protocol has superior performance with regards to throughput, energy efficiency, and delay.

show abstract

“…Thus, the delay in delivering a packet from o to d over path

will depend on the sequence according to which the c-sets actually used in the frame are assigned to the frame time slots. Minimising the number of frames required to deliver all packets in a given set of measurements is an issue that is out of scope of this paper (see in Appendix B of [ 3 ] and in [ 32 ]).…”

Section: Problem Formulationmentioning

confidence: 99%

Energy Versus Throughput Optimisation for Machine-to-Machine Communication

Fitzgerald

Pióro

Tomaszewski

2020

Sensors

View full text Add to dashboard Cite

We investigate the trade-off between energy usage and (packet) throughput in wireless mesh networks performing machine-to-machine communication. For this we provide a novel mixed-integer programming formulation to maximise the throughput while maintaining minimal energy usage, together with an effective price-and-branch solution algorithm based on column generation. The resulting optimisation model is the main original contribution of the presented paper. We conducted a numerical study using network examples from 10 to 40 nodes, in which periodic sensor measurements are aggregated and disseminated to actuators. In almost all cases, we were able to achieve maximum throughput and minimum energy usage simultaneously, and in those cases where this was not possible, the costs incurred in one objective in order to achieve the other were typically low. The solution times for all network sizes were of the order of seconds, showing that our optimisation model is feasible to use in practice.

show abstract

On end-to-end delay minimization in wireless networks under the physical interference model

Cited by 7 publications

References 28 publications

Energy-Optimal Data Aggregation and Dissemination for the Internet of Things

Energy-Optimal Data Aggregation and Dissemination for the Internet of Things

Enhanced QoS-Aware Routing Protocol for Delay Sensitive Data in Wireless Body Area Networks

Energy Versus Throughput Optimisation for Machine-to-Machine Communication

Contact Info

Product

Resources

About