IEEE Standard for local and metropolitan area networks : supplement to Integrated Services (IS) LAN Interface at the Medium Access Control (MAC) and Physical (PHY) layers : Managed Object Conformance (MOCS) Proforma

A genetic algorithm for energy efficient fog layer resource management in context-aware smart cities

In order to transmit IPv6 packets on IEEE 802.11 networks run outside
the context of a basic service set (OCB, earlier "802.11p") there is a
need to define a few parameters such as the recommended Maximum
Transmission Unit size, the header format preceding the IPv6 header,
the Type value within it, and others. This document describes these
parameters for IPv6 and IEEE 802.11 OCB networks; it portrays the
layering of IPv6 on 802.11 OCB similarly to other known 802.11 and
Ethernet layers - by using an Ethernet Adaptation Layer. In addition,
the document attempts to list what is different in 802.11 OCB
(802.11p) compared to more 'traditional' 802.11a/b/g/n layers,
layers over which IPv6 protocols operates without issues. Most
notably, the operation outside the context of a BSS (OCB) has impact
on IPv6 handover behaviour and on IPv6 security. An example of an
IPv6 packet captured while transmitted over an IEEE 802.11 OCB link
(802.11p) is given.

Transmission of IPv6 Packets over IEEE 802.11 Networks Outside the Context of a Basic Service Set

Over the recent era, Wireless Sensor Network (WSN) has attracted much attention among industrialists and researchers owing to its contribution to numerous applications including military, environmental monitoring and so on. However, reducing the network delay and improving the network lifetime are always big issues in the domain of WSN. To resolve these downsides, we propose an Energy-Efficient Scheduling using the Deep Reinforcement Learning (DRL) (E2S-DRL) algorithm in WSN. E2S-DRL contributes three phases to prolong network lifetime and to reduce network delay that is: the clustering phase, duty-cycling phase and routing phase. E2S-DRL starts with the clustering phase where we reduce the energy consumption incurred during data aggregation. It is achieved through the Zone-based Clustering (ZbC) scheme. In the ZbC scheme, hybrid Particle Swarm Optimization (PSO) and Affinity Propagation (AP) algorithms are utilized. Duty cycling is adopted in the second phase by executing the DRL algorithm, from which, E2S-DRL reduces the energy consumption of individual sensor nodes effectually. The transmission delay is mitigated in the third (routing) phase using Ant Colony Optimization (ACO) and the Firefly Algorithm (FFA). Our work is modeled in Network Simulator 3.26 (NS3). The results are valuable in provisions of upcoming metrics including network lifetime, energy consumption, throughput and delay. From this evaluation, it is proved that our E2S-DRL reduces energy consumption, reduces delays by up to 40% and enhances throughput and network lifetime up to 35% compared to the existing cTDMA, DRA, LDC and iABC methods.

https://www.mdpi.com/1424-8220/20/5/1540/pdf

Refining Network Lifetime of Wireless Sensor Network Using Energy-Efficient Clustering and DRL-Based Sleep Scheduling.

Survey and taxonomy of MAC, routing and cross layer protocols using wake-up radio

Energy consumption has become dominant issue for wireless internet of things (IoT) networks with battery-powered nodes. The prevailing mechanism allowing to reduce energy consumption is duty-cycling. In this technique the node sleeps most of the time and wakes up only at selected moments to extend the lifespan of nodes up to 5–10 years. Unfortunately, the scheduled duty-cycling technique is always a trade-off between energy consumption and delay in delivering data to the target node. The delay problem can be alleviated with an additional wake-up radio (WuR) channel. In the paper we present original power consumption models for various duty-cycling schemes. They are the basis for checking whether WuR approach is competitive with scheduled duty-cycling techniques. We determine the maximum energy level that an additional wake-up radio can consume to become a reasonable alternative of widely used duty-cycling techniques for typical IoT networks.

/pdf/energy-efficiency-trade-off-between-duty-cycling-and-wake-up-2yxl8c3lxd.pdf

Energy Efficiency Trade-Off Between Duty-Cycling and Wake-Up Radio Techniques in IoT Networks

Practical proliferation of Internet of Things (IoT) concept depends upon communication efficiency in the related network. In the paper we outline basic features of wireless communication protocols used in IoT and concentrate on analysing communication overheads. In particular, we discuss the impact of IPv6 packet length on 6LoWPAN network operation with physical and MAC layer defined by IEEE 802.15.4 standard. The presented analysis methodology is useful in estimation of the total goodput (throughput at the application level) and energy consumptions within the whole traffic model which are the crucial features of IoT networks.

Analysing efficiency of IPv6 packet transmission over 6LoWPAN network

Fast growing market related to Internet of Things creates new demands for wireless sensor networks. Here we face the problem of optimizing energy consumption in many miniature electronic devices powered from local batteries and requested long life span of nodes up to 5-10 years. The transmission processes constitute the primary source of energy consumption in the node, however complex data processing can also contribute a non negligible component. Optimizing energy consumption we can use various energy saving schemes, e.g. bringing the nodes in a sleeping mode and waking them periodically. In the paper we analyse in detail time and power components influencing energy consumption profiles. The derived original parameters are helpful to create power consumption models for specific applications. The presented methodology has been verified experimentally within (TI) CC1310F128 chip.

Evaluating energy consumption in wireless sensor networks

Wireless network nodes working in industrial environment or mounted on mobile machines are exposed to frequent and unpredictable temperature changes, which impact local clock accuracy resulting in synchronization problems (time offset). These issues have to be taken into account when optimizing the network to avoid higher energy consumption and traffic congestion. The time offset problem can be alleviated using temperature driven compensation. In the paper we propose an efficient algorithm to resolve this problem taking into account slow and rapid temperature fluctuations. It combines the physical model of the node oscillator with an original prediction method based on the linear regression. It can be embedded in low cost microcontrollers with limited resources. Our approach needed some experimental studies of oscillator features and microcontroller capabilities. The implemented prototype nodes and performed tests proved high clock resilience for industrial environment as compared with other approaches.

Adam Kozłowski

Papers

Energy Efficiency Trade-Off Between Duty-Cycling and Wake-Up Radio Techniques in IoT Networks

Analysing efficiency of IPv6 packet transmission over 6LoWPAN network

Evaluating energy consumption in wireless sensor networks

Adaptive time offset compensation for TDMA industrial wireless networks

Adaptive and Contract Aware Configuration for Industrial Wireless Networks