Wireless sensor networks consist of small electronic nodes with integrated functions of monitoring the external space, data processing and transmission. The paper proposes methods of reducing energy consumption of nodes and algorithms for their application to increase the lifetime of wireless sensor networks with redundant number of nodes. The article proposes methods for reducing (redistributing) battery power consumption in order to increase the lifetime of networks with redundant number of nodes by planning and managing the joint operation of network elements at various levels of the reference model of open systems interaction. An algorithm is proposed for the application of the developed accordance with certain criteria (increased load and redundant consumption of the unit's energy resource). With the help of simulation modeling, an assessment of the effectiveness was carried out, which made it possible to conclude that the developed control methods for the WSN increase the network life time up to 15-20% compared to similar methods of this class.
network wireless sensor network, network nodes, energy resource redundancy nodes, the lifetime of the
Modern advances in radio electronics have made it possible to create small-sized, cheap and
multifunctional wireless devices (nodes), consisting of a set of monitoring sensors, a microprocessor, a
power battery and a transceiver. These nodes are capable of transmitting monitoring data over radio
channels, providing network interaction between a plurality of similar nodes and creating wireless
sensor networks (WSN). The main properties of WSN are [
low cost and small dimensions of the unit; scalability, fast deployment and initialization; automatic configuration and restoration; the ability of nodes to carry out primary processing of monitoring data; low cost of deployment and maintenance; minimum restrictions on the placement of wireless devices; fault tolerance of the network in case of disruption of individual connections between nodes or failure of some nodes;
limited communication and energy resources of the nodes.
These features of the WSN can be effectively used to solve various applied problems related to
distributed collection, analysis and transmission of information, for example [
Automation of life support processes (monitoring of microclimate, presence of people, etc.); Industrial automation (remote control and diagnostics of industrial equipment, etc.); Defense and security (control of the movement of people and equipment, means of operational communication and reconnaissance, control of the area of the monitoring area and remote observation, assistance in carrying out rescue operations, security and fire alarms, etc.);
2022 Copyright for this paper by its authors. 4. Monitoring of the environment (natural processes, pollution, etc.) 5. Healthcare (monitoring the condition of patients, etc.).
Some areas of application of the WSN (especially defense and security) require full coverage of the
area of the object by the monitoring zones of the sensors. In addition, to ensure the reliability of
monitoring data collection, it is often necessary to overlap the area of the object with monitoring sensors
multiple times, ensuring a given degree of connectivity of the network nodes. To do this, before
deploying the WSN, planning of the locations of the nodes is carried out. But there are areas of
application of the WSN, in which the deterministic deployment of nodes is impractical (or impossible)
due to the large time or economic costs of deployment (for example, in the event of hostilities,
environmental disasters, in areas of chemical or radiation contamination, hard-to-reach areas, etc.) [
Each WSN node is equipped with an energy source of limited capacity, therefore, the fundamental
requirement for them is to reduce energy consumption to increase the lifetime (LT) of the network. The
lifetime of a network is understood as the duration of the network's functioning without loss of
connectivity of its elements due to the failure of nodes that have used up their energy resources (battery
power) [
The article proposes methods for reducing (redistributing) battery power consumption in order to increase the lifetime of networks with redundant number of nodes by planning and managing the joint operation of network elements at various levels of the reference model of open systems interaction.
To reduce the energy consumption of nodes in order to increase the lifetime of the network, a variety
of appropriate methods have been proposed [
In contrast to the classical approach to organizing sleep/wake-up cycles for the WSN with redundant number of nodes, it is proposed:
1. At the application level, disable nodes that duplicate the coverage of the monitoring area. To extend the duration of the network operation, it is proposed to organize the on/off periods of individual nodes so that at each moment of time a set of nodes is functioning, which is necessary to ensure the specified coverage of the monitoring area.
2. At the network level, use an energy-saving routing method that takes into account the periodic operation of multiple redundant nodes, as well as a method for reducing (compressing) the amount of transmitted data due to their redundancy.
3. At the data link layer, with increasing data transmission load, use hybrid multiple access (MA) methods (deterministic and random access methods have different efficiency limits depending on the load). For nodes close to the gateway (where the traffic of the entire network is concentrated), in order to reduce the number of collisions in packet transmission and increase transmission rates, it is advisable to use methods of deterministic access to the channel. For nodes remote from the gateway, it is advisable to use random channel access methods that do not require node synchronization.
Methods for increasing the lifetime of WSN
o p e n s y s t e m s i n t e r a c t i o n m o d e l l e v e l
using node coordinates using node connectivity sleep/wakeup methods on demand on a schedule asynchronous multiple access methods random with scheduling hybrid layered
nodes topology control using directional antennas at the network layer Data aggregation data compression network data forecasting stochastic time series algorithmic Organizing of data collection with adaptive sampling
with hierarchical sampling with active sampling
mobility with a mobile gateway with mobile repeaters
Controlling transmission power allows to reduce energy use by reducing transmission power (range). Based on the fact that the WSN nodes are not mobile and route options can be determined in advance, transmission power control is advisable to use at the network level in routing methods.
Reducing the use of energy resources by reducing the amount of data (aggregation) occurs by reducing the redundancy or loss of accuracy in collecting monitoring data with the introduction of transmission delays for data processing. The WSN with redundant number of nodes is used to improve the reliability and quality of coverage of the area of the monitoring object, therefore, in these networks, it is advisable to use aggregation methods at the network level at individual nodes with increased energy use to prevent their failure if other energy saving methods are ineffective. To reduce the amount of data, it is advisable to use their correlation (temporal, when the data does not change over time, and spatial, when the data from neighboring nodes coincide). The author analyzed the methods for increasing the lifetime of the WSN from the point of view of the expediency of their application in networks with redundant number of nodes, and the following methods of controlling the WSN were proposed: 1) an energy-saving method for controlling the WSN with redundant number of nodes at the application and network levels of the OSI model (MC WSN ENN);
2) an energy-saving control method of the WSN with redundant number of nodes at the link layer of the OSI model - an energy-saving method of multiple access to the channel (EMMA WSN ENN); 3) an energy-saving method of data aggregation in the WSN with redundant number of nodes (EMDA WSN ENN).
The developed methods can be used both separately and in addition to each other in accordance with the following algorithm for choosing a set of applied methods for the WSN with ENN (Figure 2): 1) if the number of nodes is redundant 1,5 , the gateway initiates the use of EMC WSN ENN ( N / Nн , N – the total number of nodes, Nн – the number required to ensure the specified coverage); 2) with an increase in the total load on the gateway and nodes close to it to the values of the resistance 4.1. An energy-saving method of control of the WSN with ENN at the application and network levels of the OSI model
When analyzing the existing methods for increasing the lifetime of the WSN, the advantages of the
EECCR methods (An Energy-Efficient m -coverage and n -connectivity Routing Algorithm Under
Border Effects in Heterogeneous Sensor Networks [
The essence of the method: at the stage of network planning, the available number of subsets of nodes is first determined, each of which can provide a given coverage of the monitoring area; and then the total number of WSN nodes is divided into a certain number of sets of nodes that will operate at different periods of time and provide m-fold coverage of the area of the monitoring area by sensors and n-fold connectivity; at the initial stage of operation, the routes of message transmission from each node in the direction of the gateway are determined, taking into account the periods of operation of the WSN and the use of energy resources by the nodes, and some nodes are included in different subsets to ensure network connectivity;
after determining the routes, data is transmitted in the direction of the gateway (when switching sets, the routes are adjusted depending on the consumption of energy by individual nodes).
To determine the minimum number of nodes that should provide a given coverage of the monitoring area, the analytical model of the WSN was used.
WSN model with redundant number of nodes: N nodes are randomly evenly distributed in the monitoring area with radius R; SΩ and N , but at a separate point N / SΩ const ; with node density - a random variable (Poisson law with an intensity distribution N / SΩ ; use M types of nodes, number of nodes of i -th type – i N (0 i 1 , 1 i M , iM1i 1); monitoring radius of type i node – rмi , maximum transmission radius of type i node – rni; i, j M , rмi< rмj, if i < j ; the network is represented as a graph G = (V,E).
It was proved that for the described WSN model with redundant number of nodes at R >> max(rмi),
R >> max(rni), i 1..M the ratio of the area of m-fold coverage S
Ωm to the area of the monitoring
area SΩ and the probability of n-fold connectivity of nodes P G, n for the used WSN model are [
A feature of the proposed method is its application in case of redundancy of nodes 1,5..2,2,5..3, N / Nmn ( Nmn – is the required number of nodes to ensure the specified characteristics of the network). For this, it is proposed to increase the number of subsets of nodes Nм and their periods of operation NT . In this case, each node will correspond to several periods of turning on and off. So for 1,5..2 : Nм 3 , Nм 3 , the number of nodes turning on period NT on = 2. For 2,5..3 Nм 5 , NT 5 , NT on = 2. To determine the required number of subsets of nodes Nм and periods NT , it is proposed to use the developed algorithm using dependencies (1) 0. 2. Distribution of WSN into sets of nodes with separate periods of operation.
The random distribution of the total number of nodes into subsets in the WSN with redundant
number of nodes, which is used in the previous methods, can lead to a decrease in the real coverage of
the area of the monitoring area in certain periods of the network operation. It can also lead to an
overconsumption of the energy resource of nodes in individual zones of the network due to their
constant inclusion (when assigning the same set numbers to neighboring nodes) [
3. Organizing of routing of messages in the WSN (determination of routes) taking into account:
periods of functioning of the WSN with ENN; use of energy resources of nodes; uniformity of load on
nodes close to the gateway; restoration of connectivity in case of failure of individual nodes. To perform
these functions, it is proposed to use the developed routing algorithm [
4. Ensuring routing of data collection messages and their transmission along designated routes in
the direction of the gateway in accordance with the periods of network operation. At this stage, the
network is periodically reconfigured in accordance with the proposed algorithm [
The advantages of the developed method: - the possibility of using the method with redundancy of nodes (the previous methods were used with integer values of redundancy 2,3, 4,... );
- a more uniform distribution of nodes into sets with the exclusion of the possibility of including a group of neighboring nodes in one set (which is possible with a random distribution of nodes into sets); - ensuring the minimum number of functioning nodes close to the gateway, restoring network connectivity in the event of failure of its individual elements; - using the lowest possible transmission power (transmission power control at the network layer); - the use of a multi-parameter routing metric that takes into account the transmission power, the number of retransmissions, the remaining battery charge, and distance from the gateway (when used for relaying nodes from another set).
{2} {3}
{3} {1}
{2} gateway {3} {3} {3} {2}
{3} {2} {3,2,1} {1,2,3} {3,2} {2,1} gateway {3,2} Ю2} {3} {1} {1} {1} {1} {3}
{2} {1} {3} {2} {2,1} {1,3} {1,3} {2,3} {1} {3,2} {2,1} {1} {2} {1} {2,3} {1} {3,1,2} {1} a) {1} {2} {1}
{2} {1} {2,1} {1} {2} {3} {2} {3} {3} {3} {2}
{1} {1} {2} {1} {1} {2} {3}
{1} {3} {2} {3} {3,1} {2,3} {3,1}
{3} {3,2} {2}
{1} {1,2} {2} {1} {1,3} {2} {3,1}
{1} {3,2}
{2} {3} b) 4.2. An energy-saving control method for the WSN with ENN at the data link layer of the OSI model
For small values of the load in the WSN, it is advisable to use random multiple access methods. For
example, the dependence of the average transmission speed of a node on network traffic for flexible
carrier sense multiple access [
S
k 2Ge k 2G ak 2m
k 2G 1 2ak e k 2G ak 2m
where a, k , m – are the network parameters that affect the intensity of collisions due to hidden terminals
and depend on the characteristics of the WSN [
The graphs of the corresponding dependencies S G for different variants of values a, k, m
are presented in Figure 4 [
G
rate due to an increase in the number of collisions. This dependence is typical for all methods of random
access to the channel [
To increase the lifetime of the WSN with increasing traffic in the network G Gгc it is proposed
to create a zone of deterministic multiple access (ZDMA) to the channel around the gateway [
The use of two types of multiple access will allow combining their advantages, reduce the consumption of energy resources of traffic-loaded nodes, and simplify the synchronization of remote network elements. The maximum number of retransmissions i in ZDMA defined as max i , where Gi Giгс , Giгс arg max S Gi , where Gi – traffic to nodes i relaying gateway to or exceeding a
Gi predetermined relatively to the level collisions.
The advantages of the developed method: - the use of ZDMA allows to increase the bandwidth of the network without complicating its synchronization; - inclusion of nodes in the zone of deterministic access, initiated by the border node of the ZDMA; - adjusting the schedules of time intervals when switching sets of redundant nodes; - adaptation of the schedule of time intervals when changing workloads; - the developed method allows the use of data aggregation mechanisms (proposed below) at the border nodes of the ZDMA without introducing additional delays due to aggregation; - managing the size of the ZDMA with aggregation of data at the border nodes is an additional way to control the energy consumption of the nodes close to the gateway. 4.3.
Data aggregation methods introduce additional delays in data collection and processing. Therefore,
it is advisable to use them on individual nodes to extend the duration of their operation in order to
increase the network lifetime. When analyzing the methods for increasing the lifetime of the WSN, the
advantages of the DyDAP method (A Dynamic Data Aggregation Scheme for Privacy Aware Wireless
Sensor Networks) [
For the WSN with redundant number of nodes, data aggregation is supposed to be used in two cases, shown in Figure 5. In the first case, it is proposed to use it at the border nodes of the ZDMA (Figure 5a), which receive and transmit data at different periods of the network operation with the ZDMA. Time separation of reception and transmission allows one to apply data aggregation without introducing additional delays. In the second case, data aggregation is applied to nodes overloaded with relaying. Figure 5b shows an example in which nodes 1 and 2 relay data to the entire "detached" subnet and, therefore, can quickly deplete their energy resources and fail, which will lead to a loss of network connectivity. If it is impossible to apply other methods of reducing the use of energy resources (in this case, due to the peculiarities of the location of the nodes), the network lifetime can be extended only by reducing the amount of data transmitted from the subnetwork using their correlation (with an acceptable loss of their accuracy).
gatew ay
ZDM
A edge nodes random access nodes a) gatew ay node 1
node 2 "detached"
subnet b) Figure 5: Application options for the data aggregation method
In the proposed method, the data volume is reduced by creating dynamic data transmission queues with the given characteristics on individual network nodes at the gateway command: the maximum length of the transmission queue and the limitation of message transmission per unit of time. With an increase in transmission queues due to a sharp increase in traffic or when the number of transmissions is limited (to extend the duration of the operation of an individual node), the possibilities of reducing the amount of data due to the spatial and temporal correlation of individual messages increase. At the node, data processing is carried out and only data that have changed over a certain period are transmitted towards the gateway, while data from a group of neighboring nodes are averaged and transmitted in one aggregated message (Figure 6a-c).
1,2,3,4 m , m 1 2 m2 m1
R m , m 3
4 m3 m4
R
а forwarding an aggregated message towards the gateway m1,2,3,4 node where spatially correlated data is aggregated nodes that transmit spatially correlated messages m1, m2, m3, m4 spatial correlation radius x forwarding messages towards the gateway
... m1,2,3,4
... transmission queue after aggregation ... m1 m3 ... m4 ... m2 ... transmission queue before aggregation в
The article proposes methods for increasing the lifetime of the WSN with redundant number of nodes at different levels of the model of interaction of open systems and algorithm for the application of the developed methods in accordance with certain criteria (increased load and redundant consumption of the unit's energy resource). With the help of simulation modeling, an assessment of the effectiveness was carried out, which made it possible to conclude that the developed control methods for the WSN increase the network life time up to 15-20% compared to similar methods of this class. During the research, it was determined that the data collection model of the WSN with one gateway imposes restrictions on the possibility of evenly distributing the load on the nodes of the WSN to extend the time of its operation. Concentration of traffic leads to increased load on nodes close to the gateway and to their premature failure. It is possible to extend the duration of the functioning of the WSN in such conditions only by aggregating data with a loss of their accuracy. In the future, it is proposed to develop methods for controlling the consumption of energy resources of the WSN with redundant number of nodes and several gateways, which will extend the life of the network without losing the accuracy of the collected data.