CN110798874A - Energy effective routing method based on harmony search - Google Patents

Energy effective routing method based on harmony search Download PDF

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Publication number
CN110798874A
CN110798874A CN201910704652.6A CN201910704652A CN110798874A CN 110798874 A CN110798874 A CN 110798874A CN 201910704652 A CN201910704652 A CN 201910704652A CN 110798874 A CN110798874 A CN 110798874A
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node
path
next hop
harmony
energy
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王宝亮
彭程
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Tianjin University
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Tianjin University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention relates to an energy effective routing method based on harmony search, which comprises the following steps: searching N paths which can be directly reached between a source node and a destination node; randomly generating a random number P1 between 0 and 1 from a source node, and if the random number P1 is smaller than the memory bank value probability HCMR, searching N from the generated HMS when the next hop node is selectedsCorresponding next hop nodes are selected and needed, and the positions of the next hop nodes are determined by adopting a wheel disc method; ) Calculating an objective function for measuring the energy consumption condition of a generated path in the whole network; and comparing the objective function value of the newly generated path with the minimum objective function value in the harmony memory library, and if the generated new solution is smaller than the optimal solution in the harmony memory library, updating the newly generated path into the harmony memory library HM.

Description

Energy effective routing method based on harmony search
Technical Field
The invention relates to an energy efficient routing method, and belongs to the technical field of wireless sensor networks.
Background
In a wireless sensor network, a sensing layer usually deploys a large number of low-power-consumption sensing nodes to collect data, and transmits the data to a gateway node through multi-hop to perform the next data forwarding or processing operation, so that the monitoring operation of a required area for a long time is realized. The application of the wireless sensor network is very wide, and the intellectualization of the sensor network is greatly improved.
In the wireless sensor network, in order to prolong the service life of the whole network, the energy consumption of each node is limited. In the current stage of research, particularly under the deployment of an outdoor sensing network, the deployment area environment is random, and the battery replacement is difficult after the node is put in. The installed node can be basically regarded as a power consumption device with limited energy, and the wireless sensor network is required to be capable of rapidly self-organizing to form a reliable, high-throughput, efficient and energy-saving data packet transmission network in practical application. At present, schemes such as changing a function mode (for example, using new energy for energy supply) or changing a hardware structure of a node cannot be popularized due to the reasons of low cost performance, difficult realization, unsatisfactory charging effect and the like. Therefore, in order to prolong the working time of the wireless sensor network as far as possible and enable the data transmission to be more stable, the research on the high-efficiency and energy-saving network routing protocol has practical significance.
The multi-hop routing design by using the meta heuristic algorithm is a well-known idea, but the solving process of the optimal solution or suboptimal solution problem is still in progress at present. Various current algorithms have defects and need further research.
Disclosure of Invention
The invention provides an energy-efficient and harmonic multi-hop self-adaptive routing algorithm, aiming at the problem of excessive energy consumption caused by different use frequencies of different nodes in a wireless sensor network. According to the invention, the consideration of the energy of the next hop node is added to the selection problem of the next hop route, so that the problem of overall energy imbalance is solved, the phenomenon of local energy holes is avoided, and the activity of each node is mobilized, thereby prolonging the service cycle of the network. The technical scheme is as follows:
an energy effective routing method based on harmony search is provided, wherein an HM represents a harmony memory library and stores a plurality of paths from a source node to a destination node; HMS is the size of the harmony memory bank; HCMR is memory bank value probability; PAR is the fine tuning probability; t ismaxRepresenting the maximum number of iterations. The method is characterized by comprising the following steps:
(1) two end nodes which definitely need to communicate, namely a source node and a destination node, are respectively marked as Ns、Nd；
(2) Searching N paths which can be directly reached between a source node and a destination node, storing the paths in the HM, and finishing initialization of the HM by storing content which is node codes sequentially passed by the paths;
(3) from the source node NsFirstly, randomly generating a random number P1 between 0 and 1, if the random number P1 is less than the memory bank value probability HCMR, then when the next hop node is selected, the next hop node needs to search N from the generated HMSsAnd the corresponding next hop node needs to be judged in the next step after the selection is finished: regenerating a random number P2 between 0 and 1, and if the random number P2 is smaller than the fine tuning probability PAR, performing fine tuning operation on the selected next-hop node, wherein the fine tuning operation mainly comprises the insertion and replacement of the selected node; otherwise, fine adjustment is not carried out; if the random number P1 is not less than the memory bank value probability HCMR, the next-hop node is at NsThe neighbor nodes are selected, all the neighbor nodes are considered comprehensively according to the residual energy of the neighbor nodes in the selection process, the more the residual energy is, the greater the occupied proportion is, and the position of the next hop node is determined by adopting a wheel disc method; the next hop node is marked as N1；
(4) For N1In other words, the selection of the next hop node repeats the step (3) until the selected next hop node is consistent with the destination node, and one path is determined;
(5) the objective function f measures the energy consumption condition of the generation path in the whole network, and the calculation rule is as follows:
Figure BDA0002151733440000021
wherein E (x) is the sum of the energy consumptions consumed along the path; l is the number of nodes of the path; eminIs the lowest remaining energy along the path node; eargCalculating the f value of each path for the average residual energy along the path nodes;
(6) comparing the objective function value of the newly generated path with the minimum objective function value in the harmony memory library, if the generated new solution is smaller than the optimal solution in the harmony memory library, updating the newly generated path into the harmony memory library HM, otherwise, deleting the newly generated path;
(7) checking whether the current iteration time T reaches the maximum iteration time TmaxIf T is less than TmaxRepeating steps (3) - (6);
(8) when T is equal to TmaxAnd then, inquiring the optimal objective function solution in the harmony memory library, and outputting the transmission path corresponding to the optimal objective function solution as the optimal routing path.
The invention has the following beneficial effects:
1. the invention provides an energy efficient routing method based on harmony search. When the next hop routing is selected, the algorithm considers the energy global property and combines the residual energy of each node to select the next hop, thereby avoiding the occurrence of energy holes in the wireless sensor network to a certain extent and prolonging the service cycle of the whole network.
2. In the execution process of the algorithm, the convergence rate can be controlled by parameters such as HMCR, PAR and the like, and the algorithm has strong flexibility and is convenient to apply and popularize.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The present invention is primarily directed to energy efficient multi-hop routing algorithms. Considering that in the path planning process of the traditional routing algorithm of the wireless sensor network, only single data transmission energy consumption is usually considered, even only the delay problem of data transmission is considered, and energy balance cannot be realized from the global aspect. Aiming at the defect, the invention adds the consideration of the residual energy of the next hop node on the basis of combining the energy consumption of the multi-hop path, can further carry out the balanced adjustment on the energy distribution of the whole network and make a reasonable global plan. The overall schematic diagram of the scheme is shown in fig. 1, and relevant preconditions and specific steps are as follows:
1 use of harmonic multi-hop routing algorithm
When the algorithm designed by the invention is used, the following conditions must be met:
(1) the number of the nodes is limited, and the positions are unchanged.
(2) The nodes are not chargeable and the initial energy is limited and the same.
(3) The distance between the two nodes can be judged through signal transmission.
2 route establishment
The gateway node sends the information to the subsequent nodes in a broadcasting mode, the relay node calculates the minimum hop count and returns the minimum hop count information to the gateway node. And the gateway node sends the calculated routing strategy to the relay node and stores the routing strategy by the relay node.
The information sent by the gateway node includes a minimum hop count, a data packet, self remaining energy, a transmission path, and the like. And updating the node residual energy information in the network in the village of the gateway node each time when the gateway node receives the returned information, and primarily establishing the route.
3 initializing and acoustic memory library
The invention is improved on the basis of a harmony search algorithm in a meta-heuristic algorithm. At the beginning of the algorithm operation, N paths (N limited) for data communication need to be stored. In order to ensure that the generated harmony memory library has certain randomness, a wheel disk method is adopted to generate the harmony memory library. When the next hop node is selected, the selection range is limited in the neighbor nodes of the node, and the selection principle adopts a mode of taking energy as a center, so that the probability that the node with high residual energy is selected as the next hop is higher.
Starting from a source node, selecting next hop nodes one by one in a wheel disc method mode to know that the next hop node is selected to a destination node. Thus, different combinations of all nodes generated on the path constitute N paths of the harmony repository.
4 generating a new Sum-sequence solution
The new harmony sequence solution needs to refer to the existing harmony memory library and is generated by certain random creation. The creation process is embodied in the selection process of the next hop node. Assuming that the value probability of the harmony memory bank is HMCR, when the next hop selection is carried out, firstly, a random number P is generated1If P is1If the node is less than the HMCR, the next hop is randomly selected from neighbor nodes of the previous node; otherwise, the next hop is randomly selected from the previous hop nodes. HM (maximum value)And the CR adopts dynamic parameters, and the value of the CR changes along with the change of the iteration times.
5 and Fine tuning of the Acoustic memory library
Since the new harmonic sequence interpretation is generated with reference to the harmonic memory library, the length of the new solution must be less than or equal to the length of the longest path in the harmonic memory library. Because of this, the solution in the harmony memory bank may not contain the length of the optimal solution or the suboptimal solution, so that the algorithm is likely to fall into a local optimal phenomenon during the search. To avoid this, the search capability of the harmony search algorithm is improved, and a new parameter HLAR is introduced and adjusted in combination with PAR for a new harmony sequence. The adjusting method comprises the following steps:
generating a random number P2，P3。P2In comparison with PAR, if P2< PAR, which requires fine-tuning of the newly generated path, including node replacement and insertion. The replacement range is defined in the neighbor nodes of the node. P3In contrast to HLAR, if P3If HLAR is less than the preset value, the fine tuning mode is to insert a new node, otherwise, the fine tuning mode is to replace a next hop node.
Wherein, the PAR also adopts dynamic parameters. The new path generated by the method passes through the objective function to carry out effect verification. The harmony memory bank is updated only if the new path has better effect than the optimal solution in the harmony memory bank, otherwise it is not processed.
6 repeat search
And repeating the steps until the algorithm stops after the preset maximum cycle number is met. When the harmony search algorithm is used for selecting the next hop route, the energy distribution of the whole wireless sensor network can be balanced to a certain degree. The algorithm is suitable for being used in an outdoor wireless sensing network, particularly under the conditions of no subsequent energy supply, limited sensing nodes and random deployment environment. Besides the energy balance system of the algorithm, attention needs to be paid to the placement environment of the sensor nodes, and energy loss caused by interference from the outside is avoided as much as possible.

Claims (1)

1. An energy effective routing method based on harmony search is provided, wherein an HM represents a harmony memory library and stores a plurality of paths from a source node to a destination node; HMS is the size of the harmony memory bank; HCMR is memory bank value probability; PAR is the fine tuning probability; t ismaxRepresenting the maximum number of iterations. The method is characterized by comprising the following steps:
(1) two end nodes which definitely need to communicate, namely a source node and a destination node, are respectively marked as Ns、Nd；
(2) Searching N paths which can be directly reached between a source node and a destination node, storing the paths in the HM, and finishing initialization of the HM by storing content which is node codes sequentially passed by the paths;
(3) from the source node NsFirstly, randomly generating a random number P1 between 0 and 1, if the random number P1 is less than the memory bank value probability HCMR, then when the next hop node is selected, the next hop node needs to search N from the generated HMSsAnd the corresponding next hop node needs to be judged in the next step after the selection is finished: regenerating a random number P2 between 0 and 1, and if the random number P2 is smaller than the fine tuning probability PAR, performing fine tuning operation on the selected next-hop node, wherein the fine tuning operation mainly comprises the insertion and replacement of the selected node; otherwise, fine adjustment is not carried out; if the random number P1 is not less than the memory bank value probability HCMR, the next-hop node is at NsThe neighbor nodes are selected, all the neighbor nodes are considered comprehensively according to the residual energy of the neighbor nodes in the selection process, the more the residual energy is, the greater the occupied proportion is, and the position of the next hop node is determined by adopting a wheel disc method; the next hop node is marked as N1；
(4) For N1In other words, the selection of the next hop node repeats the step (3) until the selected next hop node is consistent with the destination node, and one path is determined;
(5) the objective function f measures the energy consumption condition of the generation path in the whole network, and the calculation rule is as follows:
Figure FDA0002151733430000011
wherein E (x) is an edgeSum of energy consumption of path consumption; l is the number of nodes of the path; eminIs the lowest remaining energy along the path node; eargCalculating the f value of each path for the average residual energy along the path nodes;
(6) comparing the objective function value of the newly generated path with the minimum objective function value in the harmony memory library, if the generated new solution is smaller than the optimal solution in the harmony memory library, updating the newly generated path into the harmony memory library HM, otherwise, deleting the newly generated path;
(7) checking whether the current iteration time T reaches the maximum iteration time TmaxIf T is less than TmaxRepeating steps (3) - (6);
(8) when T is equal to TmaxAnd then, inquiring the optimal objective function solution in the harmony memory library, and outputting the transmission path corresponding to the optimal objective function solution as the optimal routing path.
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EP1883184A1 (en) * 2006-07-28 2008-01-30 NTT DoCoMo, Inc. Method and apparatus for routing a message
CN103631758A (en) * 2013-11-21 2014-03-12 陕西理工学院 Method for solving non-linear programming and absolute value equation through improved harmony search algorithm
CN103916927A (en) * 2014-03-17 2014-07-09 华中科技大学 Wireless sensor network routing method based on improved harmony search algorithm
CN106550422A (en) * 2016-11-08 2017-03-29 华中科技大学 A kind of wireless sensor network clustering routing based on harmonic search algorithm

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1883184A1 (en) * 2006-07-28 2008-01-30 NTT DoCoMo, Inc. Method and apparatus for routing a message
CN103631758A (en) * 2013-11-21 2014-03-12 陕西理工学院 Method for solving non-linear programming and absolute value equation through improved harmony search algorithm
CN103916927A (en) * 2014-03-17 2014-07-09 华中科技大学 Wireless sensor network routing method based on improved harmony search algorithm
CN106550422A (en) * 2016-11-08 2017-03-29 华中科技大学 A kind of wireless sensor network clustering routing based on harmonic search algorithm

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Application publication date: 20200214