CN102970223B - There is the Epidemic method for routing of avoidance mechanism - Google Patents

Abstract

The invention relates to an opportunistic network routing algorithm, which is used to improve the Epidemic routing algorithm so that nodes in the opportunistic network can efficiently forward data packets while consuming as little network resources as possible. Epidemic routing algorithm can achieve high transmission success rate and low transmission delay in some scenarios, but the adaptability of the algorithm is poor, and in other scenarios, the performance of the algorithm will drop sharply. The invention proposes a backoff mechanism, and uses the mechanism to improve the Epidemic routing algorithm. The backoff mechanism can effectively reduce the number of data packet copies in the network, suppress the crowding out effect, improve the performance of the routing algorithm, and then improve the scalability of the Epidemic routing algorithm.

Description

Epidemic Routing Method with Backoff Mechanism

technical field

The invention relates to an opportunistic network routing algorithm, which is used to enable nodes in the opportunistic network to efficiently forward data packets while reducing network resource consumption as much as possible.

Background technique

An opportunistic network is a self-organizing network that can tolerate network communication, delay and split by using the encounter opportunities brought about by node movement without the need for a complete path between the source node and the destination node. Opportunistic networks are different from traditional multi-hop wireless networks in that their nodes are not uniformly deployed, the network scale and the initial positions of nodes are not preset, and the path between source nodes and destination nodes cannot be determined in advance. Opportunistic networks use the "store-carry-forward" mode to transmit information hop by hop to achieve inter-node communication. Its architecture is different from multi-hop wireless networks. It inserts a new protocol called bundle layer between the application layer and the transport layer. layer.

Because opportunistic networks can deal with problems that are difficult to solve with traditional wireless network technologies such as network splitting and delay, and can meet the needs of network communication under harsh conditions, it is mainly used in situations where there is a lack of communication infrastructure, harsh network environments, and emergencies. .

1. Contrast routing algorithm

In order to compare with the routing algorithm of the present invention, two typical routing algorithms are selected as reference algorithms. Epidemic algorithm is a typical representative of routing algorithm based on flooding strategy, and many routing algorithms based on flooding strategy can be regarded as derived from this algorithm. The SprayandWait algorithm performs flooding according to a certain strategy and is based on a limited flooding strategy. The main performance indicators of the algorithm have significant advantages in most scenarios.

(1) Epidemic algorithm

The basic idea of the Epidemic algorithm is that when two nodes meet, they exchange data packets that the other party does not have. After enough exchanges, theoretically each non-isolated node will receive all data packets, thereby realizing the transmission of data packets.

In the Epidemic algorithm, each data packet has a globally unique identifier, and a summary vector is saved in each node to record the data packets carried in the node. When two nodes meet, the two parties first exchange summary vectors, and after knowing the data packets carried by the other party, the two parties only transmit the data packets that the other party does not have.

The Epidemic algorithm is essentially a flooding algorithm. In theory, this algorithm can maximize the success rate of data packet transmission and minimize transmission delay, but it will also cause a large number of data packet copies in the network and consume a large amount of network resources. .

The Epidemic algorithm has three goals, which are the maximum transmission success rate, the minimum transmission delay and the minimum network resource consumption. Achieving the above goals requires specific scenarios. In most scenarios, the performance of routing algorithms is significantly degraded due to excessive flooding.

(2) SprayAndWait algorithm

The SprayandWait algorithm is divided into two stages. The first is the Spray stage, where some data packets in the source node are diffused to neighboring nodes; then enter the Wait stage, if the target node is not found in the Spray stage, the node containing the data packet will transmit the data packet to the target node in DirectDelivery mode, that is, only When a target node is encountered, a data packet is sent. The transmission volume of this algorithm is significantly less than that of the Epidemic algorithm, the transmission success rate is high, the transmission delay is small, and the algorithm has strong applicability.

2. Metrics

The metrics for evaluating the performance indicators of opportunistic network routing algorithms mainly include:

(1) Transmission success rate

DeliveryRatio is the ratio of the total number of data packets successfully arriving at the target node to the total number of data packets sent by the source node within a certain period of time. This indicator describes the ability of the routing algorithm to correctly forward data packets to the target node. important indicators.

(2) Transmission delay

Delivery Delay (Delivery Delay) is the time required for a data packet to reach the destination node from the source node, and is usually evaluated by the average delivery delay. Small transmission delay means that the routing algorithm has strong transmission capability and high transmission efficiency, and it also means that less network resources will be occupied during the transmission process.

(3) Routing overhead

Routing overhead (Overhead) refers to the total number of data packets forwarded by nodes within a certain period of time, and is usually evaluated by the ratio of the number of data packets successfully reaching the target node to the total number of data packets forwarded by all nodes. High routing overhead means that nodes forward a large number of data packets, which will flood the network with a large number of data packet copies, increase the probability of data packet collisions, and consume a large amount of node energy.

3. Performance analysis of Epidemic algorithm

Based on the scenario in Table 1, the total number of data packets is 50 and each node generates 10 data packets for simulation respectively, and the results shown in Figure 1 and Figure 2 are obtained.

In Figure 1 and Figure 2, SprayAndWait is used as the comparison algorithm. This algorithm can obtain near-optimal transmission success rate and routing overhead in most scenarios, and can maintain good performance regardless of the size of the network. scalability.

From Figure 1 and Figure 2, the following conclusions can be drawn:

(1) In some specific scenarios, the Epidemic algorithm has a very high transmission success rate and a very low transmission delay, which is much better than the comparison algorithm in these two indicators;

(2) When the number of data packets is constant, the increase in the number of nodes in the network will improve the performance of the routing algorithm;

(3) In some scenarios, there are some factors closely related to the network application environment that will lead to a significant decline in the performance of the Epidemic algorithm.

Based on the scenario in Table 1, Figure 3 describes the relationship between the number of data packets and the success rate of transmission when the total number of nodes is certain. It can be seen from Figure 3 that when the number of data packets increases, the success rate of transmission decreases accordingly. The present invention refers to the cause of this phenomenon as the crowding out effect, that is, when the total number of data packets to be transmitted in the network exceeds the total amount of data packets that can be stored by the node, the node cache saturation phenomenon will occur, and the node receives new data at this time When the packets are processed, the old data packets have to be discarded according to certain rules. The existence of this effect leads to a significant decline in the performance of the Epidemic algorithm.

Contents of the invention

The present invention relates to a new opportunistic network routing algorithm. The algorithm introduces a back-off mechanism on the basis of the Epidemic routing algorithm. When the node buffer is full, the nodes that meet it will no longer forward data packets to it according to certain rules, that is, back off. The algorithm of the invention can effectively restrain crowding out effect, obtain higher transmission success rate and lower consumption of network resources.

The specific scheme of the algorithm of the present invention is to add the following (1)-(4) mechanisms on the basis of the original mechanism of the Epidemic algorithm, which is called the backoff mechanism in the present invention, and the Epidemic algorithm with the backoff mechanism is called the BackoffEpidemic algorithm.

The specific description of the mechanism is as follows:

(1) The node maintains a field, which is used to store the threshold t;

(2) The threshold t is randomly generated and obeys the uniform distribution. Its value range is (0, x), and x is a parameter, which is determined according to the network conditions;

(3) When the cache of a certain node is full, within the time t, the node refuses to receive the data packets whose target node is not the node, that is, the data packets of other nodes are backed off within the threshold time;

(4) When the backoff time exceeds the threshold t, no matter the node cache status will receive data packets, crowding out events may still occur at this time. After a packet is received, the backoff time is reset to 0.

Description of drawings

Figure 1 Comparison of transmission success rate

Figure 2 Transmission delay comparison

Figure 3 The impact of the number of data packets on the transmission success rate

Figure 4 The transmission success rate of the improved algorithm in different scenarios

Figure 5 Transmission delay of the improved algorithm in different scenarios

Figure 6 Routing overhead of the improved algorithm in different scenarios

detailed description

The principles and features of the present invention are described below, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

Use ONE (theOpportunisticNetworkingEnvironment) simulation platform to implement the routing algorithm involved in the present invention. In the following simulation, pedestrians carrying smart Bluetooth devices are simulated walking in a real urban scene, and used to implement and analyze the performance of the routing algorithm. The specific scene settings are shown in Table 1.

Table 1 Simulation scene settings

In this simulation experiment, the value of the parameter x is 100 seconds; based on the scenario in Table 1, each node generates 10 data packets at equal time intervals. Taking 5 nodes as an example, there are 50 data packets in the network packet, the simulation time is 12 hours, that is, a data packet is generated every 864 seconds, and the results are shown in Figure 4 to Figure 6.

In this simulation, the number of nodes and data packets increase simultaneously, and the increase in the number of nodes will increase the success rate of transmission, while the number of data packets exceeding the threshold will lead to crowding out effect. Figure 4 to Figure 6 are the results of the superposition of the two effects.

It can be seen from Figure 4 that when the number of nodes is small, taking 10 nodes as an example, although the cache ratio is less than 1, since a data packet is generated every 432 seconds, and it takes a certain time for the data packet to spread to other nodes, in the simulation The crowding out effect will not occur in the early stage, and the advantages of the improved algorithm are not obvious at this time.

When the number of nodes and data packets is large, such as 160 nodes, the cache ratio reaches 0.018. At this time, a significant crowding out effect will occur. The backoff mechanism in the improved algorithm plays a significant role. The BackoffEpidemic algorithm has a significantly higher transmission success rate than the Epidemic algorithm. , up to 79.5%.

It can be seen from the previous description about the backoff mechanism that it will have an adverse effect on the transmission delay, but the experimental results in Figure 5 show that this effect is not significant.

It can be seen from Figure 6 that the BackoffEpidemic algorithm has a certain impact on the routing overhead of the algorithm when there are many nodes. For example, when there are 160 nodes, the routing overhead of the BackoffEpidemic algorithm is significantly lower than that of the Epidemic algorithm, reaching 36.7%.

It can be seen from this embodiment that the Epidemic algorithm with a backoff mechanism proposed by the present invention can effectively reduce the number of data packets in the network, suppress the crowding out effect, improve the performance of the routing algorithm, and expand the scope of application of the Epidemic routing algorithm.

Claims (2)

1. an opportunistic network routing method, it is characterized in that, comprise principle, parameter and the course of work of this method for routing, this method for routing is that the one of Epidemic method for routing is improved, this method for routing is to have introduced avoidance mechanism on the basis of Epidemic method for routing, and this avoidance mechanism comprises:

Field of node maintenance, this field is used for depositing threshold value t;

After a certain nodal cache is full of, in time t, this node rejection destination node is not the packet of this node, within the threshold value moment, makes the packet of other nodes keep out of the way;

When back off time exceedes after threshold value t, no matter nodal cache state all receives packet, and when node receives after packet, it is 0 that its back off time is reset.

2. opportunistic network routing method according to claim 1, is characterized in that, threshold value t is random generation, and obedience is uniformly distributed, and its value scope is that (0, x), x is parameter, determines according to network condition.