Frequency spectrum allocation method based on byte coding and regular sorting

Abstract

The invention discloses a spectrum allocation method based on byte coding and regular sorting, which is mainly used for efficiently allocating spectrum resources in the field of optical communication, and particularly can realize quick and accurate spectrum resource allocation under the condition of a transmission path of a known service request. According to the method, firstly, K possible transmission paths are calculated after a service request arrives; generally, the sorting of the paths is based on the length of the path or the hop count of the path, and the path with the shortest path length or the least hop count is preferentially selected as a main working path for service transmission. Secondly, performing spectrum resource allocation according to the selected working path, performing pre-integration and binary coding on spectrum resources of each link in the path to obtain a spectrum use condition of the whole path, and then sorting and screening the integrated spectrum resources to obtain a spectrum block suitable for a current service request; and finally, spectrum allocation is carried out according to the spectrum size required by the service request.

Description

Technical Field

[0001] The present invention belongs to the technical field of optical communication in wireless sensor networks, and particularly relates to a spectrum allocation technology. Background Art

[0002] With the rapid development of technologies such as the Internet of Things (IoT), cloud computing, and 5G, the demand for network traffic from various new services and applications has increased sharply, driving higher requirements for network transmission capabilities and service flexibility. In this context, optical networks, as information communication infrastructures, are carrying more and more traffic and need to provide higher capacity and more flexible service capabilities. Traditional Wavelength Division Multiplexing (WDM) technology has been widely used in backbone networks and metropolitan area networks. WDM realizes the efficient utilization of fiber resources by multiplexing optical signals of different wavelengths into the same optical fiber. However, with the continuous growth of network demands, WDM faces some challenges, mainly including the problem of spectrum resource allocation. Traditional WDM networks are relatively fixed in the management and scheduling of spectrum resources and cannot flexibly cope with dynamically changing network loads and service requests.

[0003] To solve these problems, in recent years, the spectrum allocation technology of optical networks has gradually shifted to the more flexible "Flex-grid" technology, which allows for more refined spectrum resource allocation between different wavelengths, thereby improving spectrum utilization and meeting diverse service requirements. Traditional wavelength division multiplexing only needs to consider wavelength consistency and wavelength continuity. In a flexible wavelength division multiplexing system, the allocation of spectrum resources needs to consider not only wavelengths but also spectrum continuity, spectrum consistency, and spectrum adjacency.

[0004] In addition, with the increasing complexity of network services and the rising requirements for real-time performance, the efficiency and accuracy of spectrum allocation algorithms have become crucial. Especially in optical transmission networks, for known service requests and transmission paths, how to quickly and accurately allocate spectrum resources has become an urgent problem to be solved. Most existing research focuses on how to improve the overall utilization rate of spectrum resources, but in practical applications, how to quickly respond and reasonably allocate spectrum resources remains a challenging task.

[0005] Regarding the spectrum allocation problem in optical networks, the current main allocation methods include three methods: First Fit, Random Fit, and Best Fit. 1. First Fit: This method retrieves the spectrum resources on the path in order until the first spectrum block that can meet the service requirements is found. Once a qualified spectrum block is found, it is immediately allocated to the current service request. 2. Random Fit: In this method, all spectrum blocks that meet the service requirements are first retrieved, and then a spectrum block is randomly selected from them for allocation. 3. Best Fit: This method comprehensively retrieves all available spectrum resources on the working path and selects the optimal spectrum block for allocation. The optimal criterion is usually to select the spectrum block that best suits the current service requirements, so as to maximize resource utilization or improve network performance. These spectrum allocation methods have their own advantages and disadvantages. For example, random allocation can perform spectrum allocation quickly, but due to its randomness, it is easy to generate more spectrum fragmentation (that is, the length of the spectrum block is less than the minimum spectrum quantity required by the service) on the working path, resulting in low utilization of spectrum resources. Seriously, this fragmentation will block the allocation of subsequent services. Although the first fit is simple to implement, its disadvantage is that it may perform repeated retrievals on the path, resulting in low efficiency of the allocation process. In addition, the spectrum utilization rate of the first fit usually cannot reach the optimal level. Although the best fit can significantly improve the spectrum utilization rate, its disadvantage is that compared with the other two methods, its allocation process takes longer and the computational complexity is higher. Summary of the Invention

[0006] To solve the above technical problems, the present invention proposes a spectrum allocation method based on byte coding and regular sorting, aiming to balance the allocation efficiency and spectrum utilization rate and optimize the use of spectrum resources in optical networks.

[0007] The technical solution adopted by the present invention is as follows: The spectrum allocation method based on byte coding and regular sorting includes the following steps:

[0008] S1. First, for the known network topology diagram, obtain the spectrum resource usage of each link in the network; and perform binary coding on the spectrum usage of each link.

[0009] S2. According to the current service request information, calculate the length of the continuous spectrum block required by the current service request.

[0010] S3. According to the source and destination information of the service request, calculate several possible paths that meet the source and destination conditions.

[0011] S4. According to the specific service requirements, select the path with the shortest length or the fewest hops as the working path from the several possible paths obtained in step S3.

[0012] S5. After selecting the working path, integrate the spectrum resource information encoded in binary for all links on this path;

[0013] S6. Use regular expressions to match the integrated spectrum resource information to obtain several consecutive available spectrum blocks;

[0014] S7. Filter out the consecutive available spectrum blocks that meet the current service requirements;

[0015] S8. Select the optimal consecutive spectrum blocks and allocate this spectrum resource to the current service request;

[0016] S9. Update the usage of spectrum resources on the selected working path.

[0017] Advantages of the present invention: The method of the present invention first calculates K possible transmission paths after a service request arrives; usually, these paths are sorted according to the length of the path or the number of hops of the path, and the path with the shortest length or the fewest hops is preferentially selected as the main working path for service transmission. Secondly, spectrum resource allocation is performed according to the selected working path. By pre-integrating and encoding the spectrum resources of each link in the path in binary, the spectrum usage of the entire path is obtained, and then the integrated spectrum resources are sorted and filtered to obtain spectrum blocks suitable for the current service request. Finally, spectrum allocation is performed according to the spectrum size required by the service request; throughout the process, byte encoding is used to represent the spectrum resources of the path, and the use of regular expressions can greatly improve the rate of spectrum allocation. Description of the Drawings

[0018] Figure 1 It is a complete flowchart of the spectrum allocation algorithm based on byte encoding and regular sorting.

[0019] Figure 2 It is a flowchart of the byte encoding of the working path.

[0020] Figure 3 It is a flowchart of the algorithm for regular sorting and allocating spectrum.

[0021] Figure 4 It is a schematic diagram of the principle of initializing available spectrum blocks in the example path.

[0022] Figure 5 It is a schematic diagram of the principle of retrieving available consecutive spectrum blocks in the example path resources.

[0023] Figure 6 It is a schematic diagram of the principle of filtering out consecutive spectrum blocks that meet the current service requirements from available spectrum resources in the example.

[0024] Figure 7Schematic diagram of the principle of selecting the best continuous spectrum block from the filtered available spectrum blocks for an example.

[0025] Figure 8 The figure shows a comparison chart of the algorithm performance between the prior art and the present invention;

[0026] Among them, (a) is the comparison of the algorithm performance between the European optical backbone network and the present invention, (b) is the comparison of the algorithm performance between the American optical backbone network and the present invention, (c) is the comparison of the algorithm performance between COST269 and the present invention, and (d) is the comparison of the algorithm performance between 6-point 9-edge and the present invention. Detailed implementation manners

[0027] To facilitate the understanding of the technical content of the present invention by those skilled in the art, the content of the present invention will be further explained below with reference to the accompanying drawings.

[0028] As Figure 1 shown, the method of the present invention includes the following steps:

[0029] S1. First, for the known network topology diagram, obtain the spectrum resource usage situation of each link in the network;

[0030] S2. According to the current service request information, calculate the length of the continuous spectrum block required by the current service request;

[0031] S3. According to the source and destination information of the service request, calculate K possible paths that meet the source and destination conditions;

[0032] S4. According to the specific service requirements, select the path with the shortest length or the fewest hops from the K possible paths obtained in step S3 as the working path;

[0033] S5. After selecting the working path, integrate the spectrum resource information of all links on this path;

[0034] S6. Based on the integrated spectrum resource information, perform spectrum allocation operations to meet the service requirements and optimize resource usage;

[0035] S7. Screen out the continuous spectrum blocks that meet the current service requirements;

[0036] S8. Select the most suitable continuous spectrum block and allocate this spectrum resource to the current service request;

[0037] S9. Update the usage situation of the spectrum resources on the selected working path.

[0038] As Figure 2 shown, the implementation process of step S1 is:

[0039] S11. Traverse all the links in the entire network topology graph and store the spectrum resource usage of each link in the spectrum usage field of its respective link.

[0040] S12. For the spectrum resources of each link, store them in binary character form, where "0" indicates that the spectrum has been used, and "1" indicates that the spectrum is in an idle state and not used. The spectrum usage of each link is represented by a string of "01" characters.

[0041] In this embodiment, step S2 specifically calculates the spectrum length required for service transmission according to different modulation methods. The specific formula is B = R / SE, where SE is the spectrum efficiency of the modulation method, with the unit of bits per hertz (bits / Hz), B is the required spectrum length, and R is the transmission rate requested by the service.

[0042] The implementation process of step S3 is as follows:

[0043] S31. Use routing algorithms such as the Floyd algorithm, two-layer DijKstra algorithm, and depth-first search to calculate the shortest path cost table of the entire network topology graph, denoted as u;

[0044] S32. Use the shortest path cost table u calculated in S31 as the evaluation function in the A* algorithm, and then use the K shortest path algorithm based on the optimized A* algorithm of Yen to calculate K alternative paths.

[0045] The value of K is generally determined according to application requirements, network size, resource conditions, and experience. If it is necessary to disperse traffic through multiple paths, the value of K can be appropriately increased, usually choosing 3 to 5 paths. If the network has high requirements for reliability and requires multiple backup paths, the value of K can be set to 2 to 4. If only the optimal path needs to be found, the value of K can be set to 1 or 2. When the number of nodes and links is small, the value of K can be set larger (such as 5 to 10) because the computational complexity is low. When the number of nodes and links is large, the value of K should not be too large (usually 3 to 5) to avoid excessive consumption of computing resources. If the computing resources are limited (such as embedded devices or real-time systems), the value of K should be small (such as 2 to 3). If the computing resources are sufficient (such as high-performance servers), the value of K can be appropriately increased. If the cost of paths in the network (such as hop count, delay, bandwidth) varies greatly, the value of K can be small because the first few paths may already be of high quality. If the path cost differences are small, the value of K can be appropriately increased to find more feasible alternative paths.

[0046] The implementation process of step S5 is as Figure 4As shown, first, initialize the available spectrum (FS) information for each path from the obtained KSP dictionary u, denoted as Fp. Initially, Fp is represented as a string of '1's, where each '1' represents an available FS. For each link e on the path, the available FS information Fp is updated with the specific FS information of link e, denoted as F[e], by performing a logical AND operation on Fp between each pair of links. This ensures that the final FS string Fp accurately represents only the FS available on all links of the entire path p. Figures 6 to 7 The regular expression sorting and spectrum allocation process for two requests are given. One request requires 3 FSs, and the other requires 4 FSs. Both requests are transmitted along the path (A, B, C). First, calculate the available FS information for the path (A, B, C) by performing a logical AND operation on the FS availability of links AB and BC. As Figure 4 shown in step 1 of, the obtained FS information Fp is represented by the string '011100111000011010', where '1' represents an available FS and '0' represents an occupied FS.

[0047] The process of regular sorting and allocating spectrum in steps S6 - S7 is as Figure 3 shown. After obtaining the binary encoding result of the working path, use regular expressions to find all consecutive available spectrum blocks, and sort them in ascending order according to the length of the found blocks; if there is a consecutive spectrum block that is the same as the current service requirement, then allocate this spectrum block to the current service; otherwise, start selecting from consecutive spectrum blocks that are larger than the sum of the spectrum quantity required by the current service and the minimum spectrum block length required by the service, and allocate the spectrum block to the current service.

[0048] The implementation process of step S6 is as Figure 5 shown. Identify consecutive blocks of available FS by using regular expressions to match all consecutive '1' sequences in the FS information string. Then add each consecutive block of available FS to the block list Bp specific to this path. The present invention uses regular expressions to identify consecutive blocks of available fs in the obtained Fp. The goal of the present invention is to find the largest consecutive block of available fs. For example, given that fs '1' and '5' are occupied, the algorithm identifies the available block [2, 3, 4] with a length of 3. The identified blocks include a block with a length of 1 located at

[19] , a block with a length of 2 located at [16, 17], a block with a length of 3 located at [2, 3, 4], and a block with a length of 5 located at [7, 8, 9, 10, 11]. The regular expression-based method can effectively identify all available consecutive segments, thus achieving effective allocation.

[0049] The basic elements of a regular expression are composed of characters and operators (meta-characters), mainly including the following categories: 1. Character classes ([a-z], [A-Z], [0-9], [a-zA-Z0-9]); 2. Predefined character classes (\d: matches any digit, equivalent to [0-9]; \D: matches any non-digit character, equivalent to [^0-9]; \w: matches any letter, digit, or underscore, equivalent to [a-zA-Z0-9_]; \W: matches any non-letter, non-digit, or non-underscore character, equivalent to [^a-zA-Z0-9_]; \s: matches any whitespace character (space, tab, newline, etc.); \S: matches any non-whitespace character); 3. Quantifiers; 4. Boundary matchers, etc. In this article, character classes are mainly used.

[0050] The matching process of a regular expression can be understood through a Finite State Automaton (FSA). There are two common matching processes: Deterministic Finite Automation (DFA) and Non-deterministic Finite Automaton (NFA). In an NFA, each element of a regular expression can have multiple transition paths. The regular engine will try multiple possible matching paths, and this process is called backtracking. The regular engine uses backtracking to complete pattern matching. The backtracking mechanism allows the engine to gradually try to match characters and return to a previous state when a match fails to try other possibilities. For example, if a regular expression includes.*abc, then during the matching process,.* will match as many characters as possible until it can no longer match, and then backtrack until a suitable matching position is found. Backtracking is the core of NFA matching, ensuring the flexibility of regular expressions but also potentially causing performance issues, especially when the regular expression is complex. When each match fails, the NFA will return to a previous state and try other paths. Different from the NFA, the DFA can only take one path during the matching process, which makes the DFA's matching process more efficient. However, its disadvantage is that it may require more states to represent the regular expression. The DFA has no backtracking, and the matching process is very efficient, especially suitable for quickly processing long strings.

[0051] Regular expressions are a powerful and flexible text pattern matching tool. By using elements such as character classes, quantifiers, grouping, and boundary matchers, they can efficiently describe the structure of strings. The regular engine performs matching in two ways: backtracking (NFA) or state machine (DFA). The time complexity of the matching process is affected by the complexity of the regular expression itself and the length of the input string. Through the optimization and reasonable use of regular expressions, various text matching tasks can be efficiently processed in practical applications. Therefore, after binary encoding the spectrum resources on the path and then using regular expressions for matching, fast retrieval and efficient resource allocation can be achieved.

[0052] The implementation process of step S7 is as Figure 6 shown. By filtering these blocks in Bp, it is determined which blocks are suitable for allocation. The length of a suitable data block must be at least equal to the FSs required by the request r. Each eligible data block filtered from Bp is added to a separate list of suitable data blocks, denoted as Hp. If no block suitable for a specific path is found, the algorithm terminates the evaluation of that path and continues with the next candidate path. Consecutive FS blocks are allocated according to the requirements of the request. For request 1 that requires 3 fs, the highest priority block is [2, 3, 4], and the next available block [7, 8, 9, 10, 11] belongs to the second priority category, and no block is suitable for the third priority. For request 2 that requires 4 fs, only the third priority block [7, 8, 9, 10, 11] is available. Therefore, the FS block [2, 3, 4] is allocated to request 1, and the FS block [7, 8, 9, 10] is allocated to request 2. Thus, [2, 3, 4] is allocated to request 1, and the fs from 7 to 10 in [7, 8, 9, 10, 11] are allocated to request 2. Finally, the FS blocks [2, 3, 4] and [7, 8, 9, 10] are allocated to requests 1 and 2 respectively. The available FS information of the updated path (A, B, C) reflects these allocations, which is '00000011001111010' for the link (A, B) and '00001000001000011111' for the link (B, C), indicating that these FSs with '0' are now occupied and cannot be used for further requests.

[0053] The implementation process of step S8 is as follows:

[0054] S81. After calculating the number of spectrum blocks (num) required for the service request, filter out the set of available spectrum blocks according to the value of num. Then, search for the spectrum block whose length is exactly equal to num from the set of available spectrum blocks and allocate it to the current service request;

[0055] S82. If there is no available continuous spectrum block with the same length as num in the set of available spectrum blocks, use the previously calculated minimum required continuous spectrum block size (num_min) for the service as the offset, and then search for a continuous spectrum block with a length of num + num_min from the available spectrum set. After finding it, allocate it to the current service request;

[0056] S83. If no suitable available spectrum block is found in the previous two steps, use the value of num + num_min as the benchmark, and select the smallest spectrum block larger than this benchmark value for allocation.

[0057] As Figure 8 shown, it is a graph comparing the performance of different algorithms with the algorithm proposed in the present invention under four networks. The calculation time of all spectrum allocation algorithms continuously increases as the number of service requests in all four network topologies increases. This trend indicates that as the network demand increases, the complexity of spectrum allocation rises, resulting in longer calculation times for all algorithms. Figure 8 (a) to 8(d) illustrate the differences between the algorithm proposed in the present invention, the first allocation, and the optimal allocation in the network topologies of 6 - point 9 - edge, COST269, European optical backbone network, and American optical backbone network. For both the first - allocation algorithm and the optimal - allocation algorithm, the calculation time significantly increases as the number of requests increases. The optimal - allocation algorithm always shows the highest calculation time, indicating its inefficiency in handling increasing demands. Although the performance of the first allocation is slightly better than that of the optimal allocation, it also faces a significant increase in calculation time as the number of requests increases. In contrast, the algorithm we proposed is always superior to the first allocation and the optimal allocation, maintaining the lowest calculation time in all scenarios. It is worth noting that regardless of the network topology or the number of service requests, our method maintains a stable and low calculation time (less than 1 second). This consistent performance across different network topologies and request matrices highlights the excellent efficiency and scalability of our method. In summary, regardless of the network scale or the number of service requests, the spectrum allocation algorithm we proposed exhibits higher computational efficiency compared to the first allocation and the optimal allocation. The results show that this method can effectively manage the complexity of spectrum allocation while maintaining a low calculation time.

[0058] Those of ordinary skill in the art will realize that the embodiments described herein are for helping the reader understand the principles of the present invention. It should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc., made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. A spectrum allocation method based on byte encoding and regular ordering, characterized in that: The following steps are involved: S1. First, for a known network topology, obtain the spectrum resource usage of each link in the network; and use binary coding for the spectrum usage of each link; S2. Calculate the length of the continuous spectrum block required by the current service request according to the current service request information; S3. Calculate several possible paths that meet the source-destination conditions according to the source-destination information of the business request; S4. According to specific business requirements, select the path with the shortest path or the least number of hops from the possible paths obtained in step S3 as the working path; S5. After selecting the working path, integrating the binary-coded spectrum resource information of all links on the path; S6. Use a regular expression to match the integrated spectrum resource information to obtain a number of continuous available spectrum blocks; S7, screening out continuous available spectrum blocks that meet current business needs; S8. Select an optimal continuous spectrum block and allocate the spectrum resource to the current service request; S9. Update the usage of spectrum resources on the selected working path.

2. The spectrum allocation method based on byte encoding and regular ordering according to claim 1, characterized in that: Step S1 specifically includes the following sub-steps: S11, traversing all links in the entire network topology diagram, and storing the spectrum resource usage of each link in the spectrum usage field of each link; S12. The spectrum resources of each link are stored in the form of binary characters, where "0" indicates that the spectrum has been used, and "1" indicates that the spectrum is idle and not used; thus, the spectrum usage of each link is represented by a binary character string.

3. The spectrum allocation method based on byte encoding and regular ordering according to claim 2, characterized in that: Step S2 specifically calculates the spectrum length required for service transmission according to different modulation modes; the calculation formula is: B=R / SE Among them, SE is the spectrum efficiency of the modulation method, B is the required spectrum length, and R is the transmission rate requested by the service.

4. The spectrum allocation method based on byte encoding and regular ordering according to claim 3, characterized in that: Step S3 specifically includes the following sub-steps: S31, calculating the shortest path cost table of the entire network topology graph; S32. Use the shortest path cost table as the evaluation function in the A-star algorithm, and calculate K candidate paths based on Yen's K shortest path algorithm optimized by A-star.

5. The spectrum allocation method based on byte encoding and regular ordering according to claim 4, characterized in that: Step S5 specifically includes the following sub-steps: S51. For the selected working path, traverse all links on the path and record the spectrum usage of each link; S52: Perform an AND operation on the binary character strings corresponding to the spectrum usage of all links bit by bit, and finally obtain the binary character string information of the overall spectrum resource of the working path.

6. The spectrum allocation method based on byte encoding and regular ordering according to claim 5, characterized in that: Step S6 specifically includes the following sub-steps: S61. Use a regular expression to match spectrum resources in binary string form on the working path to find continuous available spectrum blocks; S62: Sort all continuous available spectrum blocks in ascending order of length.

7. The spectrum allocation method based on byte encoding and regular ordering according to claim 6, characterized in that: Step S7 specifically includes the following sub-steps: S71. For the sorted continuous available spectrum blocks, firstly select the continuous available spectrum blocks whose length is greater than or equal to the minimum spectrum block length num_min required by the service; S72 . Sort the screened continuous available spectrum blocks in order of lengths of the continuous available spectrum blocks and start indexes of the continuous available spectrum blocks from small to large.

8. The spectrum allocation method based on byte encoding and regular ordering according to claim 7, characterized in that: Step S8 specifically includes the following sub-steps: S81, calculating the number num of spectrum blocks required for the service request, and filtering out a set of available spectrum blocks from the continuous available spectrum blocks sorted in step S7 according to the value of num; S82. If there is a continuous available spectrum block with a length equal to num in the available spectrum block set, allocate the continuous available spectrum block to the current service request; otherwise, execute step S83; S83, using num_min as the offset, searching for a continuous spectrum block of length num+num_min from the available spectrum block set, and assigning it to the current service request after finding it; otherwise, executing step S84; S84. Taking the value of num+num_min as a reference, select a minimum spectrum block that is greater than the reference value for allocation.

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