Wireless body area network dynamic resource management method based on hybrid star topology

Abstract

The invention discloses a hybrid star topology-based wireless body area network dynamic resource management method, which comprises the following steps of: constructing a hybrid star topology framework comprising a main coordinator and an edge coordinator, classifying acquired physiological monitoring data through the main coordinator to correspond to A-type emergency data, B-type inspection data and C-type common data, and performing data processing on the classified data; a dynamic priority formula is designed for weighted calculation and real-time adjustment of a data transmission sequence, and it is preferentially guaranteed that the A-type emergency data preempts channel resources; when the channel utilization rate is gt; triggering migration evaluation and adopting a double-stage migration process when the class-A emergency data conflict exists at 80% and the class-A emergency data conflict exists; if the original channel utilization rate is lt; if 30%, automatically releasing to a global standby pool; transmitting power is adjusted in real time, a contention window is dynamically adjusted for channel conflicts of ABC three types of data, and PID parameter self-adaptive optimization is triggered after the conflicts continuously occur for three times; and the node is automatically switched to a low-power-consumption mode after data transmission is finished until the node is awakened in the next beacon period.

Description

Technical Field

[0001] The present invention relates to a dynamic resource management method for a wireless body area network based on a hybrid star topology. Background Art

[0002] Wireless Body Area Networks (WBANs), a core technology in medical monitoring and health surveillance, use sensor nodes deployed on the human body to collect real-time physiological data (such as heart rate, blood pressure, and blood sugar) and transmit it to end devices or the cloud for analysis and processing via low-power wireless communication technologies. With the deepening integration of the Internet of Things (IoT) and healthcare needs, WBANs are placing higher demands on network real-time performance, reliability, and energy efficiency. However, existing technologies still have significant limitations in dynamic resource management, multi-channel collaboration, and energy optimization, urgently requiring innovative solutions.

[0003] Traditional WBANs often employ a single centralized topology (such as the ZigBee-based star structure), relying on a single coordinator for network-wide synchronization and resource allocation. This architecture presents challenges such as a high risk of single points of failure and poor scalability. In mobile healthcare scenarios, the coordinator's processing power is insufficient to cope with the demand for concurrent access from multiple nodes. Some research has attempted to incorporate edge computing nodes to assist in management, but these efforts lack clear functional boundaries and coordination mechanisms for edge nodes, resulting in increased signaling overhead and inefficient resource scheduling.

[0004] Existing WBAN protocols (such as IEEE 802.15.6) often use a fixed channel allocation model, where the master coordinator statically allocates management and data channels. However, in medical scenarios, channel interference (e.g., Wi-Fi, Bluetooth) and traffic loads vary significantly, and static allocation can easily lead to low channel utilization and frequent conflicts. For example, when sudden, urgent data (such as ventricular fibrillation alarms) competes for the same channel with periodic physiological data (e.g., electrocardiograms), traditional static scheduling cannot prioritize the higher-priority service, resulting in transmission delays and data loss.

[0005] Existing research often allocates resources based on fixed priorities (e.g., A / B / C traffic), but lacks dynamic adjustment capabilities. For example, a blood pressure monitoring node for a chronic patient is long classified as Class C. However, during an acute hypertension attack, it cannot be upgraded to Class B in real time to obtain higher bandwidth, resulting in delayed monitoring data. Furthermore, existing dynamic priority formulas often rely on a single parameter (e.g., data arrival rate or buffer occupancy), ignoring traffic characteristics such as migration sensitivity and remaining energy, making them difficult to adapt to the needs of complex medical scenarios.

[0006] To address channel congestion, some solutions have proposed channel switching mechanisms. However, these mechanisms suffer from issues such as unreasonable migration triggering thresholds (e.g., requiring migration only when utilization exceeds 90%) and lengthy migration processes. For example, single-channel migration requires a complete data buffer switch, leading to service interruption during the migration. Coarse-grained migration strategies (e.g., full channel switching) can easily lead to channel fragmentation and reduce spectrum utilization. Furthermore, frequent sensor node wakeups and data retransmissions during frequent migrations lead to significant energy consumption spikes, which contradicts the long-term battery life requirements of WBANs.

[0007] Existing WBAN protocols often use fixed transmit power, failing to account for node mobility or changes in environmental interference. For example, when human movement reduces the distance to the receiver, excessively high transmit power not only exacerbates interference with neighboring nodes but also accelerates node energy depletion. While some research has introduced dynamic power control, these are often based on simple feedback mechanisms (such as the Received Signal Strength Indicator (RSSI)) and lack adaptability to multipath fading and nonlinear interference, making them difficult to operate stably in complex medical environments. Summary of the Invention

[0008] The present invention aims to solve the above problems in the prior art and provides a dynamic resource management method for a wireless body area network based on a hybrid star topology.

[0009] The technical solutions adopted in the present invention are:

[0010] A method for dynamic resource management of a wireless body area network based on a hybrid star topology comprises the following steps:

[0011] 1) Build a hybrid star topology architecture consisting of a master coordinator and edge coordinators. The master coordinator serves as the global control hub and uses a software-defined networking (SDN) architecture to implement network topology management, time synchronization, and global notification of channel load status. The edge coordinators serve as distributed control nodes and perform localized channel migration assessment and dual-channel parallel migration based on a dynamic channel status table.

[0012] 2) The main coordinator classifies the physiological monitoring data collected in the wireless body area network into Class A emergency data, Class B inspection data, and Class C general data. A dynamic priority formula is designed to use weighted calculations to adjust the data transmission order in real time, giving priority to Class A emergency data in preempting channel resources.

[0013] 3) The edge coordinator monitors channel utilization. When channel utilization exceeds 80% and a Class A emergency data conflict occurs, a migration assessment is triggered, using a two-stage migration process. After the migration is complete, if the original channel utilization is less than 30%, it is automatically released to the global spare pool.

[0014] 4) Based on the signal strength deviation value, the incremental PID algorithm adjusts the transmit power in real time. At the same time, the contention window is dynamically adjusted to address channel conflicts for the three types of data (ABC). After three consecutive conflicts, the PID parameter adaptive optimization is triggered.

[0015] 5) After the data transmission is completed, the node automatically switches to low power mode until it wakes up in the next beacon cycle. The edge coordinator combines the channel migration and power control strategies described in steps 3 and 4 to dynamically optimize channel resource allocation and transmission power.

[0016] Furthermore, in step 2, the dynamic priority formula is expressed as:

[0017]

[0018] Among them, P represents the priority of data; is the node category, where category A = 7, category B = 6, category C = 5; used Indicates the buffer occupancy rate; B max Indicates the maximum capacity of the buffer; is the data arrival rate.

[0019] Furthermore, in step 3, the two-stage migration process includes:

[0020] Header information pre-migration: Send the migration request packet header information to the target channel and receive the confirmation frame;

[0021] Payload confirmation migration: After receiving the confirmation frame, the data payload is migrated to the target channel segment by segment.

[0022] Furthermore, in step 4, the control increment of the incremental PID algorithm is expressed as:

[0023]

[0024] Among them, Δ u (k) represents the control increment; K p ,K i ,K d They represent the control coefficients of the proportional, integral, and differential terms respectively; e(k) represents the current signal strength deviation; e(k−1) represents the signal strength deviation of the previous round; and e(k−1) represents the signal strength deviation of the previous two rounds.

[0025] Furthermore, in step 5, the edge coordinator combines the channel migration and power control strategies described in steps 3 and 4 to dynamically optimize channel resource allocation and transmit power. The specific operations include:

[0026] Monitor the load status of the current channel;

[0027] If the load is too high or there is an urgent need for data transmission, channel migration will be performed first;

[0028] According to the channel status after migration, the transmit power is adjusted to balance energy efficiency and transmission reliability.

[0029] Furthermore, in step 5, the operation of the node entering the low power consumption mode includes:

[0030] After data transmission is completed, unnecessary functional modules are shut down to reduce energy consumption;

[0031] Set a timer to automatically wake up when the next beacon cycle arrives;

[0032] After waking up, re-evaluate the current channel status and data transmission requirements.

[0033] The present invention achieves a balance between low power consumption and high reliability through a dynamic sleep strategy and an energy efficiency and performance coordination mechanism: the node automatically switches to a low power consumption mode after the data transmission is completed and does not wake up until the next beacon cycle, thereby reducing ineffective energy consumption; at the same time, it combines channel migration and power control strategies to dynamically optimize channel resource allocation and transmission power, reducing energy consumption while maintaining network performance, thereby extending the node's battery life and resolving the contradiction between energy efficiency and performance that is difficult to strike a balance in traditional solutions.

[0034] The present invention has the following beneficial effects:

[0035] This invention uses a master coordinator (SDN controller) and edge coordinators (such as smartphones) to achieve efficient resource scheduling. This eliminates the need for network nodes to compete for a single channel and instead allows them to utilize multiple channels for data transmission. This design effectively distributes data traffic, significantly reducing the probability of data collisions and, consequently, significantly reducing network latency. Furthermore, the multi-channel mechanism significantly alleviates network congestion and reduces energy loss, thereby comprehensively improving the overall network performance and system quality of service of the wireless body area network. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a hybrid star topology diagram of the wireless body area network in an embodiment of the present invention.

[0037] Figure 2 4 is a superframe structure diagram of a wireless body area network in an embodiment of the present invention.

[0038] Figure 3 This is a flow chart of a method for dynamic resource management of a wireless body area network based on a hybrid star topology in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described below with reference to the accompanying drawings.

[0040] like Figure 1 As shown, this embodiment of the present invention utilizes a hybrid star-topology wireless body area network (WBAN). Building on the existing star topology, it introduces edge coordinators (such as smartphones or local gateways) as secondary control nodes. The primary coordinator (SDN controller) adds a global channel utilization notification field when synchronizing global time via extended beacon frames. When edge coordinators broadcast detailed time slot allocations on their local subnets, they also include the current channel migration status identifier. Each edge coordinator maintains a dynamic channel status table, which contains mappings between the primary channel load ratio, a backup channel pool (six pre-stored backup channels), and service priority levels.

[0041] Set thresholds and classify various sensor nodes according to monitoring requirements. Dynamic node classification adjustment mechanism is as follows:

[0042] Basic physiological indicator monitoring equipment (heart rate / blood pressure) is initially classified as Class B nodes;

[0043] Special monitoring equipment (blood sugar / body temperature) is initially classified as a Class C node;

[0044] When the monitoring data exceeds the preset threshold, the node category level is dynamically upgraded;

[0045] Make personalized adjustments based on the patient's individual health status (e.g., upgrade the blood pressure monitoring node to Class B for hypertensive patients).

[0046] like Figure 2 As shown, in this embodiment of the present invention, the wireless body area network adopts a superframe structure consisting of an active period and a dormant period. The active period is divided into four phases in the order of execution: a beacon phase, a channel allocation phase, a dynamic scheduling phase, and finally a data transmission phase. After each phase is completed in sequence, the dormant period begins.

[0047] A new channel migration evaluation sub-phase is added to the dynamic scheduling phase of the superframe structure: the edge coordinator calculates channel utilization based on a sliding window with a 5-superframe period; when it detects that the channel utilization is greater than 80% and there is a Class A service request conflict, a migration evaluation is triggered; and through the spectrum sensing mechanism of the backup channel pool, the backup channel with the least interference is selected to perform migration preparation.

[0048] In the beacon phase, the coordinator achieves time synchronization of network nodes by broadcasting beacon frames, which synchronously carry global channel load status information.

[0049] During the channel allocation phase, the coordinator scans available channel resources and reserves management channels for Class A / B services first, and the remaining channels are divided into N data channels.

[0050] During the dynamic scheduling phase, this protocol uses a three-level priority classification mechanism to manage transmitted data:

[0051] A Emergency data (alarm of abnormal vital signs);

[0052] B. Inspection data (routine physiological parameter monitoring);

[0053] C general data (device status information);

[0054] New dynamic priority calculation formula:

[0055]

[0056] Among them, P represents the priority of data; is the node category, where category A = 7, category B = 6, category C = 5; used Indicates the buffer occupancy rate; B max Indicates the maximum capacity of the buffer; is the data arrival rate.

[0057] During the data transmission phase, if a wireless sensor node has a data transmission requirement, it first checks the initial channel usage status. If the channel is idle, it directly performs the data transmission task through the initial channel. If the initial channel is occupied, it selects another data channel from the available channel set to complete the data transmission. When the data transmission process is completed, the sensor node will automatically switch to low-power sleep mode and remain in this state until the end of the current beacon period. A new dynamic channel migration process has been added to the data transmission phase:

[0058] When detecting that the initial channel utilization is >80%, the edge coordinator triggers migration evaluation;

[0059] Through the dual-channel parallel transmission mechanism, Class C services are switched to the backup channel 5;

[0060] The migration process adopts two stages: header information pre-migration + payload confirmation migration.

[0061] After the migration is completed, the channel elastic release mechanism is triggered. If the original channel utilization rate is less than 30%, it is released to the global spare pool.

[0062] like Figure 3 FIG2 is a specific flow chart of a method for dynamic resource management of a wireless body area network based on a hybrid star topology in an embodiment of the present invention.

[0063] Step 1: In the beacon phase, the coordinator broadcasts beacon frames to the wireless body area network to achieve node time synchronization.

[0064] Step 2: In the channel allocation phase, the coordinator divides the functions of all available channels into two categories: a single management channel and multiple data channels. It also implements a dedicated configuration for each wireless sensor node, that is, designates a data channel as the initial communication channel for the node.

[0065] Step 3: The sensor node implements a dynamic category adjustment mechanism based on the type characteristics of the collected data and the comparison results of its value with the preset threshold, and temporarily stores the data to be transmitted in its built-in data buffer.

[0066] Step 4: When the sensor node has data to send, it sends a request frame to the coordinator. The request frame contains detailed information such as the category information of the sensor node, the current sampling rate parameters, the length specifications of the data packet to be transmitted, and the current occupancy status of the node buffer.

[0067] Step 5: When a wireless sensor node needs to send data, it first checks the pre-assigned initial channel for availability. If the detection result shows that the initial channel is available, the data transmission operation is directly carried out through the initial channel. If the initial channel is occupied, the system automatically selects one of the other available data channels to complete the data transmission task.

[0068] Step 5a: When the sensor node detects that the initial channel is occupied, the edge coordinator checks whether there is any Class C service to be migrated in the migration queue;

[0069] Step 5b: If there is a service to be migrated, the coordinator sends a migration instruction to the source node, including the target channel identifier and the migration time window;

[0070] Step 5c: After the source node completes data buffer migration on the target channel, it switches the Class C service data to the backup channel 5 through the dual-channel parallel transmission mechanism, and the primary channel 1 only retains Class A / B services;

[0071] Step 5d: A two-stage confirmation mechanism is used during the migration process: first, the packet header information is migrated, and then the data payload is migrated after the receiving end returns confirmation, ensuring data integrity during the migration process.

[0072] Step 6: When the wireless sensor node selects a data channel other than the initial channel, it will evaluate and compare the priority of the data to be sent with the data currently being transmitted on the currently selected data channel. This protocol categorizes data into three categories, from high to low urgency: A. Emergency data (highest priority); B. Inspection data (medium priority); and C. Normal data (basic priority). If the evaluation determines that the priority of the data to be sent is higher than the data currently being transmitted on the currently selected data channel, the wireless sensor node will terminate the original data transmission process on that channel and then use the channel resources to transmit its own high-priority data.

[0073] Conflict avoidance mechanism

[0074] Step 6a: After the node detects that the channel is idle, it waits for a random backoff time. , t backoff represents the backoff time, that is, the time a node needs to wait after detecting that the channel is idle; CW represents the contention window size, which is a dynamically adjusted parameter with an initial value and maximum value that can be set according to network conditions; rand(0,1) represents a random number generated between 0 and 1, which is used to introduce randomness to prevent multiple nodes from competing for the channel at the same time.

[0075] Step 6b: If a conflict occurs, dynamically adjust the CW value according to the fuzzy logic rules (initial After three consecutive conflicts );

[0076] Step 6c: The backoff times are linked to the power control parameters, and each conflict triggers an adaptive adjustment of the PID parameters.

[0077] The priority calculation method for sensor nodes is:

[0078]

[0079] in:

[0080] is the node category (A=7 / B=6 / C=5), is the buffer occupancy, is the data arrival rate, For business rate requirements, is the maximum supported rate of the channel, is the weight coefficient of the basic resource, is the weight coefficient of the remaining energy, is the migration sensitivity coefficient (C type business =0.7, Class A / B =0).

[0081] Step 7: If the priority of the data to be sent is lower than the data being transmitted in the currently selected data channel, the wireless sensor node will enter a waiting state until the data transmission process on the channel is completely completed, and then use the channel resources to transmit its own data.

[0082] Step 8: When the coordinator successfully completes the data reception operation, it will send a confirmation frame back to the sender of the data to indicate successful reception.

[0083] Step 9: As the sender, the sensor node determines that the data transmission process has been completed after receiving the confirmation frame sent back by the coordinator, and then enters a low-power sleep mode until the end of the current beacon cycle; if no confirmation frame is received within the preset time, the data retransmission mechanism is automatically triggered.

[0084] Step 10. After the migration of Class C services is completed, the edge coordinator updates the local channel status table and triggers the channel elastic release mechanism: if the original channel utilization rate is less than 30% after the migration, the channel resources are released to the global spare pool.

[0085] In addition, given that the distance between the WBAN and the service center changes dynamically during movement, maintaining the original transmission power level when the distance between the two decreases will not only lead to an abnormal increase in energy consumption on the coordinator side, but also interfere with the normal communication of other nearby WBANs. To this end, the service center monitors the received WBAN coordinator signal strength in real time and compares it with the preset expected signal strength to calculate the deviation value e, and then adopts a discrete incremental PID control algorithm:

[0086]

[0087] in, 、 、 Represent the proportional term, differential term, and integral term respectively. Before The signal strength deviation received by the wheel, To control the coordinator's transmission power in the next round.

[0088] In summary, the dynamic resource management method for wireless body area networks (WBANs) based on a hybrid star topology proposed in this paper utilizes a master coordinator (SDN controller) and edge coordinators (e.g., smartphones) to achieve efficient resource scheduling through collaborative work. This eliminates the need for network nodes to compete for a single channel and instead allows them to utilize multiple channels for data transmission. This design effectively distributes data traffic, significantly reduces the probability of data collisions, and thus significantly reduces network latency. Furthermore, the multi-channel mechanism significantly alleviates network congestion and effectively reduces energy loss, thereby comprehensively improving the overall network performance and system quality of service of the WBAN.

[0089] The above description is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements can be made without departing from the principles of the present invention. These improvements should also be regarded as the scope of protection of the present invention.

Claims

1. A method for dynamic resource management in a wireless body area network based on a hybrid star topology, characterized by: The following steps are involved: 1) Build a hybrid star topology architecture consisting of a master coordinator and edge coordinators. The master coordinator serves as the global control hub and uses a software-defined networking (SDN) architecture to implement network topology management, time synchronization, and global notification of channel load status. The edge coordinators serve as distributed control nodes and perform localized channel migration assessment and dual-channel parallel migration based on a dynamic channel status table. 2) The main coordinator classifies the physiological monitoring data collected in the wireless body area network into Class A emergency data, Class B inspection data, and Class C general data. A dynamic priority formula is designed to use weighted calculations to adjust the data transmission order in real time, giving priority to Class A emergency data in preempting channel resources. 3) The edge coordinator monitors channel utilization. When channel utilization exceeds 80% and a Class A emergency data conflict occurs, a migration assessment is triggered and a two-stage migration process is adopted. After the migration is completed, if the original channel utilization is less than 30%, it will be automatically released to the global spare pool; 4) Based on the signal strength deviation value, the incremental PID algorithm adjusts the transmit power in real time. At the same time, the contention window is dynamically adjusted to address channel conflicts for the three types of data (ABC). After three consecutive conflicts, the PID parameter adaptive optimization is triggered. 5) After the data transmission is completed, the node automatically switches to low power mode until it wakes up in the next beacon cycle. The edge coordinator combines the channel migration and power control strategies described in steps 3 and 4 to dynamically optimize channel resource allocation and transmission power.

2. The method for dynamic resource management of a wireless body area network based on a hybrid star topology according to claim 1, wherein: In step 2, the dynamic priority formula is expressed as: Among them, P represents the priority of data; is the node category, where category A = 7, category B = 6, category C = 5; used Indicates the buffer occupancy rate; B max Indicates the maximum capacity of the buffer; is the data arrival rate.

3. The method for dynamic resource management of a wireless body area network based on a hybrid star topology according to claim 1, wherein: In step 3, the two-phase migration process includes: Header information pre-migration: Send the migration request packet header information to the target channel and receive the confirmation frame; Payload confirmation migration: After receiving the confirmation frame, the data payload is migrated to the target channel segment by segment.

4. The method for dynamic resource management of a wireless body area network based on a hybrid star topology according to claim 1, wherein: In step 4, the control increment of the incremental PID algorithm is expressed as: Among them, Δ u (k) represents the control increment; K p ,K i ,K d They represent the control coefficients of the proportional, integral, and differential terms respectively; e(k) represents the current signal strength deviation; e(k−1) represents the signal strength deviation of the previous round; and e(k−1) represents the signal strength deviation of the previous two rounds.

5. The method for dynamic resource management of a wireless body area network based on a hybrid star topology according to claim 1, wherein: In step 5, the edge coordinator combines the channel migration and power control strategies described in steps 3 and 4 to dynamically optimize channel resource allocation and transmit power. The specific operations include: Monitor the load status of the current channel; If the load is too high or there is an urgent need for data transmission, channel migration will be performed first; According to the channel status after migration, the transmit power is adjusted to balance energy efficiency and transmission reliability.

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