Non-uniform vehicle task unloading method for dealing with sparse RSU edge network

Abstract

The invention discloses a non-uniform vehicle task unloading method for coping with a sparse RSU edge network, and belongs to the technical field of communication. In order to solve the problems of transmission link interruption and task unloading failure possibly caused by high mobility and non-uniform driving of road vehicles in a sparse RSU edge network scene, the invention provides a non-uniform vehicle task unloading method for coping with a sparse RSU edge network. According to the method, the problems of short link duration and no RSU coverage between the vehicles and the RSU are solved through a mode of establishing a forwarding link between the vehicles, and a V2I, V2V2I and vehicle local unloading hybrid unloading mode is adopted, so that the task unloading efficiency of the system is improved. The unloading period is dynamically adjusted according to the real-time speed of the vehicle, and the optimal unloading mode and computing resource allocation are selected according to the real-time position of the vehicle and the computing resource state of the system, so that the task completion rate of the system is maximized, and the unit task unloading time delay is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a method for unloading non-uniform speed vehicle tasks in response to a sparse RSU edge network. Background Art

[0002] With the rapid development of Internet of Vehicles (IoV) technology, a large number of delay-sensitive and computation-intensive in-vehicle applications are emerging. Providing vehicle-to-infrastructure (V2I) edge computing services for mobile vehicles on the road through roadside units (RSU) has become a mainstream solution for current IoV business applications.

[0003] However, most of the existing research on the problem of vehicle task offloading in edge networks considers the ideal scenario of vehicles traveling on roads with full coverage of RSUs. Less research is done on the possibility that sparse deployment of RSUs or RSU failures may lead to the loss of network functions on some road sections. The high mobility and non-uniform speed characteristics of vehicles may further lead to frequent interruptions of transmission links or task losses, resulting in task offloading failures or deterioration of service quality.

[0004] In view of the above problems, the present invention proposes a method for unloading tasks of non-uniform vehicles in sparse RSU edge networks. According to the speed change characteristics of the task vehicle and the task delay constraint, the task unloading cycle is dynamically planned, and a hybrid unloading mode combining local (Local), vehicle-to-infrastructure (V2I), and vehicle-to-vehicle-to-infrastructure (V2V2I) is adopted to dynamically adjust the task scheduling strategy and computing resource allocation strategy, which can maximize the task completion rate and reduce the system unit task unloading delay. Summary of the invention

[0005] The present invention aims to solve the above problems of the prior art. A method for unloading tasks of non-uniform vehicles in a sparse RSU edge network is proposed. The technical solution of the present invention is as follows:

[0006] A method for offloading non-uniform speed vehicle tasks in a sparse RSU edge network comprises the following steps:

[0007] 101. According to the unloading request of task vehicle i, obtain the task data volume s i , the computational complexity of the task is c i , task delay threshold Initialize the remaining task amount of task vehicle i Remaining Tolerable Delay Unloading cycle number k = 0;

[0008] 102. Let k = k + 1, according to the current speed v of task vehicle i i, calculate the kth unloading cycle duration t of task vehicle i i,k , the maximum number of tasks that can be processed in the local offload mode s i,k , and the unit task processing delay τ in Local mode i,k , let the unloading mode model of task vehicle i in the kth cycle be Local, and the unloading task volume of task vehicle i Unit task processing delay

[0009] 103. If the mission vehicle i is within the coverage of any roadside unit RSU j, according to the link duration between the mission vehicle i and RSU j and the computing resources that RSU j can allocate to task vehicle i calculate The maximum amount of tasks that RSU j can handle in V2I offloading mode in the time period of task vehicle i i,k , jump to step 104, otherwise, jump to step 106;

[0010] 104. If i,k > 0, calculate the unit task processing delay τ of task vehicle i in V2I offloading mode i,k , jump to step 105, otherwise, jump to step 106;

[0011] 105. If Let model = V2I, Jump to step 107, otherwise, jump to step 107;

[0012] 106. Find the best relay vehicle i′ in V2V2I unloading mode for task vehicle i, where i≠i′, and calculate the maximum task volume and unit task processing delay τ that can be processed in V2V2I mode i,k , if s i,k >0 and Let model = V2V2I, Jump to step 107, otherwise, jump to step 107;

[0013] 107. Execute task uninstallation according to the current uninstallation mode model,

[0014] 108. The k-th cycle task is unloaded, so if and Jump to step 102, otherwise, jump to step 109;

[0015] 109. The steps are completed.

[0016] Furthermore, the kth cycle duration t of task vehicle i in step 102 is i,k The calculation method is shown in formula (1):

[0017]

[0018] In formula (1), ρ and σ are used to adjust v i With t i,k The constant of the relationship between i represents the speed of task vehicle i, v min represents the minimum speed of the vehicle, represents the remaining tolerance delay of the task of task vehicle i.

[0019] Furthermore, in steps 102, 103, and 106, the maximum amount of tasks s that can be processed by the task vehicle i in the local unloading mode, the V2I unloading mode, and the V2V2I unloading mode i,k The calculation method is shown in formula (2):

[0020]

[0021] In formula (2), Indicates rounding down, f i represents the local computing resources of task vehicle i, θ represents the unit task size, represents the remaining task amount of task vehicle i, represents the link duration between mission vehicle i and RSU j, represents the computing resources that RSU j can allocate to task vehicle i, represents the link duration between vehicle i′ and its associated RSU j, represents the data transmission rate between vehicle i and RSU j, and the calculation method is shown in formula (3):

[0022]

[0023] In formula (3), B V2I represents the bandwidth of the V2I link, p i represents the transmission power of mission vehicle i, represents the channel gain between mission vehicle i and RSU j, N0 represents the noise power, represents the path loss between mission vehicle i and RSU j;

[0024] In formula (2), represents the link duration between vehicle i and vehicle i′, and the calculation method is shown in formula (4):

[0025]

[0026] Among them, the calculation methods of t1, t2, t3, and t4 are shown in formula (5) to formula (8) respectively:

[0027]

[0028] In formula (5)-formula (8), a max with a min Represent the maximum and minimum acceleration of the vehicle, R V2V Indicates the maximum communication distance between vehicles, d i,i′ represents the distance between task vehicle i and relay vehicle i′, μ i,i′ represents the position relationship between task vehicle i and relay vehicle i′. The calculation method is shown in formula (9):

[0029]

[0030] In formula (9), x i represents the position of task vehicle i, x i′ represents the position of relay vehicle i′;

[0031] In formula (2), represents the V2V2I link transmission rate, and the calculation method is shown in formula (10):

[0032]

[0033] In formula (10), represents the V2V link transmission rate, and the calculation method is shown in formula (11):

[0034]

[0035] In formula (11), B V2V represents the V2V link bandwidth, represents the channel gain between task vehicle i and relay vehicle i′, represents the path loss between task vehicle i and relay vehicle i′.

[0036] Furthermore, the unit task processing delay τ in the local unloading mode, V2I unloading mode, and V2V2I unloading mode in steps 102, 103, and 106 is i,k The calculation method is shown in formula (12):

[0037]

[0038] Furthermore, the link duration between task vehicle i and RSU j in step 103 is The calculation method is shown in formula (13):

[0039]

[0040] In formula (13), x i represents the position of task vehicle i, x j represents the position of RSU j, a max represents the maximum acceleration of the vehicle, and R represents the coverage radius of the RSU.

[0041] Furthermore, in step 103, RSU j can allocate computing resources to task vehicle i. The calculation method is shown in formula (14):

[0042]

[0043] In formula (14), represents the currently available computing resources of RSU j, represents the total computing resources in RSU j, γ represents a non-zero constant, and n represents the number of mission vehicles within the coverage of RSU j.

[0044] Furthermore, in step 106, the best relay vehicle i′ in the V2V2I unloading mode is found for the task vehicle i, and the maximum task volume s that can be processed in the V2V2I mode is calculated. i,k and unit task processing delay τ i,k , specifically including the following steps:

[0045] 1) Initialize the maximum task volume s that vehicle i can handle in V2V2I mode i,k =0, unit task processing delay τ i,k =∞, candidate relay vehicle set

[0046] 2) Add idle vehicles within one hop from task vehicle i and within the coverage of any RSU j to set I′;

[0047] 3) If Take any vehicle i′ from I′ and calculate the duration of the link between task vehicle i and vehicle i′. The link duration between vehicle i′ and its associated RSU j And the computing resources that RSU j can allocate to task vehicle i Calculated in The maximum amount of tasks that the V2V2I link can handle within a certain period of time and unit task processing delay Jump to step 4), otherwise, jump to step 5);

[0048] 4) If and make Let i′ be the relay vehicle of task vehicle i, jump to step 3), otherwise, jump to step 3);

[0049] 5) Output the maximum task volume s that task vehicle i can handle in V2V2I mode i,k and unit task processing delay τ i,k ;

[0050] 6) The step ends.

[0051] The advantages and beneficial effects of the present invention are as follows:

[0052] The present invention discloses a method for unloading tasks of vehicles with non-uniform speed in sparse RSU edge networks. Most of the existing research on the problem of vehicle task unloading in edge networks considers the ideal scenario of vehicles driving on roads fully covered by RSUs, and less research on the possibility that sparse deployment of RSUs or RSU failures may lead to the loss of network functions in some sections of the road, and the high mobility and non-uniform speed characteristics of vehicles may further lead to frequent interruptions of transmission links or task losses, thereby causing task unloading failures or deterioration of service quality. In response to the above problems, the present invention proposes a method for unloading tasks of vehicles with non-uniform speed in sparse RSU edge networks. According to the speed change of the task vehicle and the task delay constraint, the task unloading cycle is dynamically planned, and according to the link duration between the vehicle and the RSU and between the vehicles in different cycles, a hybrid unloading mode combining Local, V2I, and V2V2I is adopted to dynamically adjust the task scheduling strategy and computing resource allocation strategy, optimize the system resource utilization, thereby maximizing the task completion rate and reducing the system unit task unloading delay. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 The present invention provides a preferred embodiment of a flow chart of a method for unloading non-uniform-speed vehicle tasks in a sparse RSU edge network. DETAILED DESCRIPTION

[0054] The following will describe the technical solutions in the embodiments of the present invention in detail in conjunction with the accompanying drawings in the embodiments of the present invention. The described embodiments are only part of the embodiments of the present invention.

[0055] The technical solution of the present invention to solve the above technical problems is:

[0056] The concepts and models involved in the present invention are as follows:

[0057] The present invention assumes that the sparse RSU edge network is composed of RSU and vehicles. RSU is sparsely deployed on one side of the road. The RSU set is represented by J (j∈J). Each RSU is configured with an edge server, which can provide task offloading services for vehicle terminals. The vehicles on the road travel at non-uniform speeds within a certain speed range. The vehicle set is represented by I (i∈I). Each vehicle can obtain the current position, speed and other information in real time through the on-board unit (OBU). The task vehicle can offload the task to the RSU through the V2I or V2V2I mode, or calculate the task locally. Taking into account the uncertainty of the driving state of non-uniform vehicles, a dynamic periodic scheduling method is adopted for task offloading. The unloading period set of vehicle i is represented by K i (k∈K i ), since the result size is much smaller than the input data size, the result return delay is ignored.

[0058] The task request of vehicle i is expressed as Among them, s i represents the amount of task data, c i represents the computational complexity of the task, Indicates the maximum tolerable delay of a task. i The unit task is used as the smallest unit to arbitrarily split into subtasks with the same computational complexity and calculate them in cycles. They represent the task unloading amount and unit task processing delay of vehicle i in the kth cycle respectively. Let I′(i′∈I′) represent the set of relay vehicles of task vehicle i.

[0059] The technical solution of the present invention is described as follows:

[0060] 1. The kth cycle duration t of mission vehicle i i,k The calculation method is shown in formula (1):

[0061]

[0062] In formula (1), ρ and σ are constants used to adjust v i With t i,k The relationship between i represents the speed of task vehicle i, v min represents the minimum speed of the vehicle, represents the remaining tolerance delay of the task of task vehicle i.

[0063] 2. The maximum amount of tasks that can be handled by task vehicle i in local unloading mode, V2I unloading mode, and V2V2I unloading mode i,k The calculation method is shown in formula (2):

[0064]

[0065] In formula (2), Indicates rounding down, f i represents the local computing resources of task vehicle i, θ represents the unit task size, represents the remaining task amount of task vehicle i, represents the link duration between mission vehicle i and RSU j, represents the computing resources that RSU j can allocate to task vehicle i, represents the link duration between vehicle i′ and its associated RSU j, represents the data transmission rate between vehicle i and RSU j, and the calculation method is shown in formula (3):

[0066]

[0067] In formula (3), B V2I represents the bandwidth of the V2I link, p i represents the transmission power of mission vehicle i, represents the channel gain between mission vehicle i and RSU j, N0 represents the noise power, represents the path loss between mission vehicle i and RSU j;

[0068] In formula (2), represents the link duration between vehicle i and vehicle i′, and the calculation method is shown in formula (4):

[0069]

[0070] Among them, the calculation methods of t1, t2, t3, and t4 are shown in formula (5) to formula (8) respectively:

[0071]

[0072] In formula (5)-formula (8), a max with a min Represent the maximum and minimum acceleration of the vehicle, R V2V Indicates the maximum communication distance between vehicles, d i,i′ represents the distance between task vehicle i and relay vehicle i′, μ i,i′ represents the position relationship between task vehicle i and relay vehicle i′. The calculation method is shown in formula (9):

[0073]

[0074] In formula (9), x i represents the position of task vehicle i, x i′represents the position of relay vehicle i′;

[0075] In formula (2), represents the V2V2I link transmission rate, and the calculation method is shown in formula (10):

[0076]

[0077] In formula (10), represents the V2V link transmission rate, and the calculation method is shown in formula (11):

[0078]

[0079] In formula (11), B V2V represents the V2V link bandwidth, represents the channel gain between task vehicle i and relay vehicle i′, represents the path loss between task vehicle i and relay vehicle i′;

[0080] 3. Unit task processing delay τ in local offloading mode, V2I offloading mode, and V2V2I offloading mode i,k The calculation method is shown in formula (12):

[0081]

[0082] 4. Link duration between mission vehicle i and RSU j The calculation method is shown in formula (13):

[0083]

[0084] In formula (13), x i represents the position of task vehicle i, x j represents the position of RSU j, a max represents the maximum acceleration of the vehicle, and R represents the coverage radius of the RSU;

[0085] 5. Computing resources that RSU j can allocate to task vehicle i The calculation method is shown in formula (14):

[0086]

[0087] In formula (14), represents the currently available computing resources of RSU j, represents the total computing resources of RSU j, γ represents a non-zero constant, and n represents the number of mission vehicles within the coverage area of ​​RSU j; 6. Sub-algorithm 1: Find the best relay vehicle i′ in the V2V2I unloading mode for mission vehicle i

[0088] Step 1: Initialize the maximum task volume s that vehicle i can handle in V2V2I offloading mode i,k =0, unit task processing delay τ i,k =∞, candidate relay vehicle set

[0089] Step 2: Add idle vehicles within one hop from the task vehicle i and within the coverage of any RSU j to the set I′;

[0090] Step 3: If Take any vehicle i′ from I′ and calculate the duration of the link between task vehicle i and vehicle i′. The link duration between vehicle i′ and its associated RSU j And the computing resources that RSU j can allocate to task vehicle i Calculated in The maximum amount of tasks that the V2V2I link can handle within a certain period of time and unit task processing delay Jump to step 4), otherwise, jump to step 5);

[0091] Step 4: If and make Let i′ be the relay vehicle of task vehicle i, jump to step 3), otherwise, jump to step 3);

[0092] Step 5: Output the maximum task volume s that vehicle i can handle in the V2V2I offloading mode i,k and unit task processing delay τ i,k ;

[0093] Step 6: End of step.

[0094] A method for offloading non-uniform speed vehicle tasks in a sparse RSU edge network, wherein the specific implementation method comprises the following steps:

[0095] Step 1: According to the unloading request of task vehicle i, obtain the task data volume s i , the computational complexity of the task is c i , task delay threshold Initialize the remaining task amount of task vehicle i Remaining Tolerable Delay Unloading cycle number k = 0;

[0096] Step 2: Let k = k + 1, according to the current speed v of task vehicle i i , calculate the kth unloading cycle duration t of task vehicle i i,k, the maximum number of tasks that can be processed in the local offload mode s i,k , and the unit task processing delay τ in Local mode i,k , let the unloading mode model of task vehicle i in the kth cycle be Local, and the unloading task volume of task vehicle i Unit task processing delay

[0097] Step 3: If the mission vehicle i is within the coverage of any roadside unit RSU j, according to the link duration between the mission vehicle i and RSU j and the computing resources that RSU j can allocate to task vehicle i calculate The maximum amount of tasks that RSU j can handle in V2I offloading mode in the time period of task vehicle i i,k , jump to step 104, otherwise, jump to step 106;

[0098] Step 4: If s i,k > 0, calculate the unit task processing delay τ of task vehicle i in V2I offloading mode i,k , jump to step 105, otherwise, jump to step 106;

[0099] Step 5: If Let model = V2I, Jump to step 107, otherwise, jump to step 107;

[0100] Step 6: Call sub-algorithm 1 to find the best relay vehicle i′ in the V2V2I unloading mode for task vehicle i, where i≠i′, and calculate the maximum task volume s that can be processed in the V2V2I unloading mode i,k and unit task processing delay τ i,k , if s i,k >0, and Let model = V2V2I, Jump to step 107, otherwise, jump to step 107;

[0101] Step 7: Execute task uninstallation according to the current uninstallation mode model,

[0102] Step 8: The k-th cycle task is unloaded, let if and Jump to step 102, otherwise, jump to step 109;

[0103] Step 9: End of the step.

[0104] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions.

[0105] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0106] The above embodiments should be understood to be only used to illustrate the present invention and not to limit the protection scope of the present invention. After reading the contents of the present invention, technicians can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A method for offloading non-uniform-speed vehicle tasks in a sparse RSU edge network, characterized in that: The following steps are involved:

101. According to the unloading request of task vehicle i, obtain the task data volume s i , the computational complexity of the task is c i , task delay threshold Initialize the remaining task amount of task vehicle i Remaining Tolerable Delay Unloading cycle number k = 0; 102. Let k = k + 1, according to the current speed v of task vehicle i i , calculate the kth unloading cycle duration t of task vehicle i i,k , the maximum number of tasks that can be processed in the local offload mode s i,k , and the unit task processing delay τ in Local mode i,k , let the unloading mode model of task vehicle i in the kth cycle be Local, and the unloading task volume of task vehicle i Unit task processing delay 103. If the mission vehicle i is within the coverage of any roadside unit RSUj, according to the link duration between the mission vehicle i and RSUj and the computing resources that RSUj can allocate to task vehicle i calculate The maximum amount of tasks that RSUj can handle in V2I offloading mode in the time period s i,k , jump to step 104, otherwise, jump to step 106; 104. If i,k > 0, calculate the unit task processing delay τ of task vehicle i in V2I offloading mode i,k , jump to step 105, otherwise, jump to step 106; 105. If Let model = V2I, Jump to step 107, otherwise, jump to step 107; 106. Find the best relay vehicle i′ in V2V2I unloading mode for task vehicle i, where i≠i′, and calculate the maximum task volume s that can be processed in V2V2I unloading mode i,k and unit task processing delay τ i,k , if s i,k >0 and Let model = V2V2I, Jump to step 107, otherwise, jump to step 107; 107. Execute task uninstallation according to the current uninstallation mode model, 108. The k-th cycle task is unloaded, so if and Jump to step 102, otherwise, jump to step 109; 109. The steps are completed.

2. According to claim 1, a method for unloading tasks of non-uniform vehicles in a sparse RSU edge network is characterized in that: The kth cycle duration t of the task vehicle i in step 102 i,k The calculation method is shown in formula (1): In formula (1), ρ and σ are used to adjust v i With t i,k The constant of the relationship between i represents the speed of task vehicle i, v min represents the minimum speed of the vehicle, represents the remaining tolerance delay of the task of task vehicle i.

3. According to claim 2, a method for unloading non-uniform speed vehicle tasks in a sparse RSU edge network is characterized in that: The maximum amount of tasks s that can be handled by the task vehicle i in the local unloading mode, the V2I unloading mode, and the V2V2I unloading mode in steps 102, 103, and 106 i,k The calculation method is shown in formula (2): In formula (2), Indicates rounding down, f i represents the local computing resources of task vehicle i, θ represents the unit task size, represents the remaining task amount of task vehicle i, represents the link duration between mission vehicle i and RSUj, represents the computing resources that RSUj can allocate to task vehicle i, represents the link duration between vehicle i′ and its associated RSUj, represents the data transmission rate between vehicle i and RSUj, and the calculation method is shown in formula (3): In formula (3), B V2I represents the bandwidth of the V2I link, p i represents the transmission power of mission vehicle i, represents the channel gain between mission vehicle i and RSUj, N0 represents the noise power, represents the path loss between mission vehicle i and RSUj; In formula (2), represents the link duration between vehicle i and vehicle i′, and the calculation method is shown in formula (4): Among them, the calculation methods of t1, t2, t3, and t4 are shown in formula (5) to formula (8) respectively: In formula (5)-formula (8), a max with a min Represent the maximum and minimum acceleration of the vehicle, R V2V Indicates the maximum communication distance between vehicles, d i,i′ represents the distance between task vehicle i and relay vehicle i′, μ i,i′ represents the position relationship between task vehicle i and relay vehicle i′. The calculation method is shown in formula (9): In formula (9), x i represents the position of task vehicle i, x i′ represents the position of relay vehicle i′; In formula (2), represents the V2V2I link transmission rate, and the calculation method is shown in formula (10): In formula (10), represents the V2V link transmission rate, and the calculation method is shown in formula (11): In formula (11), B V2V represents the V2V link bandwidth, represents the channel gain between task vehicle i and relay vehicle i′, represents the path loss between task vehicle i and relay vehicle i′.

4. According to claim 1, a method for unloading non-uniform speed vehicle tasks in a sparse RSU edge network is characterized in that: The unit task processing delay τ in the local offloading mode, V2I offloading mode, and V2V2I offloading mode in steps 102, 103, and 106 i,k The calculation method is shown in formula (12):

5. According to claim 1, a method for unloading tasks of non-uniform vehicles in a sparse RSU edge network is characterized in that: The link duration between task vehicle i and RSUj in step 103 The calculation method is shown in formula (13): In formula (13), x i represents the position of task vehicle i, x j represents the position of RSUj, a max represents the maximum acceleration of the vehicle, and R represents the coverage radius of the RSU.

6. A method for unloading non-uniform-speed vehicle tasks in a sparse RSU edge network according to claim 1, characterized in that: In step 103, RSUj can be the computing resource allocated to task vehicle i The calculation method is shown in formula (14): In formula (14), Indicates the currently available computing resources of RSUj, represents the total computing resources in RSUj, γ represents a non-zero constant, and n represents the number of mission vehicles within the coverage area of ​​RSUj.

7. A method for unloading non-uniform speed vehicle tasks in a sparse RSU edge network according to claim 1, characterized in that: In step 106, the best relay vehicle i′ in the V2V2I unloading mode is found for the task vehicle i, and the maximum task volume s that can be processed in the V2V2I unloading mode is calculated. i,k and unit task processing delay τ i,k , specifically including the following steps: 1) Initialization task: The maximum amount of tasks s that vehicle i can handle in V2V2I offloading mode i,k =0, unit task processing delay τ i,k =∞, candidate relay vehicle set 2) Add idle vehicles within one hop from task vehicle i and within the coverage of any RSUj to set I′; 3) If Take any vehicle i′ from I′ and calculate the duration of the link between task vehicle i and vehicle i′. Duration of the link between vehicle i′ and its associated RSUj And the computing resources that RSUj can allocate to task vehicle i Calculated in The maximum amount of tasks that the V2V2I link can handle within a certain period of time and unit task processing delay Jump to step 4), otherwise, jump to step 5); 4) If and make Let i′ be the relay vehicle of task vehicle i, jump to step 3), otherwise, jump to step 3); 5) Output the maximum task volume s that vehicle i can handle in V2V2I unloading mode i,k and unit task processing delay τ i,k ; 6) The step ends.

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