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• task scheduling assessments ls-type:: annotation hl-page:: 1 hl-color:: green id:: 647f5e8e-3620-4571-b9c1-f09220b15450
• task scheduling technique ls-type:: annotation hl-page:: 1 hl-color:: green id:: 647f5e9f-2447-4500-bdcd-15b963b2979a
• system can be simulated, and its underlying technical complexity reduced by increasing the abstraction level from which these systems are designed ls-type:: annotation hl-page:: 1 hl-color:: green id:: 647f5f7e-46e8-4897-867b-d3796ae03a83
• Domain-Specific Language based on SimulateIoT is proposed for the design, code generation and simulation of IoT systems for the assessment of task-scheduling proposals ls-type:: annotation hl-page:: 1 hl-color:: purple id:: 647f5f91-f7db-4897-8e7b-28ca17cab4aa
• this computing layer is able to provide bet-4 ter QoS to specific IoT applications and users ls-type:: annotation hl-page:: 2 hl-color:: green id:: 647f6380-e364-4ff9-9931-7f9209dcecbb
• delay-sensitive applications ls-type:: annotation hl-page:: 2 hl-color:: purple id:: 647f6386-d7a2-48dc-84d6-b8dee26c420d
• Cloud-to-Thing continuum17 paradigm emerges (Bittencourt et al. 2018). ls-type:: annotation hl-page:: 2 hl-color:: blue id:: 647f639f-d3a0-4976-aa2b-1ad53459a2e1
• services are decomposed into a set26 of tasks which have to be processed by the computing27 nodes of this federation ls-type:: annotation hl-page:: 2 hl-color:: green id:: 647f6468-b055-4af8-b64c-6701e058d6eb
• avoiding the aforementioned costs in device49 acquisition, configuration, etc. ls-type:: annotation hl-page:: 2 hl-color:: purple id:: 647f64a0-95a6-4a45-9d57-648e15abd462
• ncreasing the abstrac- 56 tion level from which the IoT systems are designed helps 57 to tackle the underlying technological complexity ls-type:: annotation hl-page:: 2 hl-color:: purple id:: 647f64b7-a576-4fcd-93d3-6531a0a77dc1
• SimulateIoT ls-type:: annotation hl-page:: 2 hl-color:: blue id:: 647f64bd-99f0-4158-a681-ad89a16ef3df
• SimulateIoT is 70 not able to simulate a suitably IoT infrastructure to test 71 task scheduling proposals ls-type:: annotation hl-page:: 2 hl-color:: yellow id:: 647f64d4-f72c-40d8-bcb1-eb48fe898756 hl-stamp:: 1686070504651
• simulator proposed ls-type:: annotation hl-page:: 2 hl-color:: red id:: 647f64f9-eaf0-43b0-acff-2a0cf2c7c9fc
• required infrastructure ls-type:: annotation hl-page:: 2 hl-color:: green id:: 648034ed-aab7-4368-9e59-4f331b9e80f7
• ask 79 scheduling ls-type:: annotation hl-page:: 2 hl-color:: green id:: 648034f2-12b5-49ac-81d6-f73b39042e8e
• deploy ls-type:: annotation hl-page:: 2 hl-color:: green id:: 648034f6-143f-44f6-b222-39970cab79e4
• test ls-type:: annotation hl-page:: 2 hl-color:: green id:: 648034f8-447c-4a0d-965f-af46f41329a7
• compare ls-type:: annotation hl-page:: 2 hl-color:: green id:: 648034fa-7477-46e8-b3bd-759a1420f88e
• analyse ls-type:: annotation hl-page:: 2 hl-color:: green id:: 648034fc-c2ce-46a2-b554-717cd292a457
• task scheduling proposals ls-type:: annotation hl-page:: 2 hl-color:: purple id:: 64803500-26b6-4415-89ee-f5ea449e3e8c
• The main work contributions are the following: ls-type:: annotation hl-page:: 2 hl-color:: yellow id:: 6480352b-4a9e-4a09-9e56-952713e6db98 hl-stamp:: 1686123861006
• IoT simulators ls-type:: annotation hl-page:: 3 hl-color:: green id:: 64803a1a-ce8e-4a61-9317-e1cab016d14e
• IoT systems with task scheduling features ls-type:: annotation hl-page:: 3 hl-color:: green id:: 64803a25-9a5d-486b-835e-d4c8537ea000
• mathematical model, which could negatively impact52 the trustworthiness of the simulato ls-type:: annotation hl-page:: 3 hl-color:: yellow id:: 64803a8f-03a6-4f91-a4a9-c1499ca459e6
• Besides, note that this sim- 69 ulator is based on a mathematical model, which could 70 negatively impact the trustworthiness of the simulator. ls-type:: annotation hl-page:: 3 hl-color:: yellow id:: 64803ad6-c439-4a34-b326-7d06133d7642
• which could negatively impact37 the trustworthiness of the simulator ls-type:: annotation hl-page:: 3 hl-color:: yellow id:: 64803adc-f075-4494-b954-4a39e1ff894a
• WorkflowSim ls-type:: annotation hl-page:: 3 hl-color:: green id:: 64803b22-c6bd-4603-aebb-4bec15980286
• WorkflowSim ls-type:: annotation hl-page:: 3 hl-color:: green id:: 64803b25-aa64-4899-8d67-fa091eaa398c
• 1. The proposed simulator ls-type:: annotation hl-page:: 3 hl-color:: green id:: 64803b6c-2fa4-47ec-9d8d-a0ed587b9f53
• The rest of the simula- 95 tors described above base their results on mathematical 96 models ls-type:: annotation hl-page:: 3 hl-color:: yellow id:: 64803c6b-b153-4456-b7df-b38219206c5b
• a simulator ls-type:: annotation hl-page:: 3 hl-color:: red id:: 64803ca7-c2f8-4bea-8280-2576c99242ea
• current simulation needs ls-type:: annotation hl-page:: 3 hl-color:: yellow id:: 64803cbd-ce52-49ba-aaa7-a19990fdb8dc
• the aim of this section is also to outline5 the new features added as part of this extension ls-type:: annotation hl-page:: 4 hl-color:: green id:: 64803cf1-82c0-442e-9250-a7242f22bda5
• it is required to extend: 1)33 The Metamodel or Abstract Syntax (M2) ls-type:: annotation hl-page:: 4 hl-color:: green id:: 64803d32-deb0-46e8-83ec-32c052a928bf
• 2. The Graphi-34 cal Concrete Syntax or the element that allows to graph-35 ically design models (M1) from the Metamodel (M2) and ls-type:: annotation hl-page:: 4 hl-color:: green id:: 64803d3a-1c81-45cc-8556-66909e2e0b80
• 3. Model-to-Text Transformations (M2T), the element37 that carries out the code generation (M0) from models38(M1). ls-type:: annotation hl-page:: 4 hl-color:: green id:: 64803d3e-7801-4590-ad9f-3e71182500b9
• fed-46 eration ls-type:: annotation hl-page:: 4 hl-color:: green id:: 64803d64-7cb4-4c8f-8c0d-0a1bf38b599e
• exten- 61 sions in this communication (coloured in red) ls-type:: annotation hl-page:: 4 hl-color:: green id:: 64803da2-996f-4d95-98bd-62354ea415b2
• previous version of the 63 simulator (coloured in blue) ls-type:: annotation hl-page:: 4 hl-color:: green id:: 64803da6-179f-4cc8-a81e-6ff1b6df69c9
• [:span] ls-type:: annotation hl-page:: 5 hl-color:: yellow id:: 64803ddb-3a89-4f96-9e8e-5d6a6c7f33c3 hl-type:: area hl-stamp:: 1686126040756
• Task Processor ls-type:: annotation hl-page:: 5 hl-color:: yellow id:: 64804108-1977-4b05-be71-27c9cafeb120
• Furthermore, note that the Networking Node can also2 share the status of each link (current delay and avail-3 able bandwidth) with the Task Scheduler. In this way,4 the Task Scheduler can use this data for scheduling5 purposes. ls-type:: annotation hl-page:: 6 hl-color:: green id:: 6480418a-b4e4-46e8-8268-c9882a9d0056
• the resulting simulator allows users to simu-10 late suitable IoT systems where users can perform sev-11 eral tests and analyse their task scheduling proposals12 without the need for high investment in the acquisition13 of devices, their configuration, deployment, etc. ls-type:: annotation hl-page:: 6 hl-color:: green id:: 648041b9-7042-446a-a0cf-3bb0af70be3d
• Before extending SimulateIoT towards the Cloud-17 to-Things continuum and towards task scheduling,18 it is first necessary to identify the main concepts19 of these systems ls-type:: annotation hl-page:: 6 hl-color:: green id:: 6480473e-61c8-497c-8078-84da74d6c222
• In this regard, this section addresses these concepts24 in detail ls-type:: annotation hl-page:: 6 hl-color:: yellow id:: 6480474c-5f9b-4426-9661-7b3576c71f90
• dependency ls-type:: annotation hl-page:: 6 hl-color:: green id:: 64804815-e8d3-47b4-95b8-ba8d9233548e
• size ls-type:: annotation hl-page:: 6 hl-color:: yellow id:: 64804838-ed30-4849-a098-7a51df981bfb
• offloadSize which represent the size 58(bytes) of the data that have to be transmitted from the 59 source Task to the target Task ls-type:: annotation hl-page:: 6 hl-color:: green id:: 64804858-3a03-40a1-bd35-95bdc8ffd1c5
• Note that the offloadSize attribute 62 represents the offload size (bytes) of the processing 63 results of a Task. ls-type:: annotation hl-page:: 6 hl-color:: yellow id:: 64804875-2d41-46c6-bea4-6f321bc3002d
• Task Apps, which 71 can be deployed in the different nodes of the fog and 72 cloud layers. ls-type:: annotation hl-page:: 6 hl-color:: green id:: 64804a87-ed97-4eca-aa27-69a78eec0200
• limited to 80 consuming these resources and services. ls-type:: annotation hl-page:: 6 hl-color:: green id:: 64804aab-2053-4ae3-b3fd-5f8960913c31
• can help these layers in the provision of these6 services and resources to the rest of the system ls-type:: annotation hl-page:: 7 hl-color:: green id:: 64804ac3-2d4d-42cf-a261-2420a8bca499
• they are able to provide better latency,11 request-response time, etc. This new paradigm is called12 Cloud-Edge computing ls-type:: annotation hl-page:: 7 hl-color:: green id:: 64804ad6-f6c3-4ca7-8c9a-25e2f8c90710
• ask scheduling is often applied to environments that28 have a Cloud-to-Things continuum infrastructure ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480b864-4d18-46c1-8f45-35a6adf121d5
• SimulateIoT is a hybrid simula-41 tor/emulator of IoT systems ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480b88d-85ec-43e8-9c1f-74d7d2fdf7e2
• configuring the network where49 simulations will be deployed could be a tedious, error-50 prone and costly task. ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480b8ba-0e82-47ce-a1e8-7e0292a7978c
• this component 73 is the most relevant, as it is where the simulator will 74 integrate users’ task scheduling proposals, ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480b8ef-d3ca-4804-b12d-b8092acb22c4
• offloaded Tasks ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480e0f5-d29f-49fa-8dfb-ffc0cba39d58
• data ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480e0fd-7915-4518-a727-d82efae991fd
• between each node ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480e102-10e5-4e09-97ca-6b81b2b4e057
• ardware usage ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480e10c-0a3b-45d6-b129-5f9e890a09e1
• return of 95 the scheduled Tasks ls-type:: annotation hl-page:: 7 hl-color:: green id:: 6480e116-131e-4246-b0f3-db94d7dd0821
• 1. Metamodel or Abstract13 Syntax ls-type:: annotation hl-page:: 8 hl-color:: green id:: 6480e2ae-4bb9-4782-bfa6-16e315c38b23
• 2. Graphical Concrete Syntax ls-type:: annotation hl-page:: 8 hl-color:: green id:: 6480e2b1-3dad-4090-9fff-815ea925dc80
• 3. Model-to-14 Text Transformations (M2T) ls-type:: annotation hl-page:: 8 hl-color:: yellow id:: 6480e2b5-58da-4cf5-a34b-95a0e61bb1e8 hl-stamp:: 1686168253876
• model partially real-19 ity ls-type:: annotation hl-page:: 8 hl-color:: red id:: 6480e2ec-6f8b-4dee-87de-456ccdb9869e
• task scheduling32 capabilities and with a Cloud-to-Thing continuum infras-33 tructure ls-type:: annotation hl-page:: 8 hl-color:: purple id:: 6480e320-6237-4872-a3bc-5a8a1da828fe
• with enough expressiveness to define IoT systems with a36 Cloud-to-Thing continuum infrastructure and with task37 scheduling capabilities ls-type:: annotation hl-page:: 8 hl-color:: purple id:: 6482f85b-4b1d-4115-967a-8dd0c999f404
• section is divided into46 the domain-specific concepts identified in Section ls-type:: annotation hl-page:: 8 hl-color:: red id:: 6482f883-5392-4735-be82-71e7b7d5338f
• (classes and relations shown in Figure 4). In this re- 52 gard, note that this section does not aim to describe how 53 these components work internally, which is addressed 54 in Section 6, where M2T are presented. 55 Finally, note that in this section, to better describe 56 the elements of the metamodel, the numerical labels 57 shown in Figure 4 are used below as references in the 58 text. These references are used by means of the expres- 59 sion [class name] x , where x is the label associated 60 with the [class] in Figure 4. ls-type:: annotation hl-page:: 8 hl-color:: yellow id:: 6482f8e7-e5b0-48de-a41e-8e18bc36c213
• Task 74 will be generated ls-type:: annotation hl-page:: 8 hl-color:: yellow id:: 64830213-e06f-4ee8-8fd3-b414a1fb2ea5
• offload_size, to allow users to3 model the offload size of each Workflow_edge (data4 transmission between Workflow_nodes). ls-type:: annotation hl-page:: 10 hl-color:: yellow id:: 648334c7-8ec6-4e62-be49-0fab38b6de95
• Task34 Apps that will be deployed on each fog or cloud node35 during the simulation ls-type:: annotation hl-page:: 10 hl-color:: green id:: 6483353a-88a7-40e3-a07c-0c48fe181c1e
• Networking 69 Node code of each modelled node ls-type:: annotation hl-page:: 10 hl-color:: green id:: 6483381b-dff4-4a77-94d8-4c9e380a8992
• Thus, the following lists 74 and describes the classes ls-type:: annotation hl-page:: 10 hl-color:: green id:: 6483383f-3bf0-4907-b16b-5cd306f481b5
• . Thus, the following lists 74 and describes the classes and relationship ls-type:: annotation hl-page:: 10 hl-color:: yellow id:: 64833845-6df3-4c5f-a0dd-2d406d504b8b
• node federations ls-type:: annotation hl-page:: 10 hl-color:: green id:: 64833858-395f-4935-9a4a-0783f6afe4d7
• Environment ls-type:: annotation hl-page:: 10 hl-color:: green id:: 648338ad-586b-4013-83aa-22bff8e3bb58
• Node ls-type:: annotation hl-page:: 10 hl-color:: green id:: 648338b5-e0e0-4f37-8c06-f5f1cb4a3c50
• Links that connect each node belonging 98 to the same federation ls-type:: annotation hl-page:: 10 hl-color:: green id:: 648338f3-619c-459f-9842-62616fb4568e
• SimulateIoT40 does not support the deployment of task scheduling41 approaches in its simulations as it does not have the42 required components for this purpose, such as compo-43 nents that generate tasks, process them, etc. ls-type:: annotation hl-page:: 4 hl-color:: purple id:: 64888589-7318-48ab-8159-167032dc703b
• [:span] ls-type:: annotation hl-page:: 5 hl-color:: green id:: 648885ec-87a7-42e1-b844-d2f55727005a hl-type:: area hl-stamp:: 1686668778106
• On the one hand, the scheduling is carried8 out in the fog or cloud layer by the Task Scheduler ls-type:: annotation hl-page:: 5 hl-color:: green id:: 64888896-726e-4938-bcb5-8b6a26af438f
• component that belongs to the Entities that support10 task scheduling ( ls-type:: annotation hl-page:: 5 hl-color:: green id:: 6488889c-a9e3-43d1-906d-6bd54d9780a8
• The CPU and RAM concepts have been included in17 SimulateIoT regarding the processing of Tasks ls-type:: annotation hl-page:: 5 hl-color:: green id:: 648888d5-c7d1-4424-b3cb-e0148ce982cb
• that will be used when processing Tasks ls-type:: annotation hl-page:: 5 hl-color:: green id:: 648888df-89b2-414c-a15e-0b8339814f00
• acting as a single entity rather than 28 isolated nodes ls-type:: annotation hl-page:: 5 hl-color:: green id:: 64888bc1-6144-4269-8b7a-0bab4f42b556
• Networking ls-type:: annotation hl-page:: 5 hl-color:: yellow id:: 64888bd3-99f2-4bbe-8fa6-edb7a85a7299 hl-stamp:: 1686670318485
• Node ls-type:: annotation hl-page:: 5 hl-color:: green id:: 64888bd5-29ca-4e20-9198-2c42a931e39f
• Tasks by means of38 workflows that the nodes designed for these purposes39 will generate, offload, schedule or process. ls-type:: annotation hl-page:: 6 hl-color:: purple id:: 64888dd3-28ed-443b-85a3-455becba92ff hl-stamp:: 1686670806117
• Task and workflow will be used as41 synonyms. ls-type:: annotation hl-page:: 6 hl-color:: purple id:: 64888de2-ba77-4fd7-b15f-0ae75676edc7
• This workflow represents a Tasks de-44 composed in four Tasks, Task A, Task B, Task C and45 Task D. ls-type:: annotation hl-page:: 6 hl-color:: yellow id:: 64888f67-daaf-47ec-8ede-a20e8579dd8f hl-stamp:: 1686671212219
• Extensions of Model-to-text transfor-40 mations ls-type:: annotation hl-page:: 12 hl-color:: yellow id:: 648894cf-c51b-47d7-9cc7-3a5859c12ef8
• health-38 care, traffic safety and control (IoV) or industry (IIoT) ls-type:: annotation hl-page:: 23 hl-color:: green id:: 64889551-47dd-425c-82ed-171c2ef044c6 hl-stamp:: 1686672724413
• predictive maintenance of electric 64 motors, as well as the suitability of the application of 65 IoT and task scheduling to achieve this purpose, it has 66 been considered appealing to show the application of 67 the proposed simulator in this context. ls-type:: annotation hl-page:: 23 hl-color:: yellow id:: 648895a8-2048-405d-ab8a-9c8a5afbd768 hl-stamp:: 1686672810203
• predicting the failure of 71 electric motors ls-type:: annotation hl-page:: 23 hl-color:: yellow id:: 648895b4-b153-476b-9506-928d675b2ac1 hl-stamp:: 1686672825509
• i ls-type:: annotation hl-page:: 23 hl-color:: red id:: 64889622-3847-4351-a92c-d5366aff6c1c hl-stamp:: 1686672932818
• ii) to generate configuration code to deploy all the20 generated services, such as the message brokers21 necessary, including the topic configurations de-22 fined, the gateway configurations, etc. ls-type:: annotation hl-page:: 26 hl-color:: yellow id:: 648896a5-7b5e-4812-bc7e-a58ff156a535 hl-stamp:: 1686673068163
• Simulation analysis ls-type:: annotation hl-page:: 26 hl-color:: yellow id:: 648897a2-020c-4402-ad68-e65073f838ba
• based on51 a mathematical model, which could negatively impact52 the trustworthiness of the simulator. ls-type:: annotation hl-page:: 3 hl-color:: yellow id:: 64889be0-aaf4-4ea3-ba07-f1dfee2378d0