iOS Apps that access the same BLE peripheral: How to distinguish? - bluetooth-lowenergy

I have to following scenario:
My app requests and receives data from an BLE peripheral (a glucometer). It it possible that the user has another app (from another developer) installed, that also communicates with the peripheral. I noticed that my app receives characteristic notifications for requests that where initiated by the other app. This causes my app to receive some data twice.
Is there any way to distinguish between responses to my request and responses that are caused by another app? Or how can I handle it?

While the stack obviously knows which app a certain (read, write) response belongs to (because there may only be one pending request, and it knows who sent the request), there is no logical or sound reason why it should dispatch a notification to a single app (among those who have enabled notifications).
Note that the GATT specification does not define "multiple gatt clients per link", there is only one client, so the peripheral doesn't even know there might be two apps talking to it. Hence when it sends a notification, it doesn't include a "target app" field.
The feature of multiplexing multiple apps to the same GATT connection is something iOS and Android teams etc. came up with.

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HTTP Server-Push: Service to Service, without Browser

I am developing a cloud-based back-end HTTP service that will be exposed for integration with some on-prem systems. Client systems are custom-made by external vendors, they are back-end systems with their own databases. These systems are deployed in companies of our clients, we don't have access to them and don't control them. We are providing vendors our API specifications and they implement client code.
The data format which my service exchanges with clients is based on XML and follows a certain standard. Vendors implement their client systems in different programming languages and new vendors will appear over time. I want as many of clients to be able to work with my service as possible.
Most of my service API is REST-like: it receives HTTP requests, processes them, and sends back HTTP responses.
Additionally, my service accumulates some data state changes and needs to regularly push this data to client systems. Because of the below limitations, this use-case does not seem to fit the traditional client-server HTTP request-response model.
Due to the nature of the business, the client systems cannot afford to have their own HTTP API endpoints open and so my service can't establish an outbound HTTP connection to them for delivering data state notifications. I.e. use of WebHooks is not an option.
At the same time my service stakeholders need recorded acknowledgment that data state notifications were accepted by the client system, therefore fire-and-forget systems like Amazon SNS don't seem to apply.
I was considering few approaches to this problem but I'm not sure if I'm missing some simple options or some technologies that already address the problem. Hence this question.
The question text updated: options moved to my own answer.
Related questions and resources
REST API with active push notifications from server to client
Is ReST over websockets possible?
Can we use Web-Sockets for Communication between Microservices?
What is difference between grpc and websocket? Which one is more suitable for bidirectional streaming connection?
https://www.smashingmagazine.com/2018/02/sse-websockets-data-flow-http2/
I eventually found answers to my question myself and with some help from my team. For people like me who come here with a question "how do I arrange notifications delivery from my service to its clients" here's an overview of available options.
WebHooks
This is when the client opens endpoint iself. The service calls client's endpoints whenever the service has some notification to deliver. This way the client also acts as a service and so the client and the service swap roles during notification delivery.
With WebHooks the client must be able to open the endpoint with a well-known address. This is complicated if the client's software is working behind NAT or firewall or if the client is Browser or a mobile application.
The service needs to be prepared that client's WebHook endpoints may not always be online and may not always be healthy.
Another issue is flow control: special measures should be taken in the service not to overwhelm the client with high volume of connections, requests and/or data.
Polling
In this case the client is still the client and the service is still the service, unlike WebHooks. The service offers an endpoint where the client can continuously request new notifications. The advantage of this option is that it does not change connection direction and request-response direction and so it works well with HTTP-based services.
The caveat is that polling API should have some rich semantics to be reasonably reliable if loss of notifications is not acceptable. Good examples could be Google Pub/Sub pull and Amazon SQS.
Here are few considerations:
Receiving and deleting notification should be separate operations. Otherwise, if the service deletes notification just before giving it to the client and the client fails to process the notification, the notification will be lost forever. When deletion operation is separate from receiving, the client is forced to do deletion explicitly which normally happens after successful processing.
In case the client received the notification and has not yet deleted it, it might be undesirable to let the same notification to be processed by some other actor (perhaps a concurrent process of the same client). Therefore the notification must be hidden from receiving after it was first received.
In case the client failed to delete the notification in reasonable time because of error, network loss or process crash, the service has to make notification visible for receiving again. This is retry mechanism which allows the notification to be ultimately processed.
In case the service has no notifications to deliver, it should block the client's call for some time by not delivering empty response immediately. Otherwise, if the client polls in a loop and response comes immediately, the loop iteration will be short and clients will make excessive requests to the service increasing network, parsing load and requests counts. A nice-to have feature is for the service to unblock and respond to the client as soon as some notification appears for delivery. This is sometimes called "long polling".
HTTP Server-sent Events
With HTTP Server-sent Events the client opens HTTP connection and sends a request to the service, then the service can send multiple events (notifications) instead of a single response. The connection is long-living and the service can send events as soon as they are ready.
The downside is that the communication is one-way, the client has no way to inform the service if it successfully processed the event. Because this feedback is absent, it may be difficult for the service to control the rate of events to prevent overwhelming the client.
WebSockets
WebSockets were created to enable arbitrary two-way communication and so this is viable option for the service to send notifications to the client. The client can also send processing confirmation back to the service.
WebSockets have been around for a while and should be supported by many frameworks and languages. WebSocket connection begins as HTTP 1.1 connection and so WebSockets over HTTPS should be supported by many load balancers and reverse proxies.
WebSockets are often used with browsers and mobile clients and more rarely in service-to-service communication.
gRPC
gRPC is similar to WebSockets in a way that it enables arbitrary two-way communication. The advantage of gRPC is that it is centered around protocol and message format definition files. These files are used for code generation that is essential for client and service developers.
gRPC is used for service-to-service communication plus it is supported for Browser clients with grpc-web.
gRPC is supported on multiple popular programming languages and platforms, yet the support is narrower than for HTTP.
gRPC works on top of HTTP/2 which might cause difficulties with reverse proxies and load balancers around things like TLS termination.
Message queue (PubSub)
Finally, the service and the client can use a message queue as a delivery mechanism for notifications. The service puts notifications on the queue and the client receives them from the queue. A queue can be provided by one of many systems like RabbitMQ, Kafka, Celery, Google PubSub, Amazon SQS, etc. There's a wide choice of queuing systems with different properties and choosing one is a challenge on its own. The queue can also be emulated by using database for example.
It has to be decided between the service and the client who owns the queue, i.e. who pays for it. Either way, the queuing system and the queue should be available whenever the service needs to push notifications to it otherwise notifications will be lost (unless the service buffers them internally, with another queue).
Queues are typically used for service-to-service communication but some technologies also allow Browsers as clients.
It is worth noting that an "implicit" internal queue might be used on the service side in other options listed above. One reason is to prevent loss of notifications when there's no client available to receive them. There are many other good reasons like letting clients handle notifications at their pace, allowing to maximize processing throughput, allowing to handle spiky traffic with fixed capacity.
In this option the queue is used "explicitly" as delivery mechanism, i.e. the service does not put any other mechanism (HTTP, gRPC or WebSocket endpoint) in front of the queue and lets the client receive notifications from the queue directly.
Message passing is popular in organizing microservice communications.
Common considerations
In all options it has to be decided whether the loss of notifications is tolerable for the service, the client and the business. Some simpler technical choices are possible if it is ok to lose notifications due to processing errors, unavailability, etc.
It is valuable to have a monitoring for client processing errors from the service side. This way service owners know which clients are more broken without having to ask them.
If the queue is used (implicitly or explicitly) it is valuable to monitor the length of the queue and the age of the oldest notifications. It lets service owners judge how stale data may be in the client.
In case the delivery of notification is organized in a way that notification gets deleted only after a successful processing by the client, the same notification could be stuck in infinite receive loop when the client fails to process it. Such notification is sometimes called "poison message". Poison messages should be removed by the service or the queuing system to prevent clients being stuck in infinite loop. A common practice is to move poison messages to a special place, sometimes called "dead letter queue", for the later human intervention.
One alternative to WebSockets for the problem of server→client notifications with acks from the client seems to be gRPC.
It supports bidirectional communication between server and client in bidirectional streaming mode.
It works on top of HTTP 2.0. In our case functioning over HTTP ports is essential.
There are client and server generators for multiple popular languages and platforms. A nice thing is that I can share protocol definition file with vendors and can be sure my service and their clients will talk the same language.
Drawbacks:
Not as many languages and platforms are supported compared to HTTP. Alternative C from the question will be more accessible if based on HTTP 1.1. WebSockets have also been around longer and I would expect broader adoption than gRPC.
Not all gRPC implementations seem to currently support XML format for data according to FAQ. In order to transport XML my service and its clients will have to transfer XML message as byte arrays inside of gRPC protobuf message.
With gRPC, TLS termination cannot be done on general-purpose HTTP 1.1 load balancer. An application-layer HTTP/2-aware reverse proxy (load balancer) such as Traefik is required.
There are approaches like this and this to allow HTTP 1.1 compatible protocols but they have their own restrictions like limited amount of available clients or necessary client customizations.

Bluetooth LE Characteristic Write Response

I have an embedded device running BT5 with GATT server setup. On the server I have setup a service with various characteristics to allow a client (PC or Mobile Device) to adjust various parameters of the device by writing to the characteristics.
I would like, for the device to send a response back from the application level for each write. It's not clear to me what the recommended way would be.
I thought about having the client read or subscribe to a general status characteristic, but I want to make sure I am not missing an easier way to do this. I looked at the BT write with response command, but it seems the acknowledgement for that may happen lower than the application.
You should be able to use the Write Response as "application level response". I have not seen any Bluetooth stack where this response is sent at a lower level before the application has processed the request. The reason is probably because the application can even send an Application Error code instead of a Write Response, so it would be stupid to move the Write Response handling to a lower level. Even in Android (if you set up a GATT server) you send the Write Response from the application.
The situation is different with Indications, though, where the Bluetooth stack sometimes sends the Confirmation at a lower level than the application, before it even informs the application that an Indication has arrived, which I find a bit strange and makes Indications kind of pointless compared to Notifications.
I solved this using a Notification characteristic. The client first subscribes to notification events on that CCD, and then every command sent to the host/device is acknowledged by the host firing the notification. To better synchronize command-and-response, you could add an incremental command-id with every command, and have the command-id be part of the notification data that is sent back to the client.
However I implemented this because I needed a response after the device has processed the command, with the results sent back to the client. If all you want to know is whether or not the host has received the command, a Write-With-Response CCD is the way to go.
I looked at the BT write with response command, but it seems the acknowledgement for that may happen lower than the application.
Indeed, the Write-With-Response-Handler is almost always implemented on the BLE stack, not on application level. However I don't see why this would be a problem; you should get error reports by your BLE stack in some form when a Write-with-Response fails. If it's a blocking call it might even return a success-value.

Converting HTTP requests to MQTT and back again for smart home integration

We have an already running MQTT setup for communication between smart home devices and remote server, for remotely controlling the devices. Now we want to integrate our devices with Google Home and Alexa. These two use HTTP for communication with third party device clouds.
I have implemented this for Google Home and after receiving the request to device cloud, the request is converted to MQTT. This MQTT request is then sent to smart home device. The device cloud waits for few seconds to receive reply from smart home device. If no reply is received within predefined time, it then sends failure HTTP response to Google Home else it sends the received reply.
Is there a better way to handle this? Since this is a commercial project I want to get this implemented in the correct way.
Any help will be appreciated.
Thanks
We're using AWS IoT and I think it's a good way to handle IoT issues, below are some features of it:
Certification, each device is a thing and attached its own policy, it's security
Shadow, it's device's current state JSON document, The Device Shadow service acts as an intermediary, allowing devices and
applications to retrieve and update a device's shadow
Serverless, we use lambda to build skill and servers, it's flexible
Rule, we use it to intercept MQTT messages so that we can report device's state changing to Google and Alexa. BTW, to Google, Report State implementation has become mandatory for all partners launch & certify.
You can choose either MQTT or HTTP
It’s time-consuming but totally worth it! We've sold 8k+ products, so far so good.
At least Google Home doesn't really require synchronous operation there. Once you get the EXECUTE-intent via their API, you just need to sent that to your device (but it doesn't necessarily has to report its state back).
Once its state changes, you either store it for further QUERY-intents or provide this data to the Google Homegraph server using the "Report State" interface.
I'm developing gBridge.io as a project providing quite similar functionality (but for another target group). There, it is strictly split as described: A HTTP endpoint listener reacts to commands from Google Home and sends it to a cache, where it is eventually sent to the matching MQTT topic. Another worker is listening to MQTT topics from the users and storing there information in the cache, so it can be sent back to Google once required.

Is it possible to broadcast messages in a production PWA using FCM for Web without having a dedicated XMPP server?

This is an architectural question. I haven't implemented FCM yet, but as far as I understand someone needs to deploy an XMPP server in a real world scenario which provisions the inventory of the registered device tokens.
In my use case I'd like to just broadcast short messages about important update information, like "XY presenter's session at 15:00 got cancelled" and I'm not interested in the device tokens. My application is a Progressive Web App, so I would use FCM for Web.
The demos I saw so far showed a client receiving the device token, then that specific device token was picked up from the debug environment and used to send the demo message to the client - thus bypassing the need of a deployed stand-alone XMPP server, but just for demo purposes.
I'd want to avoid the use of an XMPP server, I'm not interested in dealing with the device tokens at all - if possible. Firebase's FCM/GCM server have them anyway. My plan is to pick a single topic name for that channel (the only topic what my app would use actually at this point), and push messages to the devices who listen to that topic. Is this a viable plan? I haven't found any mention of this whatsoever. Firebase knows all the tokens internally and it would make the architecture simpler if I don't have to deploy a server.
I don't know how the decomission/expiration of the device tokens would happen on Firebase's side, but that's another issue I'd have to deal with if I'll run my own XMPP server and provision tokens.
To send messages to a device (so-called downstream messages), you need to specify the server key. As its name implies, this key should only be present on a server or in some other trusted environment. So to send messages to devices you will need to run code in a trusted environment.
The server doesn't have to speak the XMPP protocol however. You can also just use HTTP to call the FCM servers. But a server will be needed, simply because sending downstream messages can only be done from a server.
For a simple example of sending device-to-device messages with this approach, see my blog post Sending notifications between Android devices with Firebase Database and Cloud Messaging. It's about Android, but the same approach of using the Firebase Database as a message queue will work across all platforms.
The tricky bit to map will be (as you already mention) the fact that topics are not available to FCM for the web yet. Last time I tested, you could call a server-side end-point to subscribe to a topic, like described in this answer: GCM: How do you subscribe a device to a topic?.

Web sockets with redis backplane scaleout - multiple redis channels per user or one redis channel for all users

I am connecting clients to our servers using SignalR (same as socketio websockets) so I can send them notifications for activities in the system. It is NOT a chat application. So messages when sent will be for a particular user only.
These clients are connected on multiple web servers and these servers are subscribed to a redis backplane. Like mentioned in this article - http://www.asp.net/signalr/overview/performance/scaleout-in-signalr
My question here is for this kind of notification system, in redis pubsub - should i have multiple channels - one per user in the backplane and the app server listening to each users notification channel. Or have one channel for all these notifications and the app server parses each message and figure out if they have that userid connected and send the message to that user.
Based on the little I know about the details of your application, I think you should create channels/lists in the backplane/Redis on a per-client basis. This would be cheap in Redis, and it gives the server side process handling a specific client only the notifications they are supposed to have.
This should save your application iteration or handling of irrelevant data, which could have implications of performance at scale, and if security is at all a concern (don't know what the domain or application is), then it would be best to never retrieve/receive information unnecessarily that wasn't intended for a particular client.
I will pose a final question and some thoughts which I think support my opinion. If you don't do this on a client-by-client basis, then how will you handle when the user is not present to receive a message? You would either have to throw that message away, or have the application server handle that un-received message for every single client, every time they poll or otherwise receive information from Redis. This could really add up. Although, without knowing the details of the application, I'm not sure if this paragraph is relevant.
At the end of the day, though approaches and opinions may vary depending on the application, I would think about the architecture in terms of the entities and you outlined. You have clients, and they send and receive messages directly to one another. Those messages should be associated with each of the parties involved somehow, and they should be stored in a manner that will be efficient for lookup and which helps define/outline the structure of the application.
Hope my 2c helps!

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