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Totally Reliable Delivery Service Over The Network

I first heard of this game on April 1st, and immediately assumed it was some joke about an app where you could order food delivery through your console. A shame the controls are so wonky, a delivery service game based on Crazy Taxi sounds fun.

Totally Reliable Delivery Service over the network

In this interactive sandbox world, you will play as an extremely busy delivery service personnel. Your major goal every day is to deliver as many packages as possible. The intense challenge lies in properly locating each address and delivering packages as quickly as you can. Bear in mind that most of the tasks here are time-sensitive.

In computer networking, a reliable protocol is a communication protocol that notifies the sender whether or not the delivery of data to intended recipients was successful. Reliability is a synonym for assurance, which is the term used by the ITU and ATM Forum.

Reliable protocols typically incur more overhead than unreliable protocols, and as a result, function more slowly and with less scalability. This often is not an issue for unicast protocols, but it may become a problem for reliable multicast protocols.

Building on the packet switching concepts proposed by Donald Davies, the first communication protocol on the ARPANET was a reliable packet delivery procedure to connect its hosts via the 1822 interface.[1][2] A host computer simply arranged the data in the correct packet format, inserted the address of the destination host computer, and sent the message across the interface to its connected Interface Message Processor (IMP). Once the message was delivered to the destination host, an acknowledgment was delivered to the sending host. If the network could not deliver the message, the IMP would send an error message back to the sending host.

Meanwhile, the developers of CYCLADES and of ALOHAnet demonstrated that it was possible to build an effective computer network without providing reliable packet transmission. This lesson was later embraced by the designers of Ethernet.

If a network does not guarantee packet delivery, then it becomes the host's responsibility to provide reliability by detecting and retransmitting lost packets. Subsequent experience on the ARPANET indicated that the network itself could not reliably detect all packet delivery failures, and this pushed responsibility for error detection onto the sending host in any case. This led to the development of the end-to-end principle, which is one of the Internet's fundamental design principles.

A reliable service is one that notifies the user if delivery fails, while an unreliable one does not notify the user if delivery fails.[citation needed] For example, Internet Protocol (IP) provides an unreliable service. Together, Transmission Control Protocol (TCP) and IP provide a reliable service, whereas User Datagram Protocol (UDP) and IP provide an unreliable one.

A reliable delivery protocol can be built on an unreliable protocol. An extremely common example is the layering of Transmission Control Protocol on the Internet Protocol, a combination known as TCP/IP.

MIL-STD-1553B and STANAG 3910 are well-known examples of such timely and reliable protocols for avionic data buses. MIL-1553 uses a 1 Mbit/s shared media for the transmission of data and the control of these transmissions, and is widely used in federated military avionics systems.[10] It uses a bus controller (BC) to command the connected remote terminals (RTs) to receive or transmit this data. The BC can, therefore, ensure that there will be no congestion, and transfers are always timely. The MIL-1553 protocol also allows for automatic retries that can still ensure timely delivery and increase the reliability above that of the physical layer. STANAG 3910, also known as EFABus in its use on the Eurofighter Typhoon, is, in effect, a version of MIL-1553 augmented with a 20 Mbit/s shared media bus for data transfers, retaining the 1 Mbit/s shared media bus for control purposes.

ATM uses connection-oriented virtual channels (VCs) which have fully deterministic paths through the network, and usage and network parameter control (UPC/NPC), which are implemented within the network, to limit the traffic on each VC separately. This allows the usage of the shared resources (switch buffers) in the network to be calculated from the parameters of the traffic to be carried in advance, i.e. at system design time. That they are implemented by the network means that these calculations remain valid even when other users of the network behave in unexpected ways, i.e. transmit more data than they are expected to. The calculated usages can then be compared with the capacities of these resources to show that, given the constraints on the routes and the bandwidths of these connections, the resource used for these transfers will never be over-subscribed. These transfers will therefore never be affected by congestion and there will be no losses due to this effect. Then, from the predicted maximum usages of the switch buffers, the maximum delay through the network can also be predicted. However, for the reliability and timeliness to be proved, and for the proofs to be tolerant of faults in and malicious actions by the equipment connected to the network, the calculations of these resource usages cannot be based on any parameters that are not actively enforced by the network, i.e. they cannot be based on what the sources of the traffic are expected to do or on statistical analyses of the traffic characteristics (see network calculus).[11]

However, low latency in transferring data over the bus or network does not necessarily translate into low transport delays between the application processes that source and sink this data. This is especially true where the transfers over the bus or network are cyclically scheduled (as is commonly the case with MIL-STD-1553B and STANAG 3910, and necessarily so with AFDX and TTEthernet) but the application processes are not synchronized with this schedule.

This guides provides an overview features ofRabbitMQ, AMQP 0-9-1 and other supported protocols related to data safety.They help application developers and operators achieve reliable delivery,that is, to ensure that messages are always delivered, even encountering failuresof various kinds.

When using confirms, producers recovering from a channel or connectionfailure should retransmit any messages for which an acknowledgementhas not been received from the broker. There is a possibility ofmessage duplication here, because the broker might have sent aconfirmation that never reached the producer (due to network failures,etc). Therefore consumer applications will need to performdeduplication or handle incoming messages in an idempotent manner.

If a message is delivered to a consumer and then requeued, either automatically byRabbitMQ or by the same or different consumer, RabbitMQ will set the redelivered flag onit when it is delivered again. This is a hint that a consumer may have seenthis message before. This is not guaranteed as the original delivery might have not made it to any consumersdue to a network or consumer application failure.

RabbitMQ provides two plugins to assist with distributing nodes overunreliable networks (such as wide-area networks): Federation andthe Shovel. Both will recover from network failures and retransmit messages when necessary.Both use confirms and acknowledgements by default.

Lost messages are detected, resent and deduplicated as needed. In addition, it also includes flow control for the sending of messages to avoid that a fast producer overwhelms a slower consumer or sends messages at a higher rate than what can be transferred over the network. This can be a common problem in interactions between actors, resulting in fatal errors like OutOfMemoryError because too many messages are queued in the mailboxes of the actors. The detection of lost messages and the flow control is driven by the consumer side, which means that the producer side will not send faster than the demand requested by the consumer side. The producer side will not push resends unless requested by the consumer side.

This is enabled by configuration akka.reliable-delivery.producer-controller.chunk-large-messages and defines the maximum size in bytes of the chunked pieces. Messages smaller than the configured size are not chunked, but serialization still takes place in the ProducerController and ConsumerController.

Amazon Route 53 is a highly available and scalable cloud Domain Name System (DNS) web service. It is designed to give developers and businesses an extremely reliable and cost-effective way to route end users to Internet applications by translating human-readable names, such as, into the numeric IP addresses, such as, that computers use to connect to each other. Amazon Route 53 is fully compliant with IPv6 as well.

Amazon Virtual Private Cloud (Amazon VPC) lets you provision a logically isolated section of the AWS Cloud where you can launch AWS resources in a virtual network that you define. You have complete control over your virtual networking environment, including selection of your own IP address range, creation of subnets, and configuration of route tables and network gateways. You can use both IPv4 and IPv6 in your VPC for secure and easy access to resources and applications.

AWS App Mesh makes it easy to run microservices by providing consistent visibility and network traffic controls for every microservice in an application. App Mesh removes the need to update application code to change how monitoring data is collected or traffic is routed between microservices. App Mesh configures each microservice to export monitoring data and implements consistent communications control logic across your application. This makes it easy to quickly pinpoint the exact location of errors and automatically re-route network traffic when there are failures or when code changes need to be deployed. 041b061a72


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