Performance: Network Communication Optimization and Communication Protocol

introduction

Hi, everyone! I am Xiaomi, welcome to today's technical sharing time! Today we will discuss a very important topic - "Communication Protocol for Network Communication Optimization", which must be very familiar to those of us who are keen on technology. Without further ado, let's take a deep look at the core of microservice architecture and how to optimize network communication and improve system performance!

The core of microservice architecture

As a modern software design concept, microservice architecture has become the first choice for many companies to build complex systems. Its core concept is to split a large monolithic application into multiple small and autonomous services, each of which focuses on completing specific business functions. The core of microservice architecture is not only the technical split, but more importantly, the series of design principles and practical methods behind it, which together constitute the core essence of microservice architecture.

• First of all, one of the core elements of microservice architecture is remote communication. In a system composed of multiple microservices, each service needs to communicate frequently to complete complex business logic. This remote communication can be achieved through various protocols and technologies, such as HTTP, TCP, UDP, etc. How to efficiently conduct remote communication has become an important challenge in the design of microservice architecture.
• Secondly, service governance is also one of the core elements of microservice architecture. As the scale of the system expands, microservice architecture often faces problems such as service discovery, load balancing, and fault tolerance. The goal of service governance is to dynamically manage and monitor these services to ensure the stability and reliability of the system. In microservice architecture, technologies such as service registration and discovery, circuit breaker mode, and automatic scaling are usually used to implement service governance.
• In addition, the microservice architecture also focuses on the autonomy and independent deployment of services. Each microservice should have an independent database and code base, and can be deployed and upgraded independently without affecting other services. This autonomy makes the microservice architecture more flexible and scalable, and can better respond to changing business needs and technical challenges.

What is RPC communication

RPC (Remote Procedure Call) is a technology used to implement communication between different computers in a distributed system. Its core idea is to allow a program to call a procedure or function in another address space (usually on another machine) just like calling a local function, without the need for developers to explicitly write remote call code.

The working principle of RPC communication is relatively simple and direct, and mainly includes four steps: the client calls the remote procedure, the client communication module encapsulates the call information, the client communication module transmits the call information to the server through the network, and the server communication module receives the call information and parses and executes the corresponding remote procedure. This transparent remote call method allows developers to split the development, testing and maintenance of each component of the distributed system, greatly improving the maintainability and scalability of the system.

In RPC communication, common implementation methods include RESTful API based on HTTP protocol, remote calls based on XML-RPC or JSON-RPC, and Protobuf, Thrift, and gRPC based on binary protocols. Different implementation methods have their own advantages and disadvantages, and developers can choose the most appropriate method based on specific needs and scenarios.

RPC communication has a wide range of application scenarios, especially for building distributed systems and microservice architectures. Through RPC, different microservices can easily call each other to complete complex business logic. For example, in an e-commerce platform, the order service may need to call the user service to obtain user information, call the inventory service to check the inventory of goods, and call the payment service to complete the payment operation, and these calls can be implemented through RPC.

RMI: JDK's own RPC communication framework

RMI (Remote Method Invocation) is an object-based remote calling mechanism provided by the Java language. Its implementation principle involves key components such as remote objects, stubs, and skeletons. Let's take a deeper look at the implementation principle of RMI.

First of all, the core of RMI is the remote object. In RMI, a remote object refers to an object running on the server side, whose methods can be called by remote clients. In order for a remote object to be called by a remote client, two conditions must be met: first, the remote object must implement a remote interface (Remote Interface), which declares the methods of the remote object; second, the remote object must inherit from the java.rmi.server.UnicastRemoteObject class, which implements the basic functions of the remote object, including remote method calls and network communications.

Secondly, the client makes a remote method call through the stub of the remote object. The stub is a local proxy object that encapsulates the reference of the remote object and the details of network communication, allowing the client to call the method of the remote object just like calling a local object. The stub implements the remote interface and maintains the reference and communication channel of the remote object. When the client calls the method of the stub, the stub will encapsulate the method call into a network message and send it to the server where the remote object is located.

Finally, the server receives and processes the method call request sent by the client through the skeleton. The skeleton is a special object that is responsible for receiving the method call request sent by the client and dispatching the request to the actual remote object for execution. The skeleton generates a proxy object of the remote object through dynamic proxy technology, and forwards the method call request sent by the client to the proxy object for processing. In this way, the remote object can be called on the server side, and the client can communicate with the remote object through the stub and the skeleton.

RMI performance bottleneck in high-concurrency scenarios

In high-concurrency scenarios, RMI (Remote Method Invocation) may face various performance bottlenecks that may affect the performance and throughput of the system. Let's take a deeper look at the performance challenges and possible solutions of RMI in high-concurrency scenarios.

• First, Java default serialization is one of the performance bottlenecks of RMI. Java uses the Java serialization mechanism by default to serialize and deserialize the parameters and return values ​​of remote method calls, but the efficiency of the Java serialization mechanism is relatively low, resulting in high CPU and memory overhead. Especially in high-concurrency scenarios, a large number of serialization and deserialization operations may become a bottleneck for the system.
• Secondly, TCP short connection is also one of the performance bottlenecks of RMI. RMI uses TCP protocol by default for communication, and the short connection mode of TCP protocol will lead to a large number of connection establishment and disconnection operations, increasing system overhead and latency. In high-concurrency scenarios, frequent TCP connection management may become a bottleneck of the system, reducing the system's throughput and concurrent processing capabilities.
• In addition, blocking network I/O is also one of the performance bottlenecks of RMI. RMI uses blocking network I/O for communication by default, which means that each request will cause the thread to be blocked until the network response returns. In high-concurrency scenarios, a large number of blocked threads will consume a lot of system resources and reduce the system's response speed and throughput.

An RPC communication optimization path in a high-concurrency scenario

To address the above performance bottlenecks, we can adopt a series of optimization strategies to improve the performance of RPC communication.

• Choose the right communication protocol: First of all, choosing the right communication protocol is a key step in optimizing RPC communication. Different communication protocols have different effects on performance. For example, HTTP-based communication protocols usually add a certain amount of overhead, while binary-based communication protocols can reduce the size of data transmission and network latency. Therefore, in high-concurrency scenarios, you can consider choosing a lighter and more efficient communication protocol, such as binary-based Protobuf, Thrift, and gRPC.
• Use a single persistent connection: Secondly, using a single persistent connection can reduce the number of TCP connection establishment and disconnection times and improve the concurrent processing capability of the system. Compared with frequently establishing and closing TCP connections, using a single persistent connection can reduce network communication overhead, thereby improving system performance and stability. Therefore, in high-concurrency scenarios, you can consider using persistent connections to optimize RPC communication and reduce connection management overhead.
• Optimize Socket communication: In Socket communication, we can take a variety of optimization measures to improve performance.

Implement non-blocking I/O: Traditional blocking I/O will cause threads to be blocked while waiting for network responses, wasting valuable CPU time. Non-blocking I/O allows threads to continue to perform other tasks while waiting for network responses, improving the system's concurrent processing capabilities and response speed. By using technologies such as Java NIO (New I/O), non-blocking I/O can be implemented, thereby improving the efficiency of Socket communication.

• Efficient Reactor thread model: The Reactor thread model uses a small number of threads to handle a large number of concurrent connections, making full use of system resources and improving the system's concurrent processing capabilities and throughput. In Java, you can use tools such as Selector to implement the Reactor thread model, thereby optimizing the performance of Socket communication.

• Serial design: In high-concurrency scenarios, multiple threads may access shared resources at the same time, resulting in competition between threads and lock contention, which in turn affects system performance. By designing a reasonable serial processing mechanism, you can reduce competition between threads and improve system stability and reliability. For example, you can use a thread pool to limit the number of connections processed simultaneously, or use a queue to cache requests to reduce system pressure.

• Zero copy: In the traditional data transmission process, data needs to be copied from kernel space to user space, and then from user space to network buffer, which will generate additional copy overhead. Zero copy technology can avoid this additional copy overhead and directly transfer data between kernel space and network buffer, thus improving the efficiency and speed of data transmission.

Finally, adjusting Socket parameters is also an important means to optimize Socket communication performance.

• TCP_NODELAY: The TCP_NODELAY option can disable the Nagle algorithm, reduce the delay of TCP data packets, and improve the real-time performance of data transmission.
• SO_RCVBUF and SO_SNDBUF: By adjusting the SO_RCVBUF and SO_SNDBUF options, you can optimize the size of the Socket buffer and improve the efficiency of data transmission.
• SO_BACKLOG: Adjusting the SO_BACKLOG option can optimize the connection queue size of the server-side Socket and improve the system's concurrent connection capability.
• SO_KEEPALIVE: By enabling the SO_KEEPALIVE option, you can periodically check the status of TCP connections, release inactive connections in a timely manner, and release system resources.

Tailor-made message format

Tailoring the message format means customizing the data transmission format suitable for a specific scenario based on specific business requirements and system architecture design. In high-concurrency RPC (Remote Procedure Call) communications, using a suitable message format can improve system efficiency and reliability.

• First, the customized message format can design a flexible field structure according to business needs and data structure, including data type, field length, check bit and other information to ensure data integrity and correctness. Through reasonable field design, the size of data transmission can be reduced, network overhead can be reduced, and system throughput can be improved.
• Secondly, the message format can be tailored to the system architecture design by selecting the appropriate encoding method, such as binary encoding or text encoding. Binary encoding can reduce the data transmission size and network bandwidth usage, and improve the efficiency of data transmission; while text encoding is easier for humans to read and understand, and is convenient for debugging and maintenance.
• In addition, when tailoring the message format, you can also consider adding additional metadata information, such as message type, version number, timestamp, etc., to facilitate message identification and processing. By adding metadata information, you can improve the scalability and compatibility of the system and adapt to different versions and types of message formats.

Encoding and decoding

Encoding and decoding are essential steps in the data transmission process, especially in RPC (Remote Procedure Call) communication. Encoding is to convert data into a byte stream in a specific format for transmission over the network; decoding is to convert the received byte stream back to the original data format for subsequent processing by the program.

In high-concurrency RPC communications, efficient encoding and decoding algorithms can greatly improve system performance and throughput. A common encoding method is to use binary encoding to convert data into a compact byte stream, reducing the size of data transmission and network bandwidth usage. In contrast, text encoding is easier for humans to read and understand, but it usually increases the overhead of data transmission.

During the decoding process, the integrity and correctness of the data need to be considered. In order to prevent data damage or tampering, check bits or signature information can be added to the data and checked during the decoding process to ensure the integrity and correctness of the data. In addition, you can also consider using compression algorithms to compress the data to reduce the size of data transmission and improve the throughput of the system.

In addition to choosing the right encoding method, optimizing encoding and decoding algorithms is also the key to improving system performance. By optimizing encoding and decoding algorithms, you can reduce CPU and memory consumption and improve system processing capabilities and response speed. For example, you can use a buffer-based data reading and writing method to reduce the number of memory allocation and release times; you can use efficient data structures and algorithms to improve the speed and efficiency of encoding and decoding.

Adjust Linux TCP parameter settings options

Adjusting Linux TCP parameter setting options is one of the important means to optimize RPC (Remote Procedure Call) communication performance. In high-concurrency scenarios, properly configuring TCP parameters can improve the efficiency and stability of network communication, thereby improving system performance and throughput.

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