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Thundering Herd Problem
In computer science, the thundering herd problem occurs when a large number of processes or threads waiting for an event are awoken when that event occurs, but only one process is able to handle the event. When the processes wake up, they will each try to handle the event, but only one will win. All processes will compete for resources, possibly freezing the computer, until the herd is calmed down again. Mitigation The Linux kernel serializes responses for requests to a single file descriptor, so only one thread or process is woken up. For epoll() in version 4.5 of the Linux kernel, the EPOLLEXCLUSIVE flag was added. Thus several epoll sets (different threads or different processes) may wait on the same resource and only one set will be woken up. For certain workloads this flag can give significant processing time reduction. Similarly in Microsoft Windows, I/O completion ports can mitigate the thundering herd problem, as they can be configured such that only one of the threads ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Science
Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to practical disciplines (including the design and implementation of hardware and software). Computer science is generally considered an area of academic research and distinct from computer programming. Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and for preventing security vulnerabilities. Computer graphics and computational geometry address the generation of images. Programming language theory considers different ways to describe computational processes, and database theory concerns the management of repositories o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Input/output Completion Port
Input/output completion port (IOCP) is an API for performing multiple simultaneous asynchronous input/output operations in Windows NT versions 3.5 and later, AIX and on Solaris 10 and later. An input/output completion port object is created and associated with a number of sockets or file handles. When I/O services are requested on the object, completion is indicated by a message queued to the I/O completion port. A process requesting I/O services is not notified of completion of the I/O services, but instead checks the I/O completion port's message queue to determine the status of its I/O requests. The I/O completion port manages multiple threads and their concurrency. See also *Overlapped I/O * kqueue *epoll epoll is a Linux kernel system call for a scalable I/O event notification mechanism, first introduced in version 2.5.44 of the Linux kernel. Its function is to monitor multiple file descriptors to see whether I/O is possible on any of them. It i ... References Exte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Exponential Backoff
Exponential backoff is an algorithm that uses feedback to multiplicatively decrease the rate of some process, in order to gradually find an acceptable rate. These algorithms find usage in a wide range of systems and processes, with radio networks and computer networks being particularly notable. Exponential backoff algorithm An exponential backoff algorithm is a form of closed-loop control system that reduces the rate of a controlled process in response to adverse events. Each time an adverse event is encountered, the rate of the process is reduced by some multiplicative factor. Examples of adverse events include collisions of network traffic, an error response from a service, or an explicit request to reduce the rate (i.e. "back off"). The rate reduction can be modelled as an exponential function: :t = b^c or :f = \frac Here, is the time delay applied between actions, is the multiplicative factor or "base", is the number of adverse events observed, and is the frequen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jitter
In electronics and telecommunications, jitter is the deviation from true periodicity of a presumably periodic signal, often in relation to a reference clock signal. In clock recovery applications it is called timing jitter. Jitter is a significant, and usually undesired, factor in the design of almost all communications links. Jitter can be quantified in the same terms as all time-varying signals, e.g., root mean square (RMS), or peak-to-peak displacement. Also, like other time-varying signals, jitter can be expressed in terms of spectral density. Jitter period is the interval between two times of maximum effect (or minimum effect) of a signal characteristic that varies regularly with time. Jitter frequency, the more commonly quoted figure, is its inverse. ITU-T G.810 classifies jitter frequencies below 10 Hz as wander and frequencies at or above 10 Hz as jitter. Jitter may be caused by electromagnetic interference and crosstalk with carriers of other signals. Jit ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Process Management (computing)
A process is a program in execution, and an integral part of any modern-day operating system (OS). The OS must allocate resources to processes, enable processes to share and exchange information, protect the resources of each process from other processes and enable synchronization among processes. To meet these requirements, the OS must maintain a data structure for each process, which describes the state and resource ownership of that process, and which enables the OS to exert control over each process. Multiprogramming In any modern operating system there can be more than one instance of a program loaded in memory at the same time. For example, more than one user could be executing the same program, each user having separate copies of the program loaded into memory. With some programs, it is possible to have one copy loaded into memory, while several users have shared access to it so that they each can execute the same program-code. Such a program is said to be re-entrant. The ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lock Convoy
In computer science, a lock convoy is a performance problem that can occur when using locks for concurrency control in a multithreaded application. A lock convoy occurs when multiple threads of equal priority contend repeatedly for the same lock. Unlike deadlock and livelock situations, the threads in a lock convoy do progress; however, each time a thread attempts to acquire the lock and fails, it relinquishes the remainder of its scheduling quantum and forces a context switch. The overhead of repeated context switches and underutilization of scheduling quanta degrade overall performance. Lock convoys often occur when concurrency control primitives such as locks serialize access to a commonly used resource, such as a memory heap or a thread pool. They can sometimes be addressed by using non-locking alternatives such as lock-free algorithms or by altering the relative priorities of the contending threads. See also * Thundering herd problem In computer science, the thund ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sleeping Barber Problem
In computer science, the sleeping barber problem is a classic inter-process communication and synchronization problem that illustrates the complexities that arise when there are multiple operating system processes. The problem was originally proposed in 1965 by computer science pioneer Edsger Dijkstra, who used it to make the point that general semaphores are often superfluous. Problem statement Imagine a hypothetical barbershop with one barber, one barber chair, and a waiting room with ''n'' chairs (''n'' may be 0) for waiting customers. The following rules apply: * If there are no customers, the barber falls asleep in the chair * A customer must wake the barber if he is asleep * If a customer arrives while the barber is working, the customer leaves if all chairs are occupied and sits in an empty chair if it's available * When the barber finishes a haircut, he inspects the waiting room to see if there are any waiting customers and falls asleep if there are none There are two m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
TCP Global Synchronization
TCP global synchronization in computer networks can happen to TCP/ IP flows during periods of congestion because each sender will reduce their transmission rate at the same time when packet loss occurs. Routers on the Internet normally have packet queues, to allow them to hold packets when the network is busy, rather than discarding them. Because routers have limited resources, the size of these queues is also limited. The simplest technique to limit queue size is known as tail drop. The queue is allowed to fill to its maximum size, and then any new packets are simply discarded until there is space in the queue again. This causes problems when used on TCP/IP routers handling multiple TCP streams, especially when bursty traffic is present. While the network is stable, the queue is constantly full, and there are no problems except that the full queue results in high latency. However, the introduction of a sudden burst of traffic may cause large numbers of established, steady stre ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cache Stampede
A cache stampede is a type of cascading failure that can occur when massively parallel computing systems with caching mechanisms come under very high load. This behaviour is sometimes also called dog-piling. To understand how cache stampedes occur, consider a web server that uses memcached to cache rendered pages for some period of time, to ease system load. Under particularly high load to a single URL, the system remains responsive as long as the resource remains cached, with requests being handled by accessing the cached copy. This minimizes the expensive rendering operation. Under low load, cache misses result in a single recalculation of the rendering operation. The system will continue as before, with average load being kept very low because of the high cache hit rate. However, under ''very'' heavy load, when the cached version of that page expires, there may be sufficient concurrency in the server farm that multiple threads of execution will all attempt to render the con ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
