Having said that, things become utterly easy for you when you use Peer to Peer P2P File Sharing Software for sharing files with your friends and dear ones. With P2P Software , you can easily download or upload huge amount of data over the Internet quickly and without any hassles or restrictions.
It uses a P2P Program or P2P Software for downloading or uploading media files such as music, games, movies, and books. The use of peer-to-peer file sharing has increased over the years largely due to the availability of increased bandwidth, the widespread digitization of physical media and also because of increased capabilities of personal computers. However, not all of them are safe to work with. Many are known to spread viruses and malware. This best P2P File Sharing Software come with multitudes of capabilities and allow sharing of multiple directories and files together with safe and secure file sharing.
These file sharing software allow you to share large files and folders. They also enable you to download software , audio, video, images, data, and eBooks from numerous P2P Networks. With these P2P Programs, you can easily download many files at a time. They even allow you to preview files when downloading. We are sure you would find a one matching your requirements.
If you are looking for a safe and controlled downloading experience over the Internet, then BitTorrent is the P2P File Sharing Software that you should consider. Dubbed as the original BitTorrent Client, it is the preferred file sharing software for downloading large files. Dictionary Dictionary Term of the Day.
Decentralized Finance. Techopedia Terms. Connect with us. Sign up. Term of the Day. Best of Techopedia weekly. News and Special Offers occasional. Find and download torrents as well as play media. Download and manage torrent files with an efficient, lightweight, and customizable application. BitTorrent Free. Search the Internet for torrent files, and download and upload files on a peer-to-peer network. Tribler Free. Find, enjoy, share, and consume the contents. Halite BitTorrent Client bit Free.
Download and share files via bittorrent protocol. Halite BitTorrent Client Free. Tixati bit Free. Download and manage torrent downloads. Tixati Portable Free. Tixati Free. BitLord Free. Distribute and download files via Torrent P2P protocol. However, existing matchmaking systems, which function in the client-server model [ 26 ], may connect players in many ways. The most simple case is random matchmaking, in which players subsequently connecting to the server play with each other.
Another way is to allow players to create named game instances. Since they are publicly visible, other players may see all of them and join a game instance of their choice. It may also be the case that a global ranking system exists such as ELO [ 27 ], Trueskill [ 28 ] and that players with similar ranking scores are chosen to play together. Players may be connected based on other criteria such as age or country as well. Many matchmaking strategies compare multiple possible matches and choose an approximately satisfying result.
We still would choose to match players with ranking points difference if no better matches are available after, say, 1 minute — as players are unwilling to wait longer. Thus, we propose to direct player requests to a group of nodes which will process it. Concretely, we propose a failure resistant group structure, which enables efficient workload division among its members.
The structure elects one node as a leader. Furthermore, we describe a design of the system composed of multiple groups and show how to use it to implement custom matchmaking strategies. This paper aims to provide a solution for the problem of matchmaking players in multiplayer games on the scale of the Internet, without using a central server.
Implementing all of the aforementioned strategies in a single library would be a daunting task. Instead, in the paper we propose a P2P platform — the SelfAid network, which facilitates the process of setting up those strategies in a P2P environment, and ensures their appropriate instantiation, load balancing and replication.
With the use of the proposed solution, a game developer can obtain a matchmaking system for his game by providing only a specific matchmaking strategy further in the paper called a service algorithm. The SelfAid platform is responsible for creating at runtime processes running the defined service algorithm at the machines of some players. Furthermore, it finds provides an IP address of a process when a player wants to find an opponent.
The traffic to processes is subject to load balancing. What is more, if load on the node running the process proves to be too much, the SelfAid network creates additional processes.
This ensures that the nodes of SelfAid network use only their spare bandwidth. On the other hand, if the load on processes is too small players have to wait for a long time , some instances are deleted. Besides introducing the SelfAid network concept, the paper also discusses the correctness of the proposed solution — all guarantees exposed by the system described in the paper are formally defined and proven.
The paper is structured as follows. Section 2 elaborates on the literature related to the problems of matchmaking players in P2P multiplayer games. Section 3 describes the assumed system model. The conceptual project including functional and non-functional requirements, as well as detailed description of the Self-aid network is presented in Section 4. Section 5 contains description of a proof of concept implementation of the proposed system and an example of a matchmaking service.
Finally, conclusions and further work are presented in Section 6. In Microsoft research released an article describing a latency prediction system called Htrae [ 29 ]. Before, there existed strategies for minimizing latencies experienced by players based on either geolocation data or direct latency measurements. Htrae excels at combining both of those strategies into one. It works similarly to a network coordinate system called Vivaldi [ 30 ], that is, it assigns to each peer coordinates in a virtual spherical space in Vivaldi the space was non-spherical.
The clue of the system is that the initial positions in the virtual space are dictated by geolocation data but they are later adjusted based on latency measurements. This way the distance in virtual space can be used to predict latency between any nodes in the system. The system provides means to predict latencies between players machines, but it is not a complete matchmaking solution ready to use by game developers.
Htrae was designed with P2P games in mind, however the system itself is not free of central components such as GeoIP database or a routing table service for AS correction. Switchboard [ 31 ] is a P2P matchmaking system for mobile devices. Switchboard puts emphasis on scalability, as well as ease of use for game developers. It exposes a cloud service with a simple API for game developers, allowing them to define a few basic criteria for matchmaking.
The available criteria consist of: tolerance for latency, number of players, the exact same requirements e. The main contributions include elaborate methods of predicting latency components specific to cellular networks, the architecture of the cloud service for processing matchmaking requests, and the API for game developers. For latency prediction not specific to cellular networks, the authors decided to use previously described Htrae.
Additionally the matchmaking criteria available to game developers are not sufficient to connect players based on a ranking scheme. Both previously described works focused on reducing latency between players, as the most important problem in matchmaking.
The authors of the next work present another approach to matchmaking, focusing on providing the best user experience by using additional data about players to prevent hostile situations during gameplay.
The game is played as a match between two teams. Each team is created from players chosen to some degree randomly by the matchmaking system. Once the team is formed, each player is allowed to choose a character whom they will be playing during the match in order of their ranking the best player chooses first. Each available character corresponds to a different role and style of play and can be chosen only by one player.
The combination of the aforementioned factors results in the dissatisfaction of lower ranking players when they are forced to choose a character they do not like. The idea described in the article is to keep track of the players preference to specific characters and then compose teams of people with non-overlapping preferences.
This article shows how case specific matchmaking rules may be required for a good user experience. LOM [ 33 ], presents an attempt to create a general matchmaking system, using an abstract association criterion. The goal of LOM is to group players into independently running game sessions comprising of a certain amount of players.
In order to achieve this, a leader for each group is chosen e. The problem is then transformed into a minimum-cost flow problem where the source is connected to a layer of leaders, which in turn is connected to a layer of members all players who are not leaders , which converges in target node. The weights on the arcs between leaders and members correspond to the association criterion which is defined by game developer as e.
It is an efficient design of a server-based flexible matchmaking system. Each of the mentioned works focuses on a different matchmaking strategy and presents a concrete solution for the considered problem. The aim of this paper is to provide a more flexible solution. Instead of focusing on a single matchmaking strategy, a platform supporting any matchmaking strategy is proposed.
The SelfAid system described in this paper is a decentralized and structured P2P network. It does not feature a central node like Napster [ 34 ] or supernodes like Kazaa [ 35 ]. Instead, all nodes in the system have equal roles — they perform the same tasks and have the same rights. As all structured P2P networks, the SelfAid has a precisely defined set of rules on how nodes should choose with whom they establish and maintain connection.
Following the trend of sharing economy, SelfAid network assigns only as much work to a particular node as it can handle using spare resources. SelfAid network is a synchronized distributed system, which means that the Upper bound Transmission Time of messages [ 37 ] is assumed to be known further abbreviated UTT. All algorithms presented in this article assume perfect links messages are always delivered and FIFO channels.
Also, it is assumed that failure detection takes at least UTT. Furthermore, the code is executed in a single thread to avoid issues related to concurrent modification of variables. To be able to predict the arrival time of a message from another node, computation is assumed to be instantaneous it cannot cause a message to be delayed. The code in all algorithms contains no blocking operations.
The considered failure model is crash-stop halt failure [ 38 ]. SelfAid network operates under the assumption that each node knows the names unique identifiers of all service algorithms. Once again, a service algorithm is a specific matchmaking strategy implemented by the game developer. A game developer may define many service algorithms. A service algorithm is required to be stateless SelfAid does not provide mechanisms to ensure data consistency across processes. Furthermore, each node is able to run any of the defined service algorithms when asked by the SelfAid network.
In order to do this, a node has to have the code or executable of the service algorithm. One way to achieve this would be for all nodes to get the code or executables of service algorithms beforehand. For example, the code may be embedded in data downloaded in order to play the game. SelfAid network is responsible only for creating processes and providing contact information to reach them, so clients have to know the appropriate protocol to communicate with the service.
The goal of this paper is to provide a platform for building case-specific matchmaking strategies. The developer implements one or more service algorithms a server program for a concrete matchmaking strategy. SelfAid automatically creates processes of a given algorithm, each running on a separate machine. SelfAid also makes the processes available to clients.
For a given algorithm, a client receives addresses of all processes and picks one at random, then sends a request to it. How this request is handled is determined by the algorithm implemented by the developer.
Processes executing the same algorithm A form a group G A. Each group G has one leader, which we name the coordinator C G A. A coordinator is responsible for I publishing the contact information of the processes comprising the group, and II for recruiting new members to lessen the load on all processes.
Matchmaking requires accumulating user requests in one place. To ensure that there is only one group for a matchmaking algorithm, a rule was established.
If there are concurrent groups for the same algorithm, the one which runs longer will prevail. In case of ties, the conflicts are resolved deterministically based on the id of the node which was the first member of the group.
This node is called the original node. The rest of this section is divided into subsections. First subsection contains a description of the ring structure, consisting of nodes running an instance of a particular service algorithm. Variables stored at the nodes are listed as well. Second subsection discusses how a process running a particular service algorithm can be found and defines the concept of an announcement.
Third subsection presents the process of adding new members to the ring structure. Fourth subsection describes when and how nodes are removed from the ring structure. Fifth subsection explains how failures in the ring structure are handled. In order to be able to detect failures, instances are organized in a ring structure, as in the Fig. Each node monitors the state up or down of one other node which is called the parent. Since the coordinator may fail, its responsibilities have to be transferred to another node in case of failure.
The responsibilities include publishing announcements, checking whether they are reachable by clients, adjusting the number of nodes in the ring. In the beginning this role is fulfilled by the original node. Later, the node which detected the failure of a ring coordinator becomes the new ring coordinator. In figures, the node fulfilling the role of ring coordinator is distinguished by a bigger size of the node circle.
In Fig. This solution makes the ring more robust in case of failures because every node knows about all other nodes in the ring and their order.
It is reasonable, assuming that the number of nodes comprising a particular ring grows linearly with a small constant as it should be in case of matchmaking for games. Service algorithm lookup is the task of finding a process P A given the identifier of algorithm A. Processes are located by retrieving from the DHT an announcement stored under the key corresponding to the A identifier.
The announcement contains, among other things, a list of nodes hosting processes running A. In order to ensure proper load balancing, an instance is chosen from the list randomly, with uniform distribution of probability. If no announcement is found, a process is created at the node which issued the request.
As shown in Table 1 , an announcement contains the name of the service algorithm, the list of contact information to the nodes hosting a process running that algorithm, running time of the ring, hash of the original node identifier, hash of the service algorithm name. It is possible that many nodes simultaneously tried to lookup a service algorithm which was not run by anybody and ended up creating processes unaware about each other. In order to deal with this situation, the announcement contains additional information.
A node which received request to store an announcement stores it if it contains a higher value of running time than the one currently stored. The nodes publishing announcements must periodically check if their announcements are stored. If not, they should shut down because no clients will contact them.
0コメント