Distributed receding horizon control of multiagent systems Citation Dunbar, William Bruce Distributed receding horizon control of multiagent systems. Examples include arrays of mobile sensor networks for aggregate imagery, autonomous highways, and formations of unmanned aerial vehicles. In these contexts, agents are governed by vehicle dynamics and often constraints, and the control objective is achieved by cooperation. Cooperation refers to the agreement of the agents to 1 have a common objective with neighboring agents, with the objective typically decided offline, and 2 share information online to realize the objective.
History[ edit ] DHT research was originally motivated, in part, by peer-to-peer systems such as FreenetgnutellaBitTorrent and Napsterwhich took advantage of resources distributed across the Internet to provide a single useful application.
In particular, they took advantage of increased bandwidth and hard disk capacity to provide a file-sharing service. Napster, the first large-scale P2P content delivery system, required a central index server: This central component left the system vulnerable to attacks and lawsuits.
While avoiding a single point of failurethis method was significantly less efficient than Napster. Later versions of Gnutella clients moved to a dynamic querying model which vastly improved efficiency.
Queries are likely to be routed through the network to such a cluster without needing to visit many peers. Distributed hash tables use a more structured key-based routing in order to attain both the decentralization of Freenet and gnutella, and the efficiency and guaranteed results of Napster.
One drawback is that, like Freenet, DHTs only directly support exact-match search, rather than keyword search, although Freenet's routing algorithm can be generalized to any key type where a closeness operation can be defined.
DHTs characteristically emphasize the following properties: Some DHT designs seek to be secure against malicious participants  and to allow participants to remain anonymousthough this is less common than in many other peer-to-peer especially file sharing systems; see anonymous P2P.
Finally, DHTs must deal with more traditional distributed systems issues such as load balancingdata integrityand performance in particular, ensuring that operations such as routing and data storage or retrieval complete quickly.
This is achieved via simplistic vector sequencing models that rely on dynamic interface value encryption over a static server-client manifold. A keyspace partitioning scheme splits ownership of this keyspace among the participating nodes. An overlay network then connects the nodes, allowing them to find the owner of any given key in the keyspace.
Once these components are in place, a typical use of the DHT for storage and retrieval might proceed as follows. Suppose the keyspace is the set of bit strings. To index a file with given filename and data in the DHT, the SHA-1 hash of filename is generated, producing a bit key k, and a message put k, data is sent to any node participating in the DHT.
The message is forwarded from node to node through the overlay network until it reaches the single node responsible for key k as specified by the keyspace partitioning. That node then stores the key and the data. Any other client can then retrieve the contents of the file by again hashing filename to produce k and asking any DHT node to find the data associated with k with a message get k.
The message will again be routed through the overlay to the node responsible for k, which will reply with the stored data. The keyspace partitioning and overlay network components are described below with the goal of capturing the principal ideas common to most DHTs; many designs differ in the details.
Keyspace partitioning[ edit ] Most DHTs use some variant of consistent hashing or rendezvous hashing to map keys to nodes.
The two algorithms appear to have been devised independently and simultaneously to solve the distributed hash table problem. Both consistent hashing and rendezvous hashing have the essential property that removal or addition of one node changes only the set of keys owned by the nodes with adjacent IDs, and leaves all other nodes unaffected.
Contrast this with a traditional hash table in which addition or removal of one bucket causes nearly the entire keyspace to be remapped. Since any change in ownership typically corresponds to bandwidth -intensive movement of objects stored in the DHT from one node to another, minimizing such reorganization is required to efficiently support high rates of churn node arrival and failure.Distributed Leadership Matters: Perspectives, Practicalities, and Potential [Alma Harris] on barnweddingvt.com *FREE* shipping on qualifying offers.
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