Showing papers on "Destination-Sequenced Distance Vector routing published in 1969"

Traffic control for modifying the routing plan in a network of switching centers

Abstract: A communications network is disclosed wherein the code translation and routing apparatus at each switching center includes a memory having a number of code words and a number of routing words. Each code word stores a code which usually comprises three or six digits used in an associative search by comparison with the corresponding dialed digits. Each code word or group of code words is followed by one or three routing words, each of which designates one or more trunk groups, which may comprise a primary route and a number of alternate routes. Some of the code words include an automatic traffic control digit which directs which one of three routing words is to be used. The value of the traffic digit for each code or group of codes may be modified by a traffic controller by a call from a special station, to thereby designate which one of three predetermined routing plans stored in the respective routing words is to be used. Thus under abnormal traffic conditions caused, for example, by overloads in emergencies, or destruction of facilities, the traffic routing plan may be modified.

Simulation of a Computer Aided Routing System (CARS)

Abstract: CARS is s system designed to provide a taxi-like service at a mass transit-like cost. It allows potential passengers to request service from their via telephone, with calls being processed by a central computer facility. The computer periodically executes a routing algorithm which assigns vehicles to passengers and communicates this routing information to the vehicles. The system is 'real time' in that it will pick up a passenger and shortly after a request will deliver him to his destination within a guaranteed time (with a minimum number of deviations for collecting and delivering other passengers). The key to CARS is the routing algorithm. Since labor and vehicular costs are a major portion of the total system cost, an algorithm is required which can provide an effective dynamic service with a minimum number of vehicles. A variety of such algorithms have been proposed, but these algorithms can not be evaluated in an analytic fashion. Hence, a comprehensive simulation model has been developed to test and compare these routing algorithms. The model facilitates the investigation of relationships between such parameters as number of vehicles and quality of service. This paper describes the methodology of the simulation model and the economic gains (in terms of the need for fewer vehicles) realized through its use. The use of an ARDS storage tube display to produce graphical output from the model is also discussed.

Dynamic Communication Networks with Capacity Constraints

Abstract: Communication networks with link transit times are modeled by linear graphs with branch time delays and finite branch capacities. Memoryless linear routing strategies as well as linear routing strategies with finite memory are defined. The state reachability problem in both cases is considered, and the sets of reachable demand vectors are exhibited. The problem of finding optimal routings which minimize network losses subject to demand constraints is formulated as a linear program, and extensions to infinite memory and time-varying systems are given.

EA-COR: An Environment Adaptive Clustering Opportunistic Routing Protocol of WSN

Abstract: Generally, the radio channel quality of a wireless sensor network (WSN) is unstable in harsh environment. For instance, in maritime search and rescue, the nodes of WSN move dynamically, the topology changes with respect to the time and the communication link changes frequently as well. What is more, the given communication distance of nodes can limit the efficiency of routing. In view of these characteristics of wireless sensor networks in a harsh environment, environment adaptive clustering opportunistic routing protocol (EA-COR) is proposed in this paper to improve the unstable communication quality of harsh environment. EA-COR is based on the idea of clustering which combines with the advantages of opportunistic routing. Simulation results show that in a harsh environment EA-COR performs better than the traditional clustering routing and opportunistic routing in the aspects of network throughput, energy efficiency, and packet transmission efficiency