Congestion Avoidance

Frame-Relay is a technology that can be used to enhance the transmission of packets over a network. Over the years, the X.25 technology which has been widely used has led to several congestion problems and data loss during transmission of data through a network due to its inherent weak congestion control mechanism. The X.25 is a packet switched technology characterized with extensive protocol processing at the network nodes that causes delay and limits the available transfer speeds to 64 kbps, which is evidently insufficient for the end-users needs. It is therefore necessary to re-evaluate packet switching to meet the growing demands of the users. This research designs a network congestion control system using Frame Relay technology which uses DLCIs (Data Link Connection Identifiers), FECN (Forward Explicit Congestion Notification) and BECN (Backward Explicit Congestion Notification) to resolve the problem of queue management in the network, and modifies the mathematical model of the Queue control system in FECN thus eliminating congestion in the networks. While the Waterfall Methodology was deployed its design, the system was developed using Cisco Packet Tracer 6.0.1 for Windows and simulated using PHP, and XAMP. The Frame-Relay Technology is not only capable of reducing the prevalent congestion problems experienced in X.25 technology but also improves the low Speed of X.25 due to its incorporated efficient management of the queue in the switches during data transmissions.

Virtual characters in games and simulations often need to plan visually convincing paths through a crowded environment. This paper describes how crowd density information can be used to guide a large number of characters through a crowded environment. Crowd density information helps characters avoid congested routes that could lead to traffic jams. It also encourages characters to use a wide variety of routes to reach their destination. Our technique measures the desirability of a route by combining distance information with crowd density information. We start by building a navigation mesh for the walkable regions in a polygonal two-dimensional (2-D) or multilayered three-dimensional (3-D) environment. The skeleton of this navigation mesh is the medial axis. Each walkable region in the navigation mesh maintains an up-to-date density value. This density value is equal to the area occupied by all the characters inside a given region divided by the total area of this region. These density values are mapped onto the medial axis to form a weighted graph. An A search on this graph yields a backbone path for each character, and forces are used to guide the characters through the weighted environment. The characters periodically replan their routes as the density values are updated. Our experiments show that we can compute congestion-avoiding paths for tens of thousands of characters in real-time.

The occurrence of congestion has an extremely deleterious impact on the performance of Wireless Sensor Networks (WSNs). This article presents a novel protocol, named COALA (COngestion ALleviation and Avoidance), which aims to act both proactively, in order to avoid the creation of congestion in WSNs, and reactively, so as to mitigate the diffusion of upcoming congestion through alternative path routing. Its operation is based on the utilization of an accumulative cost function, which considers both static and dynamic metrics in order to send data through the paths that are less probable to be congested. COALA is validated through simulation tests, which exhibit its ability to achieve remarkable reduction of loss ratios, transmission delays and energy dissipation. Moreover, the appropriate adjustment of the weighting of the accumulative cost function enables the algorithm to adapt to the performance criteria of individual case scenarios.