TL;DR: In this article, a QoS management system for a data packet transmission network, where routers offer priority services of the type required for isochronous handling of data representing real-time voice, includes a Quality of Service (QoS) management system to ensure that guarantees associated with such priority service can be met with a high degree of certainty.
Abstract: A packet router for a data packet transmission network, wherein routers offer priority services of the type required for isochronous handling of data representing real-time voice, includes a Quality of Service (QoS) management system for ensuring that guarantees associated with such priority service can be met with a high degree of certainty. This management system provides prioritized queues including a highest priority queue supporting reservations for the priority service suited to isochronous handling. The highest priority queue and other queues are closely monitored by a QoS manager element for states of near congestion and critical congestion. While neither state exists, filler packet flows are promoted from lower priority queues to the highest priority queue, in order to keep the latter queue optimally utilized. If all lower priority queues are empty at such times, dummy packets are inserted as filler flows. Dummy packets have a form causing routers and other stations receiving them to immediately discard them. The volume of dummy traffic allowed for each queue of the system is a predetermined fraction of the queue's estimated peak traffic load, and that volume is displaceable to allow forwarding of additional traffic through the queue when conditions require it. While a state of near congestion exists, the QoS manager demotes filler flow units from the highest priority queues to lower priority queues, in order to lessen the potential forwarding delays presented to real traffic occupying the highest priority queue. When a state of critical congestion exists in the highest priority queue, admission of new incoming traffic flows to that queue is suspended and forwarding of filler flows from that queue out to the network is also suspended.
TL;DR: In this article, an improved estimated waiting time arrangement is proposed to derive a more accurate estimate of how long a call that is or may be enqueued in a particular queue will have to wait before being serviced by an agent, by using the average rate of advance of calls through positions of the particular queue.
Abstract: In an automatic call distribution (ACD) system, an improved estimated waiting time arrangement derives a more accurate estimate of how long a call that is or may be enqueued in a particular queue will have to wait before being serviced by an agent, by using the average rate of advance of calls through positions of the particular queue. For a dequeued call, the arrangement determines the call's individual rate of advance from one queue position to the next toward the head of the queue. It then uses this individual rate to recompute a weighted average rate of advance through the queue derived from calls that preceded the last-dequeued call through the queue. To derive a particular call's estimated waiting time, the arrangement multiplies the present weighted average rate of advance by the particular call's position number in the queue. The arrangement may be called upon to update the derivation at any time before or while the call is in queue. Also, the arrangement performs the estimated waiting time derivation separately and individually for each separate queue. The arrangement advantageously takes into consideration the effect of ACD features that affect the estimated waiting time, including changes in the numbers of agents that are serving the queue due to agent login and logout, multiple split/skill queuing, agents with multiple skills or in multiple splits, priority queuing, interflow, intraflow, and call-abandonment rates.
TL;DR: In this paper, the authors present a system for delegating security rights to Java servlets and other executable tasks by using secure operating system queues, where the servlet submitted by a given user runs in the context of that user's rights.
Abstract: Methods, systems, and devices are provided for delegating security rights to Java servlets and other executable tasks by using secure operating system queues In particular embodiments, the invention allows secure loading of Java servlets on a Novell NetWare server The invention allows users to run servlets from various locations with the same rights, namely, the user's rights The servlet submitted by a given user runs in the context of that user's rights A system according to the invention verifies that the user has the right to submit the task to a given task queue; the queue is managed by the system, and the user is authenticated to the system Queue servers which receive tasks from the queue and service them by executing the tasks are likewise authenticated by the system When a queue server attempts to service a task in a queue, the system verifies that the queue server has rights to service that queue and that job This two way verification—that a user has rights to submit the task, and that the queue server has rights to service the task—allows the user and the queue server to establish a trusted relationship using the operating system's trusted queues Moreover, existing user rights databases and access control systems can be used to determine and enforce rights and trust levels
TL;DR: In this paper, an apparatus and methods for periodic load balancing in a multiple run queue system are provided, which includes a controller, memory, initial load balancing device, idle load balancing, periodic weight balancing and starvation load balancing.
Abstract: An apparatus and methods for periodic load balancing in a multiple run queue system are provided. The apparatus includes a controller, memory, initial load balancing device, idle load balancing device, periodic load balancing device, and starvation load balancing device. The apparatus performs initial load balancing, idle load balancing, periodic load balancing and starvation load balancing to ensure that the workloads for the processors of the system are optimally balanced.