On a two-server finite queuing system with ordered entry and deterministic arrivals

Consider a two-server, ordered entry, queuing system with heterogeneous servers and finite waiting rooms in front of the servers. Service times are negative exponentially distributed. The arrival process is deterministic. A matrix solution for the steady state probabilities of the number of customers in the system is derived. The overflow probability will be used to formulate the stability condition of a closed-loop conveyor system with two work stations

Simulation Modeling and Analysis of Adjustable Service-Rate Queueing Models that Incorporate Feedback Control

Research shows that in a system model, when the production rate is adjusted based on the number of items in queue, the nature of the model changes from an open-loop queueing system to a closed-loop feedback control system. Service-rate adjustment can be implemented in a discrete event simulation model, but the effect of this adjustment has not been thoroughly analyzed in the literature. This research considers the design of feedback signals to generate realistic simulation models of production system behavior. A series of simulation experiments is conducted to provide practical guidance for simulation modelers on how adding a service-rate adjustment feedback loop to a queueing system affects system performance

Self-optimizing Uplink Outer Loop Power Control for WCDMA Network

The increasing demands for high data rates, drives the efforts for more efficient usage of the finite natural radio spectrum resources. Existing wideband code division multiple access (WCDMA) uplink outer loop power control has difficulty to answer to the new load on air interface. The main reason is that the maximum allowed noise rise per single user is fixed value. In worst case uplink load can be so high that all services, including conversational service, could be blocked. In this paper investigation has been performed to present correlation of main system parameters, used by uplink outer loop power control, to uplink load. Simulation has been created and executed to present difference in current implementation of uplink outer loop power control against proposed changes. Proposed solution is self-optimizing uplink outer loop power control in a way that maximum allowed noise rise per single user would be dynamically changed based on current uplink load on cell

An analysis of a batch server with variable and class-dependent service capacity

In many studies on batch service queueing systems, the service capacity is assumed to be constant. However, this service capacity often depends on the content of the queue. In this paper, we analyse a discrete-time single server batch server queue with general inde- pendent arrivals. We distinguish two dierent classes in the arrival stream and products of both classes are added to the tail of a single queue. The single batch server can group all waiting customers at the head of the queue that belong to the same product class up to a certain class-dependent maximum capacity. This results in a stochastic service capacity that depends on both the number of customers in the queue and their respective classes. Since it is clear that the length of a sequence of same-class customers will have a signicant impact on the performance of the system, we also include correlation between the classes of consecutive customers. Applications of this type of batch server can, for instance, be found in the pacemaker loop of a Lean manufacturing system. In the course of the analysis, we calculate the probability generating function of the system occupancy at service initi- ation opportunities. In the numerical experiments, we will look at the impact of dierent parameters on both the mean system occupancy and the probability that the server is idle at a random service initiation opportunity. We also provide a number of guidelines to pick between the exact solution and an approximated approach with unlimited service capacities, by looking at the trade-o between accuracy and computational complexity

A Runtime Verification and Validation Framework for Self-Adaptive Software

The concepts that make self-adaptive software attractive also make it more difficult for users to gain confidence that these systems will consistently meet their goals under uncertain context. To improve user confidence in self-adaptive behavior, machine-readable conceptual models have been developed to instrument the adaption behavior of the target software system and primary feedback loop. By comparing these machine-readable models to the self-adaptive system, runtime verification and validation may be introduced as another method to increase confidence in self-adaptive systems; however, the existing conceptual models do not provide the semantics needed to institute this runtime verification or validation. This research confirms that the introduction of runtime verification and validation for self-adaptive systems requires the expansion of existing conceptual models with quality of service metrics, a hierarchy of goals, and states with temporal transitions. Based on this expanded semantics, runtime verification and validation was introduced as a second-level feedback loop to improve the performance of the primary feedback loop and quantitatively measure the quality of service achieved in a state-based, self-adaptive system. A web-based purchasing application running in a cloud-based environment was the focus of experimentation. In order to meet changing customer purchasing demand, the self-adaptive system monitored external context changes and increased or decreased available application servers. The runtime verification and validation system operated as a second-level feedback loop to monitor quality of service goals based on internal context, and corrected self-adaptive behavior when goals are violated. Two competing quality of service goals were introduced to maintain customer satisfaction while minimizing cost. The research demonstrated that the addition of a second-level runtime verification and validation feedback loop did quantitatively improve self-adaptive system performance even with simple, static monitoring rules

Close the loop! System dynamics modelling in service design

Service design is a thought process using creativity, empathy in responding to a customer's need and rationality in an analysis of a recommended, innovative solution. In this paper, we propose a research methods system which enables designers to integrate design and systems thinking into a system dynamics model of a creative project. Based on these research methods, topics and problems can be detected, and solutions can be proposed. The communicative game "Close the Loop!" which uses elements of visual language, and modifies the Grounded Theory method and its three processes: open coding, axial coding, and selective coding. The aim of the game is to create a Causal Loop Diagram which expresses a dynamic hypothesis, a Stock and Flow Diagram, which solves the problem visually and follows the Causal Loop Diagram. The accuracy of this set of method is demonstrated by its application in a case study from the service area. The article is intended for researchers who endeavour to use research methods in order to improve their services and meet a customer's requirements.[RO40182011025

On human-in-the-loop CPS in healthcare: a cloud-enabled mobility assistance service

Despite recent advancements on cloud-enabled and human-in-the-loop cyber-physical systems, there is still a lack of understanding of how infrastructure-related quality of service (QoS) issues affect user-perceived quality of experience (QoE). This work presents a pilot experiment over a cloud-enabled mobility assistive device providing a guidance service and investigates the relationship between QoS and QoE in such a system. In our pilot experiment, we employed the CloudWalker, a system linking smart walkers and cloud platforms, to physically interact with users. Different QoS conditions were emulated to represent an architecture in which control algorithms are performed remotely. Results point out that users report satisfactory interaction with the system even under unfavorable QoS conditions. We also found statistically significant data linking QoE degradation to poor QoS conditions. We finalize discussing the interplay between QoS requirements, the human-in-the-loop effect, and the perceived QoE in healthcare applications