The Markov-modulated Poisson process (MMPP) cookbook
Performance Evaluation
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
G-networks with multiple classes of negative and positive customers
Theoretical Computer Science
On the Solution of a Nonlinear Matrix Equation arising in Queueing Problems
SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Matrix Analysis and Applications
Probabilistic modelling
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Queueing Systems: Theory and Applications
The MM CPP/GE/c G-Queue: Sojourn Time Distribution
Queueing Systems: Theory and Applications
ICN '01 Proceedings of the First International Conference on Networking-Part 2
PNPM '97 Proceedings of the 6th International Workshop on Petri Nets and Performance Models
A Queueing Model for Pipelined Circuit-Switched Networks with the MMPP Traffic
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Modeling multiple IP traffic streams with rate limits
IEEE/ACM Transactions on Networking (TON)
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Estimating Markov-modulated compound Poisson processes
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
ASMTA '08 Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications
Discrete-time bulk-service queue with two heterogeneous servers
Computers and Industrial Engineering
Modeling a resource contention in the management of virtual organizations
Information Sciences: an International Journal
A new performability model for queueing and FDL-related burst loss in optical switching nodes
Computer Communications
An initiative for a classified bibliography on G-networks
Performance Evaluation
Spectral expansion solutions for markov-modulated queues
Network performance engineering
Generalized QBD processes, spectral expansion and performance modeling applications
Network performance engineering
Bibliography on G-networks, negative customers and applications
Mathematical and Computer Modelling: An International Journal
An efficient model for dimensioning an ATA-based virtual storage system
Computers and Electrical Engineering
M/M/1 retrial queue with working vacations and negative customer arrivals
International Journal of Advanced Intelligence Paradigms
| Hi-index | 0.00 |
A new queue, referred to here as the HetSigma queue, in the Markovian framework, is proposed in order to model nodes in modern telecommunication networks. The queue has many of the necessary ingredients, such as joint (or individual) Markov modulation of the arrival and service processes, superposition of K CPP (compound Poisson process) streams of (positive) customer arrivals, and a CPP of negative customer arrival stream in each of the modulating phases, a multiserver with c non-identical (can also be identical) servers, GE (generalised exponential) service times in each of the modulating phases and a buffer of finite or infinite capacity. Thus, the model can accommodate correlations of the inter-arrival times (of batches), and geometric as well as non-geometric batch size distributions of customers in both arrivals and services. The use of negative customers can facilitate modelling server failures, packet losses, load balancing, channel impairment in wireless networks, and in many other applications. An exact and computationally efficient solution of this new queue for steady state probabilities and performance measures is developed and presented. A non-trivial application of the new queue to the performance evaluation of a wireless communication system is presented, along with numerical results, to illustrate the efficacy of the proposed method. The use of negative customers is also demonstrated. The new queue, perhaps with further evolution, has the potential to emerge as a generalised Markovian node model.