Tool supported modeling of sensor communication networks by using finite-source priority retrial queues

• Main Authors: Tamas Berczes, Janos Sztrik, Peter Orosz, Pascal Moyal, Nicolaos Limnios, Stylianos Georgiadis
• Format: Article
• Language: English
• Published: UT Press Publishing House 2012-06-01
• Series: Carpathian Journal of Electronic and Computer Engineering
• Subjects: Performance modeling; Finite-source retrial queues; Sensor networks; MOSEL
• Online Access: http://cjece.ubm.ro/vol/5-2012/4_Berczes.pdf
• ISSN: 1844-9689; 2343-8908

The main aim of the present paper is to draw the attention of the readers of this special issue to the modeling issues of sensor networks. The novelty of this investigation is the introduction of servers vacation combined with priority customers for finite-source retrial queues and its application to wireless sensor networks. In this paper we analyze a priority finite-source retrial queue with repeated vacations. Two types of priority customers are defined, customers with priority 1 (P1) go directly to an ordinary FIFO queue. However, if customers with priority 2 (P2) find the server in busy or unavailable state go to the orbit. These customers stay in the orbit and retry their request until find the server in idle and available state. We assume that P1 customers have non-preemptive priority over P2 customers. The server starts with a listening period and if no customer arrive during this period it will enter in the vacation mode. When the vacation period is terminated, then the node wakes up. If there is a P1 customer in the queue the server begin to serve it, and when there is no any P1 customer, the node will remain awake for exponentially distributed time period. If that period expires without arrivals the node will enter in the next sleeping period. All random variables involved in model construction are supposed to be independent and exponentially distributed ones. Our main interest is to give the main steady-state performance measures of the system computed by the help of the MOSEL tool. Several Figures illustrate the effect of input parameters on the mean response time.