Data delivery in fragmented wireless sensor networks using mobile agents

In the past few years, research in Wireless Sensor Networks (WSN) has grown at an unprecented rate. This is due to the large number of potential applications and environments WSNs can be used in. Nodes in WSNs communicate in multihop fashion to deliver the sensory information to a central processing unit, such as a base station or a sink node. This form of communication requires a degree of network connectivity which might not be always achievable, either due to the sensor deployment strategy, or due to sensor node failure, which can be malicious, or otherwise. In this thesis, we study the problem of data delivery in disconnected WSNs. A special class of disconnected sensor networks called Fragmented wireless sensor networks (FWSN) is considered. A FWSN consists of several groups of connected sensor nodes that we call fragments . We propose a mobility based approach that exploits resource rich, in terms of power and buffer size, mobile agents that move in the network and operate as data relays between fragments to eventually deliver data to the base station. The movement of the mobile nodes and their role as relay stations is modeled using a closed queueing network approach, which is used to obtain steady state results. Building on these results, we derive the distributions of the fragment-to-fragment and fragment-to-sink delays. The results show that this model accurately captures the system behavior. Using the same model, the effect of the movement policy, the number and speed of mobile relays, and the service time at each fragment on the end-to-end delay has also been studied. The proposed queueing model can also be used to model other roles of the mobile nodes, including their roles as either data collectors or data sinks. We also study some practical issues, including mobility control in large networks and engineering the service time, i.e., the time that an MR spend in relaying data between fragments

Networks of queues models with several classes of customers and exponential service times

The main target of this paper is to present the Markov chain C that, not giving explicitly the queue lengths stationary probabilities, has the necessary information to its determination for open networks of queues with several classes of customers and exponential service times, allowing to overcome ingeniously this problem. The situation for closed networks, in the same conditions, much easier is also presented.info:eu-repo/semantics/publishedVersio

Stability criteria for controlled queueing networks

We give criteria for the stability of a very general queueing model under different levels of control. A complete classification of stability (or positive recurrence), transience and null-recurrence is presented for the two queue model. The stability and instability results are extended for models with N > 3 queues. We look at a broad class of models which can have the following features: Customers arrive at one, several or all of the queues from the outside with exponential inter arrival times. We often have the case where a arrival stream can be routed so that under different routing schemes each queue can have external arrivals, i.e. we assume we have some control over the routing of the arrivals. We also consider models where the arrival streams are fixed. We view the service in a more abstract way, in that we allow a number к of different service configurations. Under every such service configuration service is provided to some or all of the queues, length of service time can change from one service configuration to another and we can change from one configuration to another according two some control policy. The service times are assumed to be exponentially distributed. The queueing models we consider are networks where, after completion at one queue, a customer might be fed back into another queue where it will be served another time often under with a different service time. These feedback probabilities change with the service configurations. Our interest is in different types of control policies which allow us to change the routing of arrivals and configurations of the service from time to time so that the controlled queue length process (which in most cases is Markov) is stable. The semi-martingale or Lyapunov function methods we use give necessary and sufficient conditions for the stability classification. We will look at some two queue models with different inter arrival and service times where the queueing process is still Markov

The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks, Journal of Telecommunications and Information Technology, 2017, nr 4

Time synchronization between sensor nodes to reduce the end-to-end delay for critical and real time data monitoring can be achieved by cautiously monitoring the mobility of the mobile sink node in underwater wireless sensor networks. The Alive-in-Range Medium Access Control (ARMAC) protocol monitors the delay of sensitive, critical and real-time data. The idea evolves as it involves reduction in duty cycle, precise time scheduling of active/sleep cycles of the sensors, monitoring the mobility of the sink node with the selection of appropriate queues and schedulers. The model for the path loss due to attenuation of electromagnetic wave propagation in the sea water is explained. The three-path reflection model evaluating reflection loss from the air-water and watersand interfaces as a function of distance between sensors and water depth is introduced. The algorithms for effective path determination and optimum throughput path determination are elaborated. The results verify that implementation of the Alive-in-Range MAC protocol has reduced the total number of packets dropped, the average queue length, the longest time in queue, the peak queue length and the average time in queue significantly, making it relevant for critical and real-time data monitoring

Performance analysis of queueing systems with resequencing

2014 - 2015The service sector lies at the heart of industrialized nations and continues to serve as a major contributor to the world economy. Over the years, the service industry has given rise to an enor- mous amount of technological, scienti c, and managerial chal- lenges. Among all challenges, operational service quality, service efficiency, and the tradeoffs between the two have always been at the center of service managers' attention and are likely to be so more in the future. Queueing theory attempts to address these challenges from a mathematical perspective. Every service station of a queueing network is characterized by two major components: the external arrival process and the service process. The external arrival process governs the timing of service request arrivals to that station from outside, and the service process concerns the duration of service transactions in that station... [edited by author]XIV n.s