Solon V. Carvalho

Spectrum allocation policy modeling for elastic optical networks

Today, optical transmission technologies are able to support 400Gbps over a single optical channel. However, this capacity cannot tit in the current fixed frequency grid optical spectrum. On the other hand, high rate optical channels have to co-exist with different ranges of line rates in order to serve heterogeneous bandwidth requests from variety of internet applications. Todays fixed rate and rigid frequency grid optical transmission systems cause over provisioning, where usually more spectral resources are provided than necessary. Recently, the concept of elastic optical networks has been proposed in order to reduce this waste of resources. In networks with such feature enabled, modulation parameters and central frequencies are not fixed and the resources can be allocated with a fine granularity, in contrast to the traditional WDM networks. This flexibility makes it possible to adapt to the granularity of the requested bandwidth without over provisioning. However, this heterogeneous bandwidth allocation may on the other hand result in fragmentation of spectral resources under dynamic traffic. In this study we quantify the fragmentation in elastic optical networks and calculate the blocking probability (BP) together with fragmentation on an elastic optical channel. In this regard, an analytical model based on a Markov Chain is developed under dynamic and flexible bandwidth traffic scenario. By using this analytical model different spectrum allocation policies are compared. A novel spectrum allocation policy is proposed which has lower BP and fragmentation ratio compared to the existing strategies.

Strategies for improving the modeling and interpretability of Bayesian networks

One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can point out the Bayesian networks as one of the most prominent when considering the easiness of knowledge interpretation achieved. Bayesian networks, however, present limitations and disadvantages regarding their use and applicability. This paper presents an extension for the improvement of Bayesian networks, treating aspects such as performance, as well as interpretability and use of their results; incorporating genetic algorithms in the model, multivariate regression for structure learning and temporal aspects using Markov chains.

On Proposing Statecharts to Specify Performance Models

This paper shows that Statecharts, a high-level specification technique, can be used to represent performance models. This is a powerful technique and is based on state-transition diagrams added with concepts of hierarchy and orthogonality to represent a system behavior. It is shown that Statecharts may conveniently be used to represent models with richness and clarity. Using an analytical approach the technique to determine performance measurements is provided. Three examples are presented and the results show Statecharts’ potential for representing systems for performance evaluation.

Technical Communication: Performance analysis of multi-service wireless network: An approach integrating CAC, scheduling, and buffer management

Traffic management (TM) mechanisms such as Call Admission Control (CAC), Scheduling, and Buffer Management (BM) play a key role in the design of multi-service wireless network by providing service differentiation from diverse applications and assigning the network resources (radio channels or buffer) according to the quality of service (QoS) requirements of each service class. We propose in this work two new models that integrate CAC, Scheduling, and BM in the design of multi-service wireless network. By presenting their Markovian models and their performance metrics, we investigate their respective design tradeoffs and compare their performance.

A Conformance Testing Process for Space Applications Software Services

Comprehensive tests for space applications software are costly but extremely necessary. These software must be reliable and produced within schedule and budget. In a tentative of make the space mission software development for space agencies and industries more costeffective, the European Committee for Space Standardization (ECSS) has been compiling a set of standards that specify the common core of some space application systems. Once the set of services is standardized, the conformance problem is raised. In this paper we present a testing process for standardized services, which is based on the IS-9646 standard for ISO protocol conformance testing. The process includes an approach to derive test and fault cases by combining conformance testing concepts with the software-implemented fault injection (SWIFI) technique. One advantage of this process is the generation of a re-usable

A queuing model for distributed scheduling in IEEE 802.16 wireless mesh networks

Summary The IEEE 802.16 standard for wireless broadband networks includes the mesh mode in its specifications, where network nodes interact to deliver packets from a client to a remote destination through intermediate nodes. This paper presents a study of the capacity of IEEE 802.16 wireless networks in mesh mode by using M/G/1/L queuing model that represents each network node by incorporating the features of the standard in order to calculate the average delay and throughput in the node. An iterative method integrates the calculation results at each node, obtaining the end-to-end delay from any node of the mesh to the Base Station. Because of multiple hops, a node far from the Base Station may have its flows damaged. To minimize this problem, we propose a criterion for a fair distribution of resources. We show the numerical results of the model which indicate a good fit when compared with simulation results. Copyright

An analytical framework for distributed coordinated scheduling in IEEE 802.16 wireless mesh networks

We present an analytical framework for the delay analysis of the distributed coordinated scheduling in the IEEE 802.16 Wireless Network in mesh mode. We designed a queuing model that expresses the network limits accurately. The queuing model is of the type M/G/1/L developed using Linear Algebraic Queuing Theory. After modeling one node, an iterative method is used to calculate the traffic flowing in the whole network. With this model, it is possible to calculate the end-to-end delay and the throughput limit of the link layer. An algorithm is presented that applies a strategy to provide fair resource sharing. The numerical results and simulations for different topologies show that the model is accurate and that the fairness strategy effectively reduces the end-to-end delay.

Modelling and Performance Evaluation of Wireless Networks

Integration between voice services and data services brought about new concepts in modelling and performance evaluation of wireless networks. In this paper it is proposed a new approach to deal with that putting together a formal method called Statecharts and a Continuous Time Markov Chain (CTMC). From the specification of the system made in Statecharts it is automatically generated a CTMC, and then evaluated the performance measures. The advantages of this technique are better representation of the behavior of the system without ambiguity and with consistency.

Analysis of traffic management mechanisms in wireless networks: Performance comparison study

Design of radio resource management (RRM) protocols in wireless networks plays a key role in the systems performance. By handling different service classes, RRM protocols must find out a trade off between the Quality of Service (QoS) requirements of real time applications and non-real time applications as well as between users and Service Providers expectations. In the current paper, Traffic Management (TM) mechanisms are combined to deal with the problem of designing multiservice RRM protocol. Particulary, we use Call Admission Control (CAC), Scheduling, and Buffer Management to ensure the QoS provisioning of the different service classes accordingly their QoS demands. Analysis of the results is outlined and the conclusions are drawn about their performance.

Strategies for improving the interpretability of Bayesian networks using Markovian time models and genetic algorithms

One of the main factors for the success of the knowledge discovery process is related to the comprehensibility of the patterns discovered by the data mining techniques used. Among the many data mining techniques found in the literature, we can point the Bayesian networks as one of most prominent when considering the easiness of knowledge interpretation achieved in a domain with uncertainty. However, the static Bayesian networks present two basic disadvantages: the incapacity to correlate the variables, considering its behavior throughout the time; and the difficulty of establishing the optimum combination of states for the variables, which would generate and/or achieve a given requirement. This paper presents an extension for the improvement of Bayesian networks, treating the mentioned problems by incorporating a temporal model, using Markov chains, and for intermediary of the combination of genetic algorithms with the networks obtained from the data.