Daniela Panno

A comparative analysis of fuzzy versus conventional policing mechanisms for ATM networks

In ATM networks, usage parameter control is required in order to ensure that each source conforms to its negotiated parameters. To this purpose, several policing methods, such as leaky bucket and window mechanisms, have been introduced in literature. However, traditional methods have proved to be inefficient in coping with the conflicting requirements of ideal policing, that is, a low false alarm probability and high responsiveness. This led us to explore alternative solutions based on artificial intelligence techniques, specifically, in the field of fuzzy systems. We propose a policing mechanism based on fuzzy logic that aims at detecting violations of the parameters negotiated. The main characteristics of the proposed fuzzy policer are simplicity and the capacity to combine a high degree of responsiveness with a selectivity close to that of an ideal policer. Moreover, it can easily be implemented in hardware, thus, enhancing both cost and processing performance. The reported simulation results show that the performance of our fuzzy policer is much better than that of conventional policing mechanisms.

Using fuzzy logic in ATM source traffic control: lessons and perspectives

Due to its capacity to capture human expertise and to formalize approximate reasoning processes, fuzzy logic can be a good answer to the many challenges of congestion control in ATM networks. The authors deal with the application of fuzzy logic to problems of usage parameter control and propose a simple mechanism which, avoiding complex mathematical calculations, guarantees low response times while remaining effective. The flexibility of the fuzzy control proposed is discussed with respect to the probability of facing various types of traffic sources, ranging from bursty to MPEG video.

A fuzzy buffer management scheme for ATM and IP networks

We address the relevant issue of managing traffic flows with different priorities in packet switched networks, namely ATM and IP networks. We consider a reference model in which two traffic flows with different priorities are multiplexed within the buffer of a cell-based switch. The solution we propose, based on the fuzzy system theory, is able to guarantee the QoS requirements of high-priority traffic flow, allowing at the same time the exploitation of unused buffer resources to accommodate low-priority traffic flow in order to maximize the total throughput. The performance assessment of the fuzzy scheme demonstrates that our solution outperforms other popular mechanisms, based on conventional logic, such as threshold and push out mechanisms.

Adaptive bandwidth allocation by hierarchical control of multiple ATM traffic classes

The authors introduce a control strategy for bandwidth management in asynchronous transfer mode (ATM) networks. A two-level hierarchy is defined, where one level performs fixed class-selective call admission control strategies that are periodically dynamically coordinated by a higher-level bandwidth allocation controller. Each admission controller decides to accept or refuse an incoming call on the basis of a class-selective rule designed to maintain a certain quality of service. A decision is taken according to the virtual capacity share that is assigned to the various service classes by the allocation controller. Bandwidth shares are periodically recomputed online by means of the constrained minimization of a cost function that takes cell loss probability and refused traffic into account. The control structure, the strategies, and the optimization algorithm used are described as well as the assumptions underlying the choices made. Initial simulation results are reported.<<ETX>>

A fuzzy expert system for usage parameter control in ATM networks

In ATM networks usage parameter control is required in order to ensure that each source conforms to its negotiated parameters. However, traditional methods, such as leaky bucket and window mechanisms, revealed themselves to be inefficient in coping with the conflicting requirements of the ideal policing. We propose a fuzzy expert system for usage parameter control. The control strategy is described through a set of fuzzy inferences which emulate the knowledge base that is typical of human expertize. The simulation results shown in the paper demonstrate that our fuzzy policer outperforms conventional policing mechanisms.

An efficient buffer management policy based on an integrated fuzzy-GA approach

This paper deals with a novel buffer management scheme based on evolutionary computing for shared-memory ATM switches. The philosophy behind it is adaptation of the threshold for each output logical queue to the real traffic conditions by means of a system of fuzzy inferences. The optimal fuzzy system is achieved using a systematic methodology based on genetic algorithms for membership-function selecting and tuning. This methodology approach allows the fuzzy system parameters to be automatically derived when the switch parameters vary, offering a high degree of scalability to the fuzzy control system. Its performance is very close to that of an ideal mechanism like the push-out mechanism, and at any rate much better than that of the threshold schemes based on conventional logic. In addition it is simple to implement and above all inexpensive when implemented using VLSI technology.

Hierarchical dynamic control of multiple traffic classes in ATM networks

A hierarchical control structure is proposed to ensure performance requirements and to maintain load balancing among different traffic classes at an ATM node. A two-level control hierarchy is defined, where one level performs fixed class-selective call admission control strategies that are periodically dynamically coordinated by a higher level bandwidth allocation controller. The call admission control rules are designed to maintain a certain grade of service, in terms of cell loss probability, given the buffer space and bandwidth (percentage of cells) assigned to each class. The assignment of buffers is performed off-line, whereas bandwidth shares are periodically recomputed on-line by the allocation controller, that attempts to minimize a cost function, accounting for overall cell loss and refused traffic. The bandwidth assignments obtained are passed to the call admission controllers, where they are used as parameters affecting the admission rules until the next intervention. The control structure, the strategies and the optimization algorithm used are described in detail, as well as the assumptions underlying the choices that have been made. Simulation results are reported and discussed.

Adaptive access control of multiple traffic classes in ATM networks

An admission control and bandwidth allocation strategy is applied to several traffic classes entering an ATM (asynchronous transfer mode) network through a statistical multiplexer. At the call level, incoming virtual calls are either accepted or refused on the basis of a class-selective control rule designed to maintain a certain grade of service. Each class is assigned a buffer partition and a virtual capacity share, which affect the parameters of the acceptance controller. Buffer space is assigned statistically with an offline procedure; on the other hand, bandwidth shares are periodically recomputed online at the cell level, by means of the (parametric) constrained minimization of a cost function, which takes cell loss probability and refused traffic into account. These quantities are computed by observing the number of refused, accepted, and active (i.e. possibly generating bursts) calls within the previous decision interval, and are assumed to be slowly varying with respect to the cell dynamics. In turn, the results of the optimization are used to adaptively adjust the parameters of the access controller.<<ETX>>

An integrated fuzzy-GA approach for buffer management

This paper deals with a novel buffer management scheme based on evolutionary computing for shared-memory asynchronous transfer mode (ATM) switches. The philosophy behind it is adaptation of the threshold for each logical output queue to the real traffic conditions by means of a system of fuzzy inferences. The optimal fuzzy system is achieved using a systematic methodology, based on genetic algorithms (GAs), which allows the fuzzy system parameters to be derived for each switch size, offering a high degree of scalability to the fuzzy control system. Its performance is comparable to that of the push-out (PO) mechanism, which can be considered ideal from a performance viewpoint, and at any rate much better than that of threshold schemes based on conventional logic. In addition, the fuzzy threshold (FT) scheme is simple and cost-effective when implemented using VLSI technology

Measurement-based coverage function for green femtocell networks

In this paper, we propose a self-optimized coverage function for LTE femtocells embedded in a macrocell area. Each Femto Base Station (FBS) adapts its pilot power, and thus the coverage, to the on-site traffic demand. Under low traffic conditions the FBSs, whose presence is not essential for the proper operation of the network, reside in a low power Listen Mode. In this way a relevant energy saving on entire femtocell network can be achieved. In a high-load scenario, FBSs dynamically create high capacity zones under interference constraints. This permits to improve system capacity and offload more traffic from the nearby macrocell and, in the same time, to minimize co-channel interference in the femtocell tier.