Erol Gelenbe

A survey of autonomic communications

Autonomic communications seek to improve the ability of network and services to cope with unpredicted change, including changes in topology, load, task, the physical and logical characteristics of the networks that can be accessed, and so forth. Broad-ranging autonomic solutions require designers to account for a range of end-to-end issues affecting programming models, network and contextual modeling and reasoning, decentralised algorithms, trust acquisition and maintenance---issues whose solutions may draw on approaches and results from a surprisingly broad range of disciplines. We survey the current state of autonomic communications research and identify significant emerging trends and techniques.

Energy-Efficient Cloud Computing

Energy efficiency is increasingly important for future information and communication technologies (ICT), because the increased usage of ICT, together with increasing energy costs and the need to reduce green house gas emissions call for energy-efficient technologies that decrease the overall energy consumption of computation, storage and communications. Cloud computing has recently received considerable attention, as a promising approach for delivering ICT services by improving the utilization of data centre resources. In principle, cloud computing can be an inherently energy-efficient technology for ICT provided that its potential for significant energy savings that have so far focused on hardware aspects, can be fully explored with respect to system operation and networking aspects. Thus this paper, in the context of cloud computing, reviews the usage of methods and technologies currently used for energy-efficient operation of computer hardware and network infrastructure. After surveying some of the current best practice and relevant literature in this area, this paper identifies some of the remaining key research challenges that arise when such energy-saving techniques are extended for use in cloud computing environments.

Analysis and synthesis of computer systems

Basic Tools of Probabilistic Modelling The Queue with Server of Walking Type and Its Applications to Computer System Modelling Queueing Network Models Queueing Networks with Multiple Classes of Positive and Negative Customers and Product Form Solution Markov-Modulated Queues Diffusion Approximation Methods for General Queueing Networks Approximate Decomposition and Iterative Techniques for Closed Model Solution Synthesis Problems in Single-Resource Systems: Characterisation and Control of Achievable Performance Control of Performance in Mutliple-Resource Systems A Queue with Server of Walking Type.

Random neural networks with negative and positive signals and product form solution

We introduce a new class of random neural networks in which signals are either negative or positive. A positive signal arriving at a neuron increases its total signal count or potential by one; a negative signal reduces it by one if the potential is positive, and has no effect if it is zero. When its potential is positive, a neuron fires, sending positive or negative signals at random intervals to neurons or to the outside. Positive signals represent excitatory signals and negative signals represent inhibition. We show that this model, with exponential signal emission intervals, Poisson external signal arrivals, and Markovian signal movements between neurons, has a product form leading to simple analytical expressions for the system state.

On the Optimum Checkpoint Interval

One of the basic problems related to the efficient and secure operation of a transaction oriented file or database system is the choice of the checkpoint interval In this paper we show that the optimum checkpoint interval (i e the time interval between successive checkpoints which maximizes system avadabihty) is a function of the load of the system We also prove that the total operating time of the system (and not the total real time) between successive checkpoints should be a deterministic quantity in order to maximize the availability An explicit expression for this time interval Is obtained These results are a significant departure from previous work where load independent results have been obtained We also present a rigorous analysis of the queuelng process related to the requests for transaction processing arriving at the system, and prove the ergodiclty conditions for the system

On Approximate Computer System Models

A new treatment of the boundary conditions of diffusionapproximations for interconnected queueing systems is presented.The results have applications to the study of the performance ofmultiple-resource computer systems. In this approximation method,additional equations to represent the behavior of the queues whenthey are empty are introduced. This reduces the dependence of themodel on heavy traffic assumptions and yields certain results whichwould be expected from queueing or renewal theory. The accuracy ofthe approach is evaluated by comparison with certain known exact ornumerical results.

Stability and Optimal Control of the Packet Switching Broadcast Channel

The purpose of this paper is to analyze and optimize the behavior of the broadcast channel for a packet transmission operating in the slotted mode Mathematical methods of Markov chain theory are used to prove the inherent lnstablhty of the system If no control is apphed, the effective throughput of the system will tend to zero tf the population of user terminals ~s sufficiently large Two classes of control pohcles are examined, the first acts on admissions to the channel from active terminals, and the second modifies the retransmlss~on rate of packets In each case sufflc~ent conditions for channel stability are given. In the case of retransm~sslon controls it is shown that only pohcles which assure a rate of retransmlsslon from each blocked terminal of the form off = 1/n, where n is the total number of blocked terminals, will yield a stable channel It ts also proved that the optimal pohcy which maximizes the maximum achievable throughput wtth a stable channel IS of the formf = (1 - k)/n Simulations illustrating channel lnstabdlty and the effect of the opnmal control are prowded

Stability of the random neural network model

In a recent paper (Gelenbe 1989) we introduced a new neural network model, called the Random Network, in which negative or positive signals circulate, modeling inhibitory and excitatory signals. These signals can arrive either from other neurons or from the outside world: they are summed at the input of each neuron and constitute its signal potential. The state of each neuron in this model is its signal potential, while the network state is the vector of signal potentials at each neuron. If its potential is positive, a neuron fires, and sends out signals to the other neurons of the network or to the outside world. As it does so its signal potential is depleted. We have shown (Gelenbe 1989) that in the Markovian case, this model has product form, that is, the steady-state probability distribution of its potential vector is the product of the marginal probabilities of the potential at each neuron. The signal flow equations of the network, which describe the rate at which positive or negative signals arrive at each neuron, are nonlinear, so that their existence and uniqueness are not easily established except for the case of feedforward (or backpropagation) networks (Gelenbe 1989). In this paper we show that whenever the solution to these signal flow equations exists, it is unique. We then examine two subclasses of networks balanced and damped networks and obtain stability conditions in each case. In practical terms, these stability conditions guarantee that the unique solution can be found to the signal flow equations and therefore that the network has a well-defined steady-state behavior.

G-networks by triggered customer movement

The generalized queueing networks (G-networks) which we introduce in this paper contain customers and signals. Both customers and signals can be exogenous, or can be obtained by a Markovian movement of a customer from one queue to another after service transforming itself into a signal or remaining a customer. A signal entering a queue forces a customer to move instantaneously to another queue according to a Markovian routing rule, or to leave the network, while customers request service. This synchronised or triggered motion is useful in representing the effect of tokens in Petri nets, in modelling systems in which customers and work can be instantaneously moved from one queue to the other upon certain events, and also for certain behaviours encountered in parallel computer system modelling. We show that this new class of network has product-form stationary solution, and establish the non-linear customer flow equations which govern it. Network stability is discussed in this new context.

Steps toward self-aware networks

Network software adapts to user needs and load variations and failures to provide reliable communications in largely unknown networks.